Wind Power: Technology, Economics and Policies [1 ed.] 9781613241387, 9781606923238

Citation preview

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Renewable Energy: Research, Development and Policies Series

WIND POWER: TECHNOLOGY, ECONOMICS AND POLICIES

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

RENEWABLE ENERGY: RESEARCH, DEVELOPMENT AND POLICIES SERIES Ethanol and Biofuels: Production, Standards and Potential Wesley P. Leland (Editor) 2009 ISBN 978-1-60692-224-8 Renewable Energy Grid Integration: The Business of Photovoltaics Marco H. Balderas (Editor) 2009 ISBN 978-1-60741-324-0 Renewable Fuel Standard Issues Daniel T. Crowe (Editor) 2009. ISBN 978-1-60692-289-7

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wind Power: Technology, Economics and Policies Cedrick N. Osphey (Editor) 2009. ISBN 978-1-60692-323-8

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Renewable Energy: Research, Development and Policies Series

WIND POWER: TECHNOLOGY, ECONOMICS AND POLICIES

CEDRICK N. OSPHEY

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

EDITOR

Nova Science Publishers, Inc. New York

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2009 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA Available upon request

ISBN 978-1-61324-138-7 (eBook)

Published by Nova Science Publishers, Inc.  New York

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

CONTENTS Preface Chapter 1

Chapter 2

Chapter 3

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Chapter 4

vii Wind Power in the United States: Technology, Economic, and Policy Issues Jeffrey Logan and Stan Mark Kaplan

1

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2007 U.S. Department of Energy

47

20% Wind Energy by 2030. Increasing Wind Energy's Contribution to U.S. Electricity Supply U.S. Department of Energy

99

Wind and Hydropower Technologies Program. 2007 Peer Review Report U.S. Department of Energy

Index

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

335 387

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

PREFACE Rising energy prices and concern over greenhouse gas emissions have focused congressional attention on energy alternatives, including wind power. Although wind power currently provides only a small fraction of U.S. energy needs, it is growing more rapidly than any other electricity source. Wind energy already plays a significant role in several European nations, and countries like China and India are rapidly expanding their capacity both to manufacture wind turbines and to integrate wind power into their electricity grids. This book describes utility-scale wind power issues in the United States as well as background on wind energy, wind resources and technology, industry composition and trends, wind power economics and policy issues. Other policy questions, such as federal funding for wind research and development, and siting and permitting requirements, are also outlined. Chapter 1 - Rising energy prices and concern over greenhouse gas emissions have focused congressional attention on energy alternatives, including wind power. Although wind power currently provides only about 1% of U.S. electricity needs, it is growing more rapidly than any other energy source. In 2007, over 5,000 megawatts of new wind generating capacity were installed in the United States, second only to new natural gas-fired generating capacity. Wind power has become “mainstream” in many regions of the country, and is no longer considered an “alternative” energy source. Wind energy has become increasingly competitive with other power generation options. Wind technology has improved significantly over the past two decades. CRS analysis presented here shows that wind energy still depends on federal tax incentives to compete, but that key uncertainties like climate policy, fossil fuel prices, and technology progress could dominate future cost competitiveness. A key challenge for wind energy is that electricity production depends on when winds blow rather than when consumers need power. Wind’s variability can create added expenses and complexity in balancing supply and demand on the grid. Recent studies imply that these integration costs do not become significant (5-10% of wholesale prices) until wind turbines account for 15-30% of the capacity in a given control area. Another concern is that new transmission infrastructure will be required to send the wind-generated power to demand centers. Building new lines can be expensive and time-consuming, and there are debates over how construction costs should be allocated among end-users and which pricing methodologies are best. Opposition to wind power arises for environmental, aesthetic, or aviation security reasons. New public-private partnerships have been established to address more

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

viii

Preface

comprehensively problems with avian (bird and bat) deaths resulting from wind farms. Some stakeholders oppose the construction of wind plants for visual reasons, especially in pristine or highly-valued areas. A debate over the potential for wind turbines to interfere with aviation radar emerged in 2006, but most experts believe any possible problems are economically and technically manageable. Federal wind power policy has centered primarily on the production tax credit (PTC), a business incentive to operate wind facilities. The PTC is set to expire on December 31, 2008. Analysts and wind industry representatives argue that the on- again off-again nature of the PTC is inefficient and leads to higher costs for the industry. While there is often bipartisan support for the PTC in Congress, debate centers more fundamentally on how to offset its revenue losses. A federal renewable portfolio standard — which would mandate wind power levels — was rejected in the Senate in late 2007; its future is uncertain. If wind is to supply up to 20% of the nation’s power by 2030, as suggested by a recent U.S. Department of Energy report, additional federal policies will likely be required to overcome barriers, and ensure development of an efficient wind market. Chapter 2 - The U.S. wind industry experienced unprecedented growth in 2007, surpassing even optimistic projections from years past. This rapid pace of development has made it difficult to keep up with trends in the marketplace. Yet, the need for timely, objective information on the industry and its progress has never been greater. This report— the second of an ongoing annual series —attempts to meet this need by providing a detailed overview of developments and trends in the U.S. wind power market, with a particular focus on 2007. As with the previous edition, this report begins with an overview of key wind power development and installation-related trends, including trends in capacity growth, in turbine make and model, and among wind power developers, project owners, and power purchasers. It then reviews the price of wind power in the United States, and how those prices compare to the cost of fossil- fueled generation, as represented by wholesale power prices. Next, the report describes trends in installed wind project costs, wind turbine transaction prices, project performance, and operations and maintenance expenses. Finally, the report examines other factors impacting the domestic wind power market, including grid integration costs, transmission issues, and policy drivers. The report concludes with a brief preview of possible developments in 2008. This version of the Annual Report updates data presented in the previous edition, while highlighting key trends and important new developments from 2007. New to this edition is a section on the contribution of wind power to new capacity additions in the electric sector, data on the amount of wind in utility systems, a summary of trends in wind project size, a discussion of the quantity of wind power capacity in various interconnection queues in the United States, and a section that underscores domestic wind turbine manufacturing investments. A note on scope: this report concentrates on larger-scale wind applications, defined here as individual turbines or projects that exceed 50 kW in size. The U.S. wind power sector is multifaceted, however, and also includes smaller, customer-sited wind applications used to power the needs of residences, farms, and businesses. Much of the data included in this report were compiled by Berkeley Lab, and come from a variety of sources, including the American Wind Energy Association (AWEA), the Energy Information Administration (EIA), and the Federal Energy Regulatory Commission (FERC). The Appendix provides a summary of the many data sources used in the report. Data on 2007

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Preface

ix

wind capacity additions in the United States are based on preliminary information provided by AWEA; some minor adjustments to those data are expected. In other cases, the data shown here represent only a sample of actual wind projects installed in the United States; furthermore, the data vary in quality. As such, emphasis should be placed on overall trends, rather than on individual data points. Finally, each section of this document focuses on historical market information, with an emphasis on 2007; the report does not seek to forecast future trends. Chapter 3 - Energy prices, supply uncertainties, and environmental concerns are driving the United States to rethink its energy mix and develop diverse sources of clean, renewable energy. The nation is working toward generating more energy from domestic resources— energy that can be cost-effective, and replaced or “renewed” without contributing to climate change or major adverse environmental impacts. In 2006, President Bush emphasized the nation’s need for greater energy efficiency and a more diversified energy portfolio. This led to a collaborative effort to explore a modeled energy scenario in which wind provides 20% of U.S. electricity by 2030. Members of this 20% wind collaborative (see 20% Wind Scenario sidebar) produced this report to start the discussion about issues, costs, and potential outcomes associated with the 20% Wind Scenario. A 20% Wind Scenario in 2030, while ambitious could be feasible if the significant challenges identified in this report are overcome. This report was prepared by DOE in a joint effort with industry, government, and the Nation’s national laboratories (primarily the National Renewable Energy Laboratory and Lawrence Berkeley National Laboratory). The report considers some associated challenges, estimates the impacts and considers specific needs and outcomes in the areas of technology, manufacturing and employment, transmission and grid integration, markets, siting strategies, and potential environmental effects associated with a 20% Wind Scenario. In its Annual Energy Outlook 2007, the U.S. Energy Information Agency estimates that U.S. electricity demand will grow by 39% from 2005 to 2030, reaching 5.8 billion megawatthours (MWh) by 2030. To meet 20% of that demand, U.S. wind power capacity would have to reach more than 300 gigawatts (GW) or more than 300,000 megawatts (MW). This growth represents an increase of more than 290 GW within 23 years. The data analysis and model runs for this report were concluded in mid-2007. All data and information in the report are based wind data available through the end of 2006. At the time this report was written (2007), the U.S. wind power fleet numbered 11.6 GW and spanned 34 states. American wind farms are expected to generate an estimated 48 billion kilowatt-hours of wind energy in 2008, more than 1% of U.S. electricity supply. This capacity addition of 5,244 MW in 2007 exceeds the more conservative growth trajectory developed for the 20% Wind Scenario of about 4,000 MW/year in 2007 and 2008. The wind industry is on track to grow to a size capable of installing 16,000 MW/year, consistent with the latter years in the 20% Wind Scenario, more quickly than the trajectory used for this analysis. Chapter 4 - Objective review and advice from peers—peer review—provides Department of Energy (DOE) managers, staff, and researchers with a powerful and effective tool for enhancing the management, relevance, effectiveness, and productivity of all of the Office of Energy Efficiency and Renewable Energy (EERE) research, development, demonstration, deployment, and supporting business management programs. A peer review is defined as:

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

x

Preface A rigorous, formal, and documented evaluation process using objective criteria and qualified and independent reviewers to make a judgment of the technical/ scientific/business merit, the actual or anticipated results, and the productivity and management effectiveness of programs and/or projects.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The Wind Program peer review focused on technology application and acceptance activities that were planned, underway, or recently completed. The findings are considered by Wind Program managers, staff, and researchers in setting priorities, conducting operations, and improving projects. The DOE Wind Program peer review was conducted July 11-12, 2007, at the Denver Marriott West Hotel in Golden, CO. Presentations were given on specific technical projects within the Systems Integration, Market Policy and Analysis, Environmental and Siting, and Technology Acceptance Activities program areas. The following document is the peer review panel’s observations and findings, the response from the Wind Program to these, and supporting meeting materials including an agenda and participants list. In accordance with the DOE Peer Review Guide Section 6.0, peer reviewers provided both quantitative and narrative evaluations of the materials and projects presented at the peer review meeting. The comments herein are the most direct reflection of reviewers’ written evaluations, and where possible have been included verbatim.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

In: Wind Power: Technology, Economics and Policies ISBN 978-1-60692-323-8 Editor: Cedrick N. Osphey, pp. 1-46 © 2009 Nova Science Publishers, Inc.

Chapter 1

WIND POWER IN THE UNITED STATES: TECHNOLOGY, ECONOMIC, AND POLICY ISSUES* Jeffrey Logan and Stan Mark Kaplan

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Energy Policy Resources, Science, and Industry Division

Rising energy prices and concern over greenhouse gas emissions have focused congressional attention on energy alternatives, including wind power. Although wind power currently provides only about 1% of U.S. electricity needs, it is growing more rapidly than any other energy source. In 2007, over 5,000 megawatts of new wind generating capacity were installed in the United States, second only to new natural gas-fired generating capacity. Wind power has become “mainstream” in many regions of the country, and is no longer considered an “alternative” energy source. Wind energy has become increasingly competitive with other power generation options. Wind technology has improved significantly over the past two decades. CRS analysis presented here shows that wind energy still depends on federal tax incentives to compete, but that key uncertainties like climate policy, fossil fuel prices, and technology progress could dominate future cost competitiveness. A key challenge for wind energy is that electricity production depends on when winds blow rather than when consumers need power. Wind’s variability can create added expenses and complexity in balancing supply and demand on the grid. Recent studies imply that these integration costs do not become significant (5-10% of wholesale prices) until wind turbines account for 15-30% of the capacity in a given control area. Another concern is that new transmission infrastructure will be required to send the wind-generated power to demand centers. Building new lines can be expensive and time-consuming, and there are debates over how construction costs should be allocated among end-users and which pricing methodologies are best.

*

This is an edited, excerpted and augmented edition of a Congressional Research Service Report for Congress publication, Order Code RL34546, dated June 20, 2008.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

2

Jeffrey Logan and Stan Mark Kaplan

Opposition to wind power arises for environmental, aesthetic, or aviation security reasons. New public-private partnerships have been established to address more comprehensively problems with avian (bird and bat) deaths resulting from wind farms. Some stakeholders oppose the construction of wind plants for visual reasons, especially in pristine or highly-valued areas. A debate over the potential for wind turbines to interfere with aviation radar emerged in 2006, but most experts believe any possible problems are economically and technically manageable. Federal wind power policy has centered primarily on the production tax credit (PTC), a business incentive to operate wind facilities. The PTC is set to expire on December 31, 2008. Analysts and wind industry representatives argue that the on- again off-again nature of the PTC is inefficient and leads to higher costs for the industry. While there is often bipartisan support for the PTC in Congress, debate centers more fundamentally on how to offset its revenue losses. A federal renewable portfolio standard — which would mandate wind power levels — was rejected in the Senate in late 2007; its future is uncertain. If wind is to supply up to 20% of the nation’s power by 2030, as suggested by a recent U.S. Department of Energy report, additional federal policies will likely be required to overcome barriers, and ensure development of an efficient wind market.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

INTRODUCTION Rising energy prices and concern over greenhouse gas emissions have focused congressional attention on energy alternatives, including wind power. Although wind power currently provides only a small fraction of U.S. energy needs, it is growing more rapidly than any other electricity source. Wind energy already plays a significant role in several European nations, and countries like China and India are rapidly expanding their capacity both to manufacture wind turbines and to integrate wind power into their electricity grids. This report describes utility-scale wind power issues in the United States. The report is divided into the following sections: • • • • •

Background on wind energy; Wind resources and technology; Industry composition and trends; Wind power economics; and Policy issues.

Three policy issues may be of particular concern to Congress: •

•

Should the renewable energy production tax credit be extended past its currently scheduled expiration at the end of 2008, and, if so, how would it be funded? The economic analysis suggests that the credit significantly improves the economics of wind power compared to fossil and nuclear generation. Should the Congress pass legislation intended to facilitate the construction of new transmission capacity to serve wind farms? As discussed below, sites for wind facilities are often remote from load centers and may require new, expensive

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

•

3

transmission infrastructure. Texas and California have implemented state policies to encourage the development of new transmission lines to serve wind and other remote renewable energy sources. Legislation before the Congress would create a federal equivalent. Should the Congress establish a national renewable portfolio standard (RPS)? As discussed in the report, the economics of wind are competitive, but not always compelling, compared to fossil and nuclear energy options, and because wind power is dependent on the vagaries of the weather it is not as reliable as conventional sources. Some benefits of wind power cited by proponents, such as a longterm reduction in demand for fossil fuels, are not easily quantified. To jump-start wind power development past these hurdles, many states have instituted RPS programs that require power companies to meet minimum renewable generation goals. A national RPS requirement has been considered and, to date, rejected by Congress.

Other policy questions, such as federal funding for wind research and development, and siting and permitting requirements, are also outlined.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

BACKGROUND The modern wind industry began in the early 1980s when the first utility-scale turbines were installed in California and Denmark.1 Wind power then, as today, was driven by high energy prices, energy insecurity, and concern about environmental degradation. Early wind turbines, installed primarily at Altamont Pass outside of San Francisco in California, were primitive compared to today’s machines, and suffered from poor reliability and high costs. Like most new technology, early wind turbines had to go through a process of “learning by doing,” where shortcomings were discovered, components were redesigned, and new machines were installed in a continuing cycle. Today’s wind industry is notably different from that in the early 1 980s. Wind turbines now are typically 100 times more powerful than early versions and employ sophisticated materials, electronics, and aerodynamics. Costs have declined, making wind more competitive with other power generation options. Large companies and investment banks now drive most wind power activity compared to the early days of collaborating scientists, inventors, and entrepreneurs.2 From the mid-1980s to the late 1990s the U.S. wind industry stagnated due to low energy prices and the technology’s reputation for high cost and low reliability. But researchers continued to make improvements in the technology, driving down costs and improving reliability. New federal and state incentives encouraged developers to focus on the production of electricity at wind plants (also known as wind farms) and not just installing the equipment.3 In 1999, the U.S. industry began a period of rapid expansion, slowed occasionally by expiring federal incentives. Strong growth continues to this day, but whether that growth will continue if federal tax incentives expire at the end of 2008, as currently scheduled, is unclear.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

4

Jeffrey Logan and Stan Mark Kaplan

Source: U.S. Department of Energy, Wind Pow ering America Program, 2008. Figure 1. Cumulative Installed U.S. Wind Capacity.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The Rise of Wind Wind power is no longer an “alternative” source of energy in many regions of the country.4 It is the fastest growing source of new power generation in the United States. Between 2004 and 2007, installed wind turbine generating capacity increased by 150% (see Figure 1), and power generation from wind turbines more than doubled.5 Only the amount of new natural gas-fired generating capacity installed during this period exceeded that of wind.6 In 2007 the U.S. wind power industry brought over 5,000 megawatts of new generating capacity on-line, the largest annual increase ever by any country.7 The United States was not alone in strong growth for wind power in 2007: global installations rose by 27% to reach a total of 94,123 megawatts.8 Only Germany, with 22,247 megawatts, has more wind power capacity than the United States.9 Wind power’s growth is driven by a combination of the following: • • • • • •

improvements in wind energy technology, high and volatile fossil fuel prices, the federal wind production tax credit (PTC) incentive,10 state renewable portfolio standards (RPS),11 difficulty siting and financing new coal-fired power plants given expectation of a future carbon constraint, and consumer preference for renewable energy.

However, wind power still accounts for only about 1% of the total electricity generated in the United States.12 In some regions, a lack of transmission capacity is already beginning to constrain further growth in the wind power sector. And in states like Iowa, Texas, and Minnesota, where wind power has achieved a higher share of total electricity generation,

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

5

there are concerns that additional wind power could lead to higher prices or threaten grid security. Finally, there is currently a shortage of wind turbine components and a backlog in scheduling transmission interconnection, leading to delays and rising costs.

Benefits and Drawbacks of Wind Power There are frequently noted benefits and drawbacks to wind energy. Text Box 1 and Text Box 2 summarize selected problems and benefits, respectively, for wind power. Text Box 1. Selected Problems Facing Wind Power

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

• • • • • •

Power output depends on when the wind blows, not when users need electricity. New transmission infrastructure is often required. Depends on inconsistent federal incentives. Causes bird and bat deaths. Considered unsightly by some. Can interfere with radar in some cases.

Drawbacks A key challenge for wind energy is that electricity production depends on when and how consistently winds blow rather than when consumers most need power. This variability can create added expenses and complexity in balancing supply and demand on the grid.13 Several recent studies note that system integration costs do not become significant ($3 to $5 per megawatt- hour) until wind turbines account for 15-30% of the capacity in a control area.14 These apparently modest cost estimates have yet to be confirmed within the context of the U.S. electricity system. Another concern is that new transmission infrastructure may be required to send the wind- generated power to where it is needed. This can be an expensive and time-consuming effort. There are debates over how construction costs should be allocated among end users and which pricing methodologies are most economically efficient. Although transmission constraints face all new power generating options, wind power is especially handicapped because wind resources are often far from demand centers and do not usually use the full capacity of the transmission line due to the variable output. Texas is analyzing new transmission capacity to send wind-generator power from West Texas to the more populated northern and eastern sections of the state that could cost from $3 billion to over $6 billion.15 On a national scale, the U.S. Department of Energy (DOE) states that the most cost-effective way to meet a 20% wind energy target by 2030 would be by constructing over 12,000 miles of new transmission lines at a cost of approximately $20 billion.16 (See the section on Transmission Constraints for more on this issue.) Wind power is supported by federal and state incentives. In 2007, the Energy Information Administration (EIA) of DOE estimated that federal incentives for wind — primarily the PTC — totaled $724 million.17 In 2008, incentives could exceed $1 billion if wind generation expands from 32 billion kilowatt-hours to 48 billion kilowatt-hours as estimated by the American Wind Energy Association (AWEA), a national trade association promoting wind.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

6

Jeffrey Logan and Stan Mark Kaplan

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Costs to states using RPS policies are difficult to estimate because they are mandated requirements. Some believe that these are high costs to pay for a relatively small amount of energy. Others note that wind energy is an evolving technology and additional breakthroughs are possible. Many in the industry believe that the on-again, off-again nature of the federal PTC incentives harm rational development of the sector.18 Among some critics, wind power also results in unacceptable bird and bat deaths. To others, it is the visual impacts that wind turbines have on the landscape, or the noise that causes objection. Finally, increasingly tall wind turbines have interfered with military and airport radar. These issues are discussed in a later section of the report.

Benefits Wind turbines have no direct emissions of air pollutants, including oxides of sulfur and nitrogen, mercury, particulates, and carbon dioxide.19 They also offset the need to mine, process, and ship coal and uranium; drill and transport natural gas (and to a much lesser degree, oil); and construct or maintain hydroelectric dams. As noted previously, wind power contributed approximately 32 billion kilowatt-hours of electricity to the U.S. electricity grid in 2007; if that electricity had been generated using the average mix of power plants in the United States, an additional 19.5 million tons of carbon dioxide would have been released that year.20 Given rising prices for coal, natural gas, and nuclear fuel, power suppliers are drawn to the certainty that wind — while variable — is inexhaustible and has no fuel cost. By displacing coal-fired and gas-fired generation, wind power would reduce the demand for these fuels, perhaps moderating future prices and price volatility. Wind plants can catalyze rural development because farmers and ranchers receive royalty payments from wind developers who lease their land; the vast majority remains available for crops or grazing. Farmers and ranchers typically receive from project developers $2,0005,000 per year for each turbine on their land.21 The land taken out of production for wind turbine pads, access roads, and ancillary equipment reduces income for corn farmers, for example, by about $165 per turbine.22 Wind energy provides an additional source of revenue for local governments in the form of property taxes on wind plant owners. Wind turbines — unlike fossil and nuclear power plants — do not require water for cooling, a potentially important issue in areas with scarce water resources. Also, the lead time for planning and constructing wind plants is shorter than that for nuclear and coal, assuming transmission access is not an issue. Text Box 2. Selected Benefits of Wind Power • • • • • • •

Operations do not produce carbon dioxide or other air pollutants. Reduces power market exposure to volatile fuel prices. Assists rural development by giving landowners income from land leases. May provide more “green jobs” than other power generation options. Offers shorter construction lead time than some other options. Provides competitive electricity, especially at peak times. Does not require water for operations.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

7

Finally, wind power proponents argue that wind energy creates “green collar” manufacturing and field service jobs rather than traditional carbon-intensive employment.23 A study by Navigant Consulting in February 2008 estimated that 76,000 U.S. jobs in the wind industry were at risk if the PTC is not renewed well before its expiration in December 2008.24 It is unclear how many U.S. jobs are at risk if traditional power plants are not built.

WIND RESOURCES AND TECHNOLOGY This section begins with a description of how wind turbines work. It then provides information on wind resources in the United States, both on and offshore. Finally, the section outlines technology trends in the wind power sector.

Wind Power Fundamentals

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Unequal solar heating of the Earth’s atmosphere and oceans creates wind. Wind turbine blades, like airplane wings, produce lift when air passes over one side of their shaped surface more rapidly than another (Figure 2). This lift spins the turbine blades and rotor, which is connected to a generator through a gearbox inside the housing. The generator, and accompanying power conditioning equipment, then delivers electricity to the transmission grid at the appropriate voltage and frequency. The process is roughly opposite to a common household fan, which uses electricity to turn the blades and create air motion.

Source: How Stuff Works, 2006. Figure 2. Wind Power Aerodynamics.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

8

Jeffrey Logan and Stan Mark Kaplan

Wind turbines can stand alone or be integrated into wind farms with power generating capacity equaling that of a traditional power plant.25 This report focuses only on large, utilityscale wind turbines. Smaller, off-grid wind power applications are also growing rapidly, although their aggregate impact is limited.26

Physical Relationships The evolution of wind power technology and market development has been influenced by three physical relationships. First, a wind turbine’s power output varies with the cube of wind speed.27 Thus, all else held constant, if wind velocity doubles, power output increases eightfold. Wind power developers, therefore, face the challenge of finding where winds blow best. Winds at 250 feet in altitude are stronger and steadier than those closer to the ground; this factor explains why wind turbine towers are placed high in the air. Second, power output varies with the area swept out by the turbine blades during their rotation. Doubling a turbine blade’s length will yield a quadrupling of power output. Today’s utility-scale wind turbine blades are commonly 130 feet long or more in an attempt to harness more energy. Turbine manufacturers have devoted attention over the past two decades to finding materials strong and durable enough to handle the twisting forces that are transmitted from the longer blades through the rotor and gearbox in fluctuating winds. Finally, power output increases directly with air density. Density is typically higher in winter months and at low altitudes, and lower in summer months and at high altitudes. Winds near the cold Scandinavian seas, for example, contain more exploitable energy than those of the hot, high-altitude desserts of the American Southwest.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wind Resources Wind resources in the United States, and elsewhere, have been studied for decades. The National Renewable Energy Laboratory (NREL) has produced national and state wind resource maps that indicate areas with promising winds (Figure 3).28 “Excellent” winds mean those that average about 17 miles per hour or above at 150 feet in altitude. Additional mapping efforts characterize seasonal and even daily variations in average wind speed. After using these maps to identify promising regions, wind plant developers must still study and document local conditions carefully — often for 12 months or longer — to ensure potential financiers that revenue streams will be sufficient and stable. DOE estimates that total U.S. wind energy potential is over 10,000 billion kilowatt-hours annually — more than twice the total electricity generated from all sources in America today.29 While this potential is not realistically achievable, wind power advocates, supported by a recent DOE study, believe that wind power could realistically contribute 20% of the nation’s total electricity generation by the year 2030.30 The U.S. Great Plains states contain most of the best onshore wind resources.31 The main drawback to these rich wind resources is that they are located far from densely populated areas and thus require the construction of transmission lines to send the electricity to the load. Building these lines is often expensive, time consuming, and controversial.32

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

9

Source: National Renewable Energy Laboratory.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 3. U.S. Wind Resources Potential.

Offshore Wind The U.S. Department of the Interior (DOI) estimates that over 90,000 megawatts of wind resource potential lies off the coasts of New England and the Mid-Atlantic states in waters less than 100 feet deep.33 Offshore sites generally have higher quality winds and are located closer to population centers, but their development costs are significantly higher. Offshore wind projects have been slow to develop in the United States due to these high costs and public opposition. In Europe, a total of 1,099 megawatts of offshore wind had been installed by the end of 2007.34 The 420 megawatt Cape Wind project near Cape Cod, Massachusetts, is the largest proposed U.S. offshore wind project to date and is currently awaiting a permit from the DOI’s Minerals Management Service (MMS).35 During the 109th Congress, a debate erupted over the project’s safety, cost, and environmental impact.36 Cape Wind and other proponents say the project is a safe, clean way to develop renewable energy and create jobs. Opponents of the project have collaborated to create the Alliance to Protect Nantucket Sound. According to the Alliance, the project poses threats to the area’s ecosystem, maritime navigation, and the Cape Cod tourism industry. MMS released a Draft Environmental Impact Statement (EIS) for the Cape Wind project in March 2008.37 The draft EIS did not indicate any critical factors that could derail the project. A final EIS is expected later in 2008. Other offshore U.S. wind projects have been proposed in Delaware (Bluewater) and Texas (Galveston).38

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

10

Jeffrey Logan and Stan Mark Kaplan

Figure 4. Evolution of U.S. Commercial Wind Technology.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wind Power Technology Commercial, utility-scale wind turbines have evolved significantly from their early days in the 1980s and 1990s (Figure 4). They are larger, more efficient, and more durable. How wind technology evolves in the future could be influenced by congressional policy, both in research and development funding, and through regulatory frameworks that influence market behavior. Utility-scale wind turbines have grown in size from dozens of kilowatts in the late 1970s and early 1980s to a maximum of 6 megawatts in 2008.39 The average size of a turbine deployed in the United States in 2007 was 1.6 megawatts, enough to power approximately 430 U.S. homes.40 The average size of turbines continues to expand as units rated between 2 and 3 megawatts become more common. Larger turbines provide greater efficiency and economy of scale, but they are also more complex to build, transport, and deploy.

Types of Wind Turbines Industrial wind turbines fall into two general classes depending on how they spin: horizontal axis and vertical axis, also known as “eggbeater” turbines. Vertical axis machines, which spin about an axis perpendicular to the ground, have advantages in efficiency and serviceability since all of the control equipment is at ground level. The main drawback to this configuration, however, is that the blades cannot be easily elevated high into the air where the best winds blow. As a result, horizontal axis machines — which spin about an axis parallel to the ground rather than perpendicular to it — have come to dominate today’s markets.41 A simplified diagram of a typical horizontal axis wind turbine is shown in Figure 5. The blades connect to the rotor and turn a low-speed shaft that is geared to spin a higher-speed

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

11

shaft in the generator. An automated yaw motor system turns the turbine to face the wind at an appropriate angle.42 There are barriers to the size of wind turbines that can be efficiently deployed, especially at onshore locations. Wind turbine components larger than standard overthe-road trailer dimensions and weight limits face expensive transport penalties.43 Other barriers to increasingly large turbines include (1) potential for aviation and radar interference, (2) local opposition to siting, (3) erection challenges (i.e, expensive cranes are needed to lift the turbine hubs to a height of 300 feet or more), and (4) material fatigue issues. Some of these issues are discussed in more detail later.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Capacity Factor As noted above, a wind turbine’s power output depends on wind speed. Capacity factor — a measure of how much electricity a power plant actually produces compared to its potential running at full load over a given period of time — is a useful tool to summarize average annual wind availability and speed for wind projects. The capacity factor a wind plant achieves strongly influences the cost of electricity produced and the profitability of the project. (See Wind Power Economics section later in this report.)

Figure 5. Components in a Simplified Wind Turbine.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

12

Jeffrey Logan and Stan Mark Kaplan

Capacity factors for power generation technologies vary considerably. Nuclear plants run nearly continuously at full load and only shut down under normal conditions to be refueled. The industry-wide average capacity factor for U.S. nuclear power plants has been about 90% in recent years. Coal plants average a capacity factor of 70%, but individual plants can have a much higher or lower utilization rate. Wind plants, on the other hand, have capacity factors typically ranging from 20% to 40%.44 Wind turbines usually spin 65% to 90% of the time, but only at their full rated capacity about 10% of the time. A recent study pegs the typical capacity factor for wind turbines at 34%.45 Offshore wind turbines generally have higher capacity factors than onshore units because ocean winds are steadier than those over land. A high capacity factor helps lower a plant’s levelized, or annualized, cost of electricity (see section on Wind Power Economics). While a low capacity factor may result in relatively high costs per kilowatt-hour, a complete economic analysis would depend on when the electricity was produced. Since electricity is valued at different prices according to daily and seasonal demand profiles, when a wind turbine actually produces electricity can be as important as its overall capacity factor.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wind Research and Development Emphasis Future advances in wind turbine technology are likely to be evolutionary rather than revolutionary.46 According to the NREL, which carries out much of DOE’s wind research and development (R&D) program, current efforts to improve wind power technology and reduce costs includes: • • • • • • •

offshore turbine deployment, drivetrain (gearbox) innovation, blade design innovation, mechanical and power controls, low wind speed turbine development, manufacturing economies of scale, and system integration improvement.47

Another general area of R&D activity is in energy storage. Energy storage does not increase power output — in fact, energy conversion always results in lost power — but storage can make wind power available when it is most needed. Currently, most energy storage options are expensive and still under development. The most common energy storage method is hydroelectric pumped storage. During periods of strong winds and low power demand, wind turbine output can be used to pump water into a reservoir at a higher elevation. The water can be released through a hydroelectric generator later when the power is most needed. Many countries have only limited pumped storage capacity and may have already exploited what exists. In the United States, pumped storage accounts for several percent of conventional hydroelectric power generation,48 but probably does not have potential to grow significantly since many of the most economic sites have already been developed and the public opposes new large-scale hydroelectric projects. Other energy storage options such as compressed air energy storage and advanced batteries face technical hurdles and high costs. Public and private sector R&D is underway to bring down costs for these options, not just for the benefit of wind power, but other variable

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

13

energy sources as well.49 A technological breakthrough in one of these storage options could enhance the ability of wind energy to supply large quantities of electricity on demand, but whether such breakthroughs are forthcoming is unpredictable.50

WIND INDUSTRY COMPOSITION AND TRENDS

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Within the United States, Texas is now the dominant state for wind power, followed by California, Minnesota, Iowa, Washington, and Colorado. Total installed wind capacity for each state at the end of 2007 is shown in Figure 6. California’s early lead in wind power has been eclipsed by rapid growth in Texas. Wind power installations are also growing rapidly in the Pacific Northwest states of Washington and Oregon, as well as in Colorado, Minnesota, Iowa, Illinois, and the Dakotas. Most of these states have good wind resources, renewable portfolio standards, and local government proponents to help overcome construction barriers. These state and local incentives supplement the federal production tax credit incentive. The Southeastern region of the United States is noticeably empty of wind power projects due primarily to poor wind resources. This issue may also influence the region’s general opposition to a national RPS.

Figure 6. Installed Wind Capacity By State in 2007.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

14

Jeffrey Logan and Stan Mark Kaplan

Source: Ventyx Energy, the Velocity Suite. Data reportedly updated through June 5, 2008. Note: Data for wind plants in Hawaii and Alaska are not available for this map.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 7. Existing and Planned North American Wind Plants by Size.

A more detailed map showing the location of each existing and planned wind plant in North America by size is presented in Figure 7. Although planned wind projects far surpass the number of existing ones, there is no guarantee that they will all be constructed. Comparing wind resources from Figure 3 with existing and planned wind plants in Figure 7 shows significant potential to continue tapping some of the best wind sites in the upper Great Plains region. Limited transmission capacity is one of the reasons high-quality wind regions like this are not seeing greater wind plant development.

Wind Turbine Manufacturers and Wind Plant Developers The major wind turbine suppliers to wind plants in the United States include General Electric (GE) Wind, Siemens, Vestas, Mitsubishi, Suzlon, and Gamesa. The 2007 U.S. market share for each of these suppliers is shown in Figure 8. The GE 1.5 megawatt turbine was the most commonly installed unit in 2007. Vestas, Siemens, and Gamesa — European manufacturers with an increasing number of production facilities in the United States — account for a combined market share roughly equivalent to that of GE. Suzlon, an Indian manufacturer and the world’s fifth largest turbine producer, may face new challenges after having to recall many of the turbine blades it sold into the U.S. market due to premature cracking.51 Other new manufacturers are also entering the field. Clipper Windpower is gaining market share as manufacturing capacity grows for its new 2.5

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

15

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

megawatt turbines. According to the Global Wind Energy Council, two Chinese firms, Gold Wind and Sinovel, are also likely to enter international markets in 2009 with low-cost turbines. Because shipping large wind turbine parts is expensive, suppliers build manufacturing facilities close to where wind plants will be installed. According to AWEA, wind industry manufacturing facilities in the United States grew from a small base in 2005 to over 100 in 2007. New wind turbine component manufacturing facilities opened in Illinois, Iowa, South Dakota, Texas, and Wisconsin in 2007, while seven other facilities were announced in Arkansas, Colorado, Iowa, North Carolina, New York, and Oklahoma.52 Expanding production and operations in the United States is especially attractive to European companies given the current value of the euro to the dollar. Despite the expansion in turbine manufacturing facilities in the United States, Europe, and Asia, demand continues to exceed supply.53 Most wind plants in the United States are built and operated by independent power producers (IPPs), also known as merchant providers, that are not regulated utilities. IPPs have the most flexibility in taking advantage of the renewable tax incentives since regulated utilities cannot claim the renewable PTC. Still, investor- owned utilities do build and operate some wind plants; one estimate states that utilities built just over 10% of the total new capacity in wind electricity in 2007.54

Source: R. Wiser and M. Bolinger, Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends, U.S. DOE, p.10. Figure 8. U.S. Wind Turbine Market Share by Manufacturer in 2007.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

16

Jeffrey Logan and Stan Mark Kaplan

Dozens of companies from around the world develop and operate wind plants in the United States. Selected examples of active developers and operators in early 2008 include Acciona, AES, Babcock & Brown, Edison Mission, FPL Energy, Gamesa Energy, Horizon, Invenergy, John Deere, Noble Environmental, PPM Energy, and RES Americas.55 According to DOE, consolidation among companies remains strong, including the purchase of Horizon Wind by Energias de Portugal (from Portugal) and the acquisition of Airtricity North America by E.ON AG (from Germany).56 As countries deploy increasing quantities of wind capacity, new operational issues need to be addressed. Grid operators must become accustomed to dealing with the variability of wind in order to operate the system efficiently and reliably. Despite the near parity in total wind generating capacity among the top three countries, the United States has a much lower percentage penetration rate of actual wind power generation than Denmark, Spain, Portugal, Ireland, and Germany (Table 1). These European countries have gained experience operating their electricity grids at higher wind integration rates.

International Comparisons

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The United States led the world in wind power deployment until 1996 when it was surpassed by Germany (Figure 9). Strong U.S. growth in new wind capacity pushed the United States into the number two spot ahead of Spain in 2007, and the Global Wind Energy Council (GWEC) expects the United States to become the world leader in installed capacity again by the end of 2009.57

Source: Adapted from J. Dorn, "Global Wind Power Capacity Reaches 100,000 M egawatts," Earth Policy Institute, M arch 2004. Figure 9. Global Installed Wind Capacity By Country.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

17

Table 1. Wind Energy Penetration Rates by Country Country Denmark Spain Portugal Ireland Germany United States

Wind Energy Penetration Rate (%) 20 12 9 8 7 1

Source: R. Wiser and M. Bolinger, Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2007, U.S. DOE, May 2008, p. 6.

China has the most rapidly growing wind sector in the world, but started from a very low base. New wind power additions in China are dwarfed by the amount of new coal-fired power plant construction.58 Chinese leaders are reportedly considering a new wind power target of 100,000 megawatts by 2020, five-fold the previous target.59 The German experience with wind power is highlighted in Text Box 3. In summary, wind technology has evolved over the past two decades, resulting in larger, more reliable machines. Manufacturing capacity in the United States has expanded significantly. These advances have led to increasingly competitive wind electricity costs, the topic of the next section.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

WIND POWER ECONOMICS Numerous complex variables affect the economics of wind power. This section includes a financial analysis that compares the cost of building and operating wind plants with competing technologies (coal, natural gas, and nuclear power). The financial analysis provides an indicative picture of how the economics of wind compare with other bulk power sources. A comprehensive analysis for a specific project would take many other factors into consideration, including the cost of any necessary transmission upgrades and other options (e.g., purchased power or demand reduction).

Cost and Operating Characteristics of Wind Power Wind power is characterized by low variable costs and relatively high fixed costs. Wind turbines have, of course, no fuel costs, and minimal variable operations and maintenance (O&M) expense.60 In addition to having no direct expense for fuel, wind also does not incur the ancillary expenses associated with fossil fuel combustion, such as air pollution control equipment and allowances needed to comply with current law and, possibly, future carbon controls. Wind also does not incur the waste disposal costs associated with conventional generation, such as scrubber sludge disposal for coal plants and radioactive waste storage for nuclear plants.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

18

Jeffrey Logan and Stan Mark Kaplan

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Text Box 3. Focus on Wind Power in Germany Germany is the world leader in installed wind power capacity. Given the country’s relatively modest wind and solar resources, it has ambitious plans for renewable energy, including a goal that renewable energy meet 20% of total energy needs by 2020. The primary driver of wind power growth in Germany is the country’s “feed-in tariff” policy that gives producers of wind power a guaranteed constant minimum price over a maximum term of 20 years. The amount of the tariff depends on the location of the wind turbine and the specific year. The average 2007 payment was about 12.9 U.S. cents/kWh and is scheduled to slowly decline to about 10.9 cents/kWh by 2015.a Electricity in Germany is relatively expensive; the wind industry’s impact on overall electricity price is not clearly known.b Wind accounts for about 18% of installed capacity and generates 7% of the country’s electricity. Most of Germany’s wind farms lie in the northern Baltic coast region where wind resources are superior. Wind plants are widely deployed in Germany and few onshore areas with good wind resources remain to be developed. The shortage of onshore sites is leading Germany to replace older, less efficient wind turbines with larger, more powerful models. The shortage of high-quality onshore sites is also leading to an expansion of offshore wind plants. In 2006, the federal government passed a law stating that grid operators must bear the costs for connecting to offshore wind plants as soon as they are ready to begin producing power. At the end of 2007, Germany had installed only seven megawatts of offshore wind generating capacity, although it had hundreds of megawatts more under development. The German wind industry is not without critics. As elsewhere, critics state that wind energy depends on expensive subsidies, especially the feed-in tariff and grid connection requirements. As Germany is a relatively mature wind user, much of the countryside is dotted with wind plants. Some Germans oppose the visual impact these wind plants create and are concerned that they may impact the tourism industry. Finally, a recent study by the German Energy Agency claimed that wind power is an expensive way to lower carbon dioxide emissions compared with other options.c a

German Energy Agency, Planning of the Grid Integration of Wind Energy in Germany Onshore and Offshore up to the Year 2020, February, 2005. The exchange rate used in this conversion was 1.55 U.S. dollars per euro. b The impact of growing wind use on Germany’s electricity prices is obscured by larger restructuring and liberalization within the sector. B. Odent, “Les factures d’électricité germaniques se shootent à la libéralisation,” l’Humanité, June 29, 2007. c Project Steering Group, “Planning of the Grid Integration of Wind Energy in Germany Onshore and Offshore Up to the Year 2020,” German Energy Agency, March 2005.

As reported in 2005, the initial cost of wind turbines is about half of total wind plant development costs (Figure 10).61

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

19

Source: National Renew able Energy Laboratory, 2005.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 10. Component Costs for Typical Wind Plants.

Although wind plants have low variable costs, the fixed O&M costs are relatively high, and wind power plants are capital intensive.62 As with other generation technologies, the cost of building a wind plant has increased in recent years. The reported unit cost of wind projects constructed in the United States declined steadily through the 1990s and, according to one study, bottomed out at about $1,400 per kilowatt of capacity in the 2000-2002 time period.63 Subsequently, project costs have risen steadily and averaged over $1,700 per kilowatt in 2007. Higher input prices (steel, cooper, concrete), a shortage of skilled workers, unfavorable currency exchange, and shortages in key wind turbine components and manufacturing capacity explain much of the overall cost increase.64 Rapidly rising costs have also been experienced by all other utility-scale generation technologies.65 In the case of wind, some analysts believe that the lapses in the production tax credit contributed to boom-and-bust cycles in the sector and discouraged steadier investment in new production capacity.66

Wind Operation and System Integration Issues Operators try to maximize the power output from units with high fixed costs so that those costs can be spread over as many kilowatt-hours of electric generation as possible. This reduces the average cost of power from the unit and makes the unit’s power more economical for consumers (and more marketable if the unit is operating in a competitive market). Wind plants, however, cannot run as baseload units (i.e., continuously operating) because generation is subject to wind variability. Like solar power, wind is a source of variable renewable power that is dependent on daily, seasonal, and locational variations in the weather. Geographic diversity — that is, installing wind turbines over a large area — may compensate to some degree for local variations in wind conditions, but ultimately wind power cannot achieve the same degree of reliability or continuous operation as fossil or nuclear technology. The combination of the relatively low capacity factor of wind plants and high fixed costs drives up the cost of wind-generated electricity.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

20

Jeffrey Logan and Stan Mark Kaplan

The variable nature of wind power has an additional cost implication. Electric power systems must be able to reliably meet all firm customer loads at all times. For this reason power systems are built around generating technologies that are dispatchable and predictable — that is, units that can be reliably turned on or off, or have their output ramped up or down, as needed to meet changes in load. However, because a wind turbine is weather dependent it is not dispatchable or as predicable as a fossil or nuclear unit. As noted previously, energy storage can help address this shortcoming in wind energy, although it also results in higher costs. When a power system is dependent on only small amounts of wind generation to meet load, the variations in wind output can be absorbed by the system’s existing buffer capacity. This capacity is either fossil fuel, nuclear, or dispatchable renewable energy (e.g., hydroelectric, geothermal, and biomass). However, when wind constitutes a large part of the system’s total generating capacity, perhaps 10% to 15% or greater, the system must incur additional costs to provide reliable backup for the wind turbines. For example, in 2007 a utility in Montana built a gas-fired plant for the primary purpose of compensating for wind power variability.67 Various estimates have been made of the cost of integrating large blocks of wind capacity into a power system. Estimates for integration costs range from $1.85 to $4.97 per megawatthour.68 In 2008, the Bonneville Power Administration established a wind integration charge of $2.82 per megawatt-hour.69 (See Text Box 4 below for a description of a recent system integration issue in Texas.) In summary, wind power has the economic advantage of zero fuel costs and no costs for the pollution controls associated with the consumption of fossil and nuclear fuel. However, wind plants have relatively high fixed costs, and the plants cannot be operated as intensively as fossil or nuclear plants due to the variability of the wind. Wind variability also creates system integration costs at high levels of wind penetration. These cost disadvantages are partly offset by the federal renewable production tax credit (discussed below) and also, in effect, by state renewable portfolio standards that mandate the use of renewable power. Text Box 4. Electricity Curtailment Event in Texas A recent event in Texas serves to illustrate the challenge of integrating wind power into existing electricity grids. At 6:41 p.m. on February 26, 2008, the Electric Reliability Council of Texas (ERCOT, the manager of most of the electric power grid in Texas) activated its emergency electric curtailment plan due to low frequency on the electricity grid. The emergency measure cut power to customers who had agreed in advance to such action in order to prevent more serious grid problems from occurring. The frequency drop was caused by an unplanned shortfall in available generation sources (primarily wind) at the same time demand was increasing. According to ERCOT’s summary report, wind generator availability dropped from 1,700 megawatts three hours before the event to about 300 megawatts at the point the emergency procedures were activated. An action item ERCOT took from the event is to accelerate plans to implement an improved wind forecasting system. The summary report is available at [http:// nterchange.puc.state.tx.us/WebApp/Interchange/Documents/27706_1 14_5777 69.PDF].

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

21

Levelized Cost Comparison Although wind power is not dispatchable, it is often seen as a replacement or supplement for conventional baseload power plants. This is because when wind conditions are favorable a wind turbine is used like a baseload plant: the wind turbine is run at full load as continuously as possible. The following economic analysis therefore compares wind power to the primary baseload alternative technologies using coal, nuclear power, or natural gas. Each technology is described briefly in Text Box 5. The generation costs of these technologies and wind power are compared using the financial analysis technique of levelized costs, which summarizes the estimated lifetime costs of each system as a levelized (“annualized”) cost per megawatt-hour of generation. This analysis is for plants entering commercial service in 2015, and costs are measured in constant 2008 dollars. The financial methodology and the key assumptions concerning plant costs and operations are described in Appendix A. The current estimate of “overnight” construction costs for each technology — that is, the cost that would be incurred if a plant could be built instantly — are summarized below in Table 2, along with the assumed capacity factor. Table 2 also indicates the type of entity assumed to build each kind of plant. Coal and nuclear plants are assumed to be constructed by regulated utilities that have the financial resources and regulatory support to undertake these very large and expensive projects. The natural gas combined-cycle plant is assumed to be built by an independent power producer (IPP). IPPs generally prefer gas-fired projects because of their relatively low capital costs and risk profiles. The wind plant is also assumed to be an IPP project because regulated utilities normally cannot make use of the production tax credit.70

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Text Box 5. Description of Primary Power Generation Technologies •

•

•

Conventional (pulverized) coal. This is the conventional technology used in most existing coal-fired power plants. Coal is ground to a fine powder, and then burned in a boiler to create steam which drives a generator. Modern coal plants are equipped with environmental control equipment that can greatly reduce air emissions, with the exception of carbon dioxide. No pulverized coal plants — or, for that matter, any other kind of fossil-fueled power plant — have been built with carbon control technology. Natural Gas Combined Cycle. This is a standard technology widely used to generate electricity. Natural gas is burned in a combustion turbine (the same type of technology used in a jet engine) to rotate a generator and produce electricity. The waste heat, in the form of exhaust gases, from the combustion turbine is then captured and used to produce steam, which drives a second generator to produce more electricity. Combined cycle plants are relatively inexpensive to build and very efficient, but use expensive natural gas as the fuel. Nuclear Power. These plants use heat from nuclear fission to produce steam for power generation. This report uses projected costs and performance for next generation nuclear plants characterized, for example, by simplified designs and modularized construction techniques.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

22

Jeffrey Logan and Stan Mark Kaplan Table 2. Assumptions for Generating Technologies

Technology

Capacity Overnight Cost in 2008 (2008$ per Kilowatt of Capacity)

Assumed Factor

Wind Coal Nuclear Natural Gas

$1,900 $2,600 $3,700 $1,200

34% 85% 90% 70%

Type of Project Developer IPP Utility Utility IPP

Sources: Overnight capital costs estimated by CRS based on a review of published information on recent power projects. Capacity factor for coal plants is from Massachusetts Institute of Technology, The Future of Coal, 2007, p. 128. Natural gas plants are assumed to operate as baseload units with a capacity factor of 70%. Capacity factor for wind from California Energy Commission, “Comparative Costs of California Central Station Electricity Generation Technologies,” December 2007, Appendix B, p. 67. Nuclear plant capacity factor reflects the recent industry average performance as reported in EIA, Monthly Energy Review, Table 8.1. Also see Appendix A to this report.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Costs were estimated for six cases intended to illustrate some of the important economic, operational, and government incentive factors that influence the relative economics of wind power.71 The Base Case (Case 1) assumes continuation of the renewable production tax credit as currently formulated. It also assumes the nuclear plant qualifies for the nuclear production tax credit (at an effective rate of $12 per megawatt-hour)72 and loan guarantee program established by the Energy Policy Act of 2005. No carbon costs are assumed. The five alternative cases have the following characteristics (each is identical to the Base Case except as indicated): •

• •

•

•

Case 2: Reduced Incentives. The renewable production tax credit is assumed to terminate and is not renewed. The nuclear plant is assumed to not receive a loan guarantee.73 Case 3: High Natural Gas Prices. Natural gas prices are assumed to be 50% higher than the current EIA forecast used in the Base Case. Case 4: Carbon Costs. This case assumes the imposition of controls on carbon emissions from fossil fueled power plants. An illustrative allowance price of $25 per metric ton of carbon dioxide is assumed, escalating at a real rate of one percent per year, first imposed in 2013.74 Case 5: Wind Capacity Factor. This case assumes that the wind plant has a capacity factor of 44% rather than the 34% used in the Base Case. The higher capacity factor could be the result of improved technology or a better-than-average location.75 Case 6: Wind Integration Cost. A system integration charge is added to the cost of wind power. The assumed cost is the Bonneville Power Administration charge of $2.82 per megawatt- hour. This cost is assumed to remain constant in real dollar terms for the forecast period.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

23

Table 3. Economic Comparison of Wind Power with Alternatives (New Plants Entering Commercial Service in 2015, Levelized 2008$ Per Megawatt-hour and Percent Difference) Case

Levelized Cost of Power, 2008$ per megawatt-hour

$67 $74

Pulverized Nuclear Coal $64 $60 $64 $77

Natural Gas CC $63 $63

Wind Cost Advantage (Disadvantage) Comparison, Percent Difference Pulverized Nuclear Natural Coal Gas CC (4%) (10%) (6%) (14%) 4% (15%)

$67

$64

$60

$79

(4%)

(10%)

18%

$67 $50

$80 $64

$60 $60

$70 $63

19% 28%

(10%) 20%

4% 26%

$69

$64

$60

$63

(7%)

(13%)

(9%)

Wind Base Case Reduced Incentives High Natural Gas Prices Carbon Cost Higher Wind Capacity Factor Wind Integration Cost

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Sources and Methodology: See main body of the report and Appendix A. Notes: “CC” = Combined Cycle. “PTC” = production tax credit. These estimates are approximations subject to a high degree of uncertainty over such factors as future fuel and capital costs. The rankings of the technologies by cost are therefore also an approximation and should not be viewed as a definitive estimate of the relative cost-competitiveness of each option.

The results for the six cases are summarized below in Table 3. These estimates should be viewed as indicative and not definitive, and are subject to a high degree of uncertainty. As shown in the table: •

•

•

In Case 1, the levelized cost of wind power is a few percent higher than coal or gasfired power; given the range of uncertainty in the assumptions, the costs of these options are essentially similar. Nuclear power, which is assumed to benefit from the full range of federal incentives (a production tax credit and loan guarantee) is about 10% less expensive than wind and the least expensive of all the alternatives examined. In Case 2, reducing incentives significantly changes the results. If the renewable production tax credit is assumed to terminate, the cost of wind power increases by 10%. In this situation coal and gas have a 14% to 15% cost advantage over wind. However, the biggest impact of reducing incentives is on nuclear power. Assuming no loan guarantee, the cost of nuclear power increases by 28% (from $60 to $77 per megawatt-hour).76 In this situation, wind power’s cost (also without a production tax credit) is essentially similar (slightly lower) than nuclear power. Natural gas prices have historically been difficult to forecast and often underestimated.77 When gas prices are assumed to be 50% higher than in the Base Case, wind has an 18% cost advantage over gas-fired electricity (Case 3).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

24

Jeffrey Logan and Stan Mark Kaplan •

•

•

The imposition of an illustrative cost of $25 per metric ton of carbon dioxide on fossil-fired generation (Case 4) has the greatest impact on the relative competitiveness of wind with coal. The carbon cost takes coal from a 4% cost advantage over wind in the Base Case to a 19% disadvantage. The impact on gasfired power is significant, but less dramatic; gas goes from a 6% cost advantage to a 4% disadvantage when carbon costs are imposed.78 As discussed above, the combination of high capital costs and relatively low utilization rates, as measured by the capacity factor, creates a cost disadvantage for wind power. The importance of utilization is illustrated by Case 5, which assumes a wind capacity factor of 44%, compared to the 34% rate used in the Base Case. With a high capacity factor, wind has the lowest cost of the alternatives examined, and in particular is over 25% less costly than coal or gas. The final case (Case 6) assumes the imposition of a system integration charge of $2.82 per Mwh on wind generation. As Table 5 shows, costs under this case and the Base Case are similar.

In summary, the financial analysis suggests the following: •

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

• •

Given the Base Case assumptions, including continuation of the renewable production tax credit, the cost of wind power is comparable to coal and gas. The addition of an illustrative system integration charge, to account for large-scale wind penetration of a utility system, does not greatly change these results. Federal financial incentive policies have a significant impact on the financial analysis. The economics of wind are materially worse when the production tax credit is eliminated, and materially improved versus nuclear power when nuclear incentives are reduced. Improved technology or prime locations that allow wind projects to achieve high rates of utilization would significantly lower the cost of wind power. Assuming higher natural gas prices than the current EIA reference forecast, or the imposition of carbon charges on coal and gas, greatly enhances the cost competitiveness of wind.

WIND POLICY ISSUES This section of the report discusses government policy issues related to wind power. Some issues, such as permitting, are primarily state and local issues, but still may be a concern to congressional constituents. Other issues, such as the extension of the renewable production tax credit, are clearly federal issues.

Siting and Permitting Issues Like other electric power projects, wind energy projects built and operated in the United States must comply with applicable federal, state, and local requirements. Most wind energy

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

25

projects in the United States today are built on private land. As a result, local and state jurisdictions play the most important role in siting and permitting wind energy projects.79 These projects, however, usually must also meet certain federal requirements such as those in the Endangered Species Act (U.S.C.§1531-1544), Migratory Bird Treaty Act (U.S.C.§§703711), or Hazard Determination by the Federal Aviation Administration (FAA).80 Key siting and permitting issues are discussed below.81

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wildlife Constraints The main environmental objection to wind power is concern about bird and bat collisions with wind turbines. A National Academy of Sciences report states that, “Out of a total of perhaps 1 billion birds killed annually as a result of human structures, vehicles and activities, somewhere between 20,000 and 37,000 died in 2003 as a result of collisions with windenergy facilities.”82 Although this is a small percentage of total birds killed, the impact on particular species could be significant, especially if wind power continues to expand rapidly. Early wind turbines in California killed birds — especially raptors (hunting birds like hawks, eagles, and owls, some of which are protected under the Endangered Species Act) — and catalyzed opposition to wind power among bird enthusiasts.83 Although bird concerns remain, today’s turbines kill far fewer birds per unit of electricity generated than early models, especially in California.84 More recently, a relatively large number of bat fatalities have occurred at wind plants in West Virginia, Pennsylvania, New York, Alberta, and elsewhere.85 As a result, the wind industry and bat supporters formed a new organization, the Bats & Wind Energy Cooperative (BWEC) to fund studies designed to reduce bat mortality.86 Most experts concede that not enough is known about avian behavior to predict accurately what the affect on species will be if wind plants continue to expand. More collaborative study is underway to improve understanding of ways to minimize avian deaths.87 Potential mitigation options include: • • • • •

Stopping wind plants during key migratory periods, Painting blades to improve visibility, Avoiding locations, such as some mountain passes, already known to be migration corridors, Employing acoustic deterrents, and Moving selected turbines.

In addition to birds and bats, wildlife protection experts are studying how wind plant construction and operation affects terrestrial animals.88 Greater prairie chickens, for example, shy away from tall structures and may thus avoid living near wind plants.89 Federal agencies produced interim recommended guidelines in 2003 to assist project developers in considering and minimizing wildlife impacts.90 The DOI (through Fish and Wildlife Services, FWS) has established a Wind Turbine Guidelines Advisory Committee to advise the Secretary on developing effective voluntary measures to minimize impacts to wildlife related to land-based wind turbines.91 Early in the 1 10th Congress, Title VII of the New Direction for Energy Independence, National Security, and Consumer Protection Act (H.R. 3221) had required formation of such a committee, but the provision was removed

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

26

Jeffrey Logan and Stan Mark Kaplan

when the bill was merged with H.R. 6. As noted previously, Congress gave MMS primary authority over most aspects of siting off-shore wind plants through EPACT05.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Aesthetic and Social Issues Some landowners object to the visual impact that wind turbines create, especially near shore, mountainous, forested, protected, or other “valuable” areas. They view wind turbines as an unacceptable human or industrial fingerprint on lands that should remain natural. These objections are reflected in the offshore Cape Wind project, where opponents argue that natural “landscapes” (or seascapes, in this case) will be forever altered by the wind turbines. In addition to the visual impacts, there are other objections. All wind turbines produce mechanical and aerodynamic noise. Noise is thus a siting criterion for regulatory purposes. Early wind turbine models were often loud, especially downwind versions (blades behind the generator). Newer models are designed to minimize noise.92 Like visual aesthetics, wind turbine noise is often a matter of individual preferences and tolerances. For residences over 1 kilometer (0.6 miles) from a wind turbine, noise is generally not an issue. Shadow flicker, also know as shadow casting or blinking, is defined as alternating changes in light intensity caused by the moving blades casting shadows on the ground or objects. No flicker shadow will be cast when the sun is obscured by clouds or when the turbine is not rotating. This phenomenon can be annoying for residents who live very close to turbines. Computer simulations can help project developers position turbines so that flicker does not interfere with nearby residences. Shadow flicker generally does not affect residences located 10 rotor diameters or more (about 0.5 miles) from the turbine, except possibly early in the morning or late in the evening when shadows are long.93 Radar Issues Wind turbines can interfere with civilian and military radar at some locations. The potential interference occurs when wind turbines reflect radar waves and cause ghosting (false readings) or shadowing (dead zones) on receiving monitors. Radar interference thus raises national security and safety concerns.94 Concern over wind power and radar interference appeared to peak after Congress enacted the National Defense Authorization Act for Fiscal Year 2006 (P.L. 109-163) on January 3, 2006. Section 358 of the law required the Department of Defense (DOD) to submit to Congress within 120 days a report on the impacts of wind plants on military readiness. In response, DOD and the Department of Homeland Security (DHS) issued a temporary ruling on March 21, 2006, contesting the construction of any wind plant within radar line of sight of key military radar facilities until the report could be completed. AWEA stated in a June 2006 fact sheet that the de facto moratorium on billions of dollars worth of wind investment in parts of the country was inappropriate.95 The temporary ruling was clarified on July 10, 2006, in a joint DOD-DHS memo to the Federal Aviation Administration (FAA),96 calling for a case-by-case evaluation of the potential of wind projects on radar systems. Permitting resumed for most of the affected projects later that year. The DOD impacts report97 concluded that wind farms located within radar line of sight of an air defense radar have the potential to degrade the ability of that radar to perform its intended function. It also noted that currently proven mitigation options to completely prevent any degradation in primary radar performance of air defense radars are limited to methods that avoid locating wind turbines within their radar line of sight. DOD has initiated research

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

27

efforts to develop additional mitigation approaches that in the future could enable wind turbines to be placed within radar line of sight of air defense radars without impacting their performance.98 The FAA has oversight over any object that could have an impact on communications in navigable airspace, either commercial or military. DOD participates in the FAA review and evaluation of applications for potential impacts to its ability to defend the nation. The FAA requires that a Notice of Proposed Construction or Alteration be filed for any project that would extend more than 200 feet above ground level (or less in certain circumstances, for example if the object is closer than 20,000 feet away from a public-use airport with a runway more than 3,200 feet long).99 Although the DOD report noted limited options to “completely prevent” the degradation of any performance of air defense radar systems, DOE believes that practical solutions to radar interference are achievable. DOE notes that in the majority of cases, interference is either not present, is not deemed significant, or can be readily mitigated.100 Potential interference is highly site specific and depends on local features, type of radar, and wind plant characteristics. In most cases, radar interference can be corrected with software that deletes radar signals from stationary targets.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Transmission Constraints Transmission constraints are considered to be one of the biggest challenges facing the U.S. wind industry. The electricity grid in the United States is aging and overloaded in some regions, and new investment is required to ensure reliable, efficient transmission of electricity.101 Siting new transmission lines is an expensive, time consuming, and, often, controversial endeavor. Wind plant developers seek access to transmission capacity that allows them to send their electricity to market without having to build new lines, especially ones they need to pay for themselves. As noted previously, much of the nation’s best wind resources are located in remote, lightly populated areas where little transmission capacity exists. Demand centers, where the electricity is consumed, can be hundreds of miles away. A 2006 estimate puts the cost of new transmission lines at $1.5- $2 million per mile, and costs may have increased since.102 Transmission constraints occur in at least 3 ways: • • •

Limited transmission capacity, Scheduling difficulties in using existing lines, and Delays in interconnecting new wind power sources to the grid.

Limited Transmission Capacity Good sites for wind plants may be located in areas with limited available capacity on the transmission network, or the sites may be distant from any existing transmission lines. These capacity limits are the most fundamental constraint facing wind power project developers. It can take many years to plan and build new infrastructure. Wind plant developers who build in regions with limited or no transmission capacity may have to incur all construction costs for new or improved transmission infrastructure, an expensive proposition.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

28

Jeffrey Logan and Stan Mark Kaplan

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Texas is attempting to address its wind power transmission constraints through competitive renewable energy zones (CREZs), which attempt to optimize the linking of promising wind zones with demand centers and overcome the “chicken and egg” problem between wind plant developers and transmission providers. California is pursuing a similar CREZ policy, and other states, including New Mexico, Wyoming, and Colorado, are expanding transmission infrastructure to accommodate wind and other electricity options.103 Under the Energy Policy Act of 2005 (EPACT05), in certain cases where transmission congestion exists, the Federal Energy Regulatory Commission (FERC) may use federal override (eminent domain) authority to site new transmission lines when states have not acted to site those lines.104 Also under EPACT05, FERC is authorized to approve a funding plan for new transmission that would charge the new generator for all costs associated with interconnection rather than socializing the interconnection costs over all users of the transmission network.105 This type of funding could be cost prohibitive for small wind facilities. Finally, EPACT05 also directed FERC to establish incentive rules to encourage greater investment in the nation’s transmission infrastructure, promote electric power reliability, and lower costs for consumers by reducing transmission congestion. Order No. 679 allows a public utility to obtain incentive rate treatment for transmission infrastructure investments under certain conditions.

Scheduling Difficulties Transmission scheduling difficulties for wind power can result because the original rules for access to transmission capacity were not designed with intermittent sources, like wind, in mind. As the electricity sector slowly transforms itself from one with several hundred vertically integrated utilities with their own transmission control areas to one with a combination of regional transmission organizations (RTOs) and traditional control centers, the rules are being rewritten. Under the old rules, economic penalties were applied to generators that did not meet their day-ahead schedule requirements. For wind power, this occurred frequently since power output varies with wind variability, making scheduling difficult. Wind developers claim that the old rules discriminated against intermittent sources. In February 2007, FERC issued Order No. 890 to allow greater access to transmission lines for power generators of all types, including renewable energy projects.106 Rate pancaking (using the transmission facilities of multiple operators and incurring access charges from each) is another scheduling barrier for wind power in some regions. Only large transmission systems acting as a single network resource allow wind plants to avoid pancaking. FERC tried to promote a Standard Market Design order in 2002-2003 that might have provided greater uniformity to transmission pricing, but the effort was dropped due to opposition.107 Transmission Interconnection There are long queues (waiting lists) in some regions of the country for wind and other power plant developers to get approval to interconnect their new facilities with the grid.108 FERC issued Orders 2003 and 661 to clarify transmission interconnection requirements and help address potential discrimination.109 FERC is also preparing new guidance to help RTOs and independent system operators (IS Os) improve their queuing methodology.110 As long as

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

29

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

there is a shortage of transmission capacity, however, transmission interconnection queuing is likely to remain a problem.111

Federal Renewable Transmission Initiatives Two bills were introduced in the 1 10th Congress to address transmission of wind power and other renewable electricity. The Clean Renewable Energy and Economic Development Act (S. 2076), introduced in September 2007, would, among other things, amend the Federal Power Act to require national renewable energy zones. These zones would be specified areas that have the potential to generate 1,000 megawatts of electricity from renewable energy, a significant portion of which could be generated in a rural area or on federal land. The legislation would also require FERC to promulgate regulations to ensure that (1) specified public utility transmission providers that finance renewable electricity connection facilities in such zones recover incurred costs and a reasonable return on equity associated with the new transmission capacity; and (2) not less than 75% of the capacity of specified high-voltage transmission facilities and lines is used for electricity from renewable energy. The legislation was referred to the Committee on Energy and Natural Resources, which held a hearing on transmission issues for renewable electricity resources on June 17, 2008.112 A similar bill in the House, the Rural Clean Energy Superhighways Act (H.R. 4059), was introduced in November 2007. It would also focus on creating national renewable energy zones under certain conditions. It requires the President to identify, and provide public notice of, additional renewable energy trunkline facilities and network upgrades required to increase substantially the generation of electricity from renewable energy within each potential zone. It directs FERC to pass regulations to ensure that a public utility that finances transmission capacity to transmit electricity from renewable energy from a zone to an electricity consuming area recovers through transmission service rates all prudently incurred costs and a reasonable return on equity associated with construction and operation of the new transmission capacity. It also directs FERC, in specified circumstances, to permit a renewable energy trunkline built by a public utility located in a zone to be initially funded through transmission charges imposed upon (1) all the utility’s transmission customers in advance of significant generation interconnection requests; or (2) all the transmission customers of a Regional Transmission Organization (RTO) or independent system operator, if the trunkline is built in an area served by one or the other. Cost allocation procedures are prescribed for new projects and network upgrades. A federal power marketing administration, including the Tennessee Valley Authority (TVA), that owns or operates electric transmission facilities is required to finance a network upgrade or a renewable energy trunkline facility, if within a certain time frame no privately or publicly funded entity commits to do so.

Renewable Production Tax Credit The renewable production tax credit is an incentive to business developers of wind plants and some other renewable energy projects that produce electricity. For each kilowatt-hour of energy produced, a developer can apply for a credit against taxes. In 2007, the credit stood at 2.0 cents per kilowatt-hour for claims against 2006 taxes. According to industry members, the PTC expirations in 2000, 2002, and 2004 have had a negative impact on the U.S. wind industry’s ability to invest in new production facilities efficiently.113

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

30

Jeffrey Logan and Stan Mark Kaplan

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Proponents of extending the credit past 2008 argue that the PTC is merited because it corrects a market failure by providing economic value for the environmental benefits of “clean” energy sources. Also, they contend it helps “level the playing field,” noting that there is an even longer history of federal subsidies for conventional energy.114 For example, they point to the percentage depletion allowance for oil and natural gas that has been in place for many decades.115 Opponents of extending the production tax credit beyond the end of 2008 argue that generally there are no market failures that warrant special tax subsidies for particular types of renewable energy technologies. They argue further that subsidies generally distort the free market and that renewables should not get special treatment that exempts them from this principle. Also, regarding the concern about the environmental problems of conventional energy sources, they contend that the most cost-effective economic policy is to put a tax on the pollution from energy sources and let the free market make the necessary adjustments. Another argument against the PTC is that intermittent renewable energy production has a fluctuating nature that makes it less valuable than energy produced by conventional facilities.

PTC Eligibility: IOUs vs. IPPs The renewable PTC is not available to investor owned utilities (IOUs), although utilities do finance and own wind plants. Typically, independent power producers (IPPs) build, finance, and own wind plants and sell power to regulated utilities. There are a number of financing mechanisms where other providers of capital assist with financing wind plants in exchange for a portion of the tax credits. One question for Congress is whether utilities should become eligible to receive the PTC. Doing so would allow them to finance wind plants at a lower cost since the interest rates they pay on debt is lower than what an IPP pays. This would reduce the cost of wind power. One impact of allowing utilities to receive the renewable tax credits is that they could become more competitive at producing wind than IPPs. This could threaten the growth of the dozens of companies that now build wind plants. Specific PTC Legislative Options Congress is considering a variety of bills that would extend or modify selected renewable energy and energy efficiency tax incentives, including wind power. Title IV of the Alternative Minimum Tax and Extenders Tax Relief Act (S. 2886), which was introduced on April 17, 2008, would extend eight incentives. Title X of the Foreclosure Prevention Act (H.R. 3221), which passed the Senate on April 10, 2008, incorporates eight renewable energy and energy efficiency tax incentives from the Clean Energy Tax Stimulus Act (S. 2821). The Renewable Energy and Energy Conservation Tax Act (H.R. 5351), which passed the House on February 27, 2008, includes 16 incentives for renewable energy and energy efficiency. Features of these bills as they relate to the PTC for wind energy are summarized in Table 4. For updated status on legislation related to the PTC, see CRS Report RL33831, Energy Efficiency and Renewable Energy Legislation in the 110th Congress, by Fred Sissine, Lynn Cunningham, and Mark Gurevitz.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

31

Table 4. Selected Wind Power Tax Incentive Bills Compared

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Renewable Energy Production Tax Credit Extension Clean Renewable Energy Bonds Revenue Offsets Offsets from reduced oil and gas subsidies

H.R. 6049

Senate Substitute to H.R. 6049

H.R. 5984, H.R. 3221 (S. 2821)

1 year $2 billion

1 year $2 billion

1 year $400 million

yes

yes

no

Carbon Constraints and the PTC Climate change is almost certain to be an important topic in this and future Congresses. Most proposals call for a cap-andtrade system to reduce greenhouse gas emissions, although carbon taxes have also been proposed. Either way of constraining greenhouse gas emissions would create an effective cost on emissions. As noted in the Economics Section of this report, the Congressional Budget Office estimated the price of carbon dioxide allowances in S. 2091 at $30 per metric ton in 2013.116 While this legislation did not pass, future versions of legislation are likely to have similar price levels on carbon dioxide allowances. According to the levelized cost analysis presented earlier, such a price would make wind power about 19% less expensive than power derived from coal. Even without the PTC, wind power would be more competitive than coal. For natural gas, the impact of carbon allowance costs would be less dramatic, although the levelized cost of wind as modeled here would be noticeably lower than natural gas power. Congress will need to reconsider the policy goal of the renewable PTC if and when a carbon constraint is imposed. Alternatives to the PTC One alternative to the PTC is the renewable energy payment system, also known as the feed-in tariff. This policy is widely used in Europe (see Text Box 1 above for the German experience). It guarantees interconnection with the electricity grid and a premium price to renewable energy producers. Financing renewable energy projects under a renewable energy payment system is reportedly easier since there is a transparent source of revenue for a fixed period, usually 20 years. Even in Germany, however, critics claim that feed-in tariffs can be expensive. A summary of the Renewable Energy Jobs and Security Act, which incorporates renewable energy payments, was circulated in mid-June 2008.117

Renewable Portfolio Standards In the late 1 990s, many states began to restructure their electric utility industries to allow for increased competition. Some of these states established an RPS, in part, as a way to create a continuing role for renewable energy in power production.118 An RPS requires utilities to provide a minimum percentage of their electricity from approved renewable energy sources.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

32

Jeffrey Logan and Stan Mark Kaplan

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Some states without a restructured industry also adopted an RPS. The number of states with an RPS has grown steadily but without consistency — RPS requirements vary from state to state. In April 2008, FERC reported that 26 states and the District of Columbia had an RPS in place, collectively covering about 54% of the national electric load.119 Mandatory state RPS targets range from a low of 2% to a high of 25% of electricity generation. However, most targets range from 10% to 20% and are scheduled to be reached between 2010 and 2025. Most states include wind energy as an eligible resource and allow some form of trading between holders of the “renewable energy credits” that result from operating wind projects.120 Non-compliance penalties imposed by states range from about 1.0 to 5.5 cents per kilowatthour. Many states in the Southeast and Midwest regions do not have an RPS requirement. Several states have broadened their RPS provisions to allow certain energy efficiency measures and technologies to help satisfy the requirement.

Federal RPS Debate State RPS action has provided an experience base for the design of a possible national requirement. Proponents of a federal RPS contend that a national system of tradable credits would enable retail suppliers in states with fewer resources to comply at the least cost by purchasing credits from organizations in states with a surplus of low-cost production. Opponents counter that regional differences in availability, amount, and types of renewable energy resources would make a federal RPS costly and unfair. Efforts to include a federal RPS in the Energy Independence and Security Act (P.L. 110140) were unsuccessful. In June 2007, S.Amdt. 1537 to H.R. 6 proposed a 15% federal RPS. Senate floor action on the proposal triggered a lively debate, but the amendment was ultimately ruled non-germane. In that debate, opponents argued that a national RPS would raise retail electricity prices and disadvantage Southeastern states because they lack sufficient renewable energy resources to meet a 15% RPS requirement. RPS proponents countered that an Energy Information Administration (EIA) report indicated that the South has sufficient biomass power potential from existing plants to meet a 15% RPS without becoming “unusually dependent” on other regions.121 Further, EIA estimated that the 15% RPS would likely raise retail prices by slightly less than 1% over the 2005 to 2030 period, but would also be likely to cause retail natural gas prices to fall slightly over that period. In December 2007, the House approved H.R. 6 with a 15% RPS, but the Senate dropped the provision under threat of an Administration veto of the bill. The prospects for another federal RPS initiative in the 110th Congress are unclear.

CONCLUSIONS Wind power in the United States is growing rapidly. Although it currently supplies only about 1% of the country’s electricity needs, some states and regions have a much higher level of wind penetration. Furthermore, the amount of proposed new wind plants either under construction or waiting to be built is significant, and could soon make wind the largest source of new power supply at the national level. Continued expansion of wind power in the United States could be slowed by lack of transmission capacity and expiration of the federal renewable production tax credit. On the other hand, federal policy on climate change,

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

33

expected by many in the 111th Congress, would likely put a value on carbon dioxide emissions and give wind power additional advantages compared to coal- and natural gasbased electricity. Congress will need to carefully consider the interactive nature of energy and climate legislation when crafting future policy.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

APPENDIX. FINANCIAL ANALYSIS METHODOLOGY AND ASSUMPTIONS The financial analysis of power plant costs in this report estimates the operating costs and required capital recovery of each generating technology for an analysis period through 2050. Plant operating costs will vary from year to year depending, for example, on changes in fuel prices and the start or end of government incentive programs. To simplify the comparison of alternatives, these varying yearly expenses are converted to a uniform annual cost expressed as 2008 present value dollars.122 Similarly, the capital costs for the generating technologies are also converted to levelized annual payments. An investor-owned utility or independent power project developer must recover the cost of the investment and a return on the investment, accounting for income taxes, tax law (depreciation rates), and the cost of money. These variables are encapsulated within an annualized capital cost for a project computed using a “capital charge rate.” The financial model used for this study computes a project-specific capital charge rate that reflects, for example, the assumed cost of money and the applicable depreciation schedule. In the case of publicly owned utilities the return on capital is a function of the interest rate. A “capital recovery factor” reflecting each project’s cost of money is computed and used to calculate a mortgage-type levelized annual payment.123 Combining the annualized capital cost with the annualized cash flows yields the total estimated annualized cost of a project. This annualized cost is divided by the projected yearly output of electricity to produce a cost per Mwh for each technology. By “annualizing” the costs in this manner it is possible to compare alternatives with different year-to-year cost patterns on an apples-to-apples basis. Inputs to the financial model include financing costs, forecasted fuel prices, non-fuel operations and maintenance expense, the efficiency with which fossil-fueled plants convert fuel to electricity, and typical utilization rates (see Tables A.1, A.2, and A.3, below). Most of these inputs are taken from published sources, such as the Energy Information Administration’s (EIA) assumptions used to produce its 2007 and 2008 long-term energy forecasts. Overnight power plant capital costs — that is, the cost to construct a plant before financing expenses — are estimated by CRS based on a review of public information on recent projects. Government incentives are also an important part of the financial analysis. EPACT05 created or extended federal incentive programs for coal, nuclear, and renewable technologies. This study assumes the following incentives: •

A renewable energy production tax credit of 2.0 cents per kWh, with the value indexed to inflation. The credit applies to the first 10 years of a plant’s operation. The Base Case analysis assumes that the tax credit, which is currently scheduled to expire

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

34

Jeffrey Logan and Stan Mark Kaplan

•

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

•

at the end of 2008, will be extended (as has happened in the past). The credit is available only to wind power production that is sold to an unaffiliated third party. Under most circumstances this requirement effectively limits the production tax credit to independent power producers. A utility that owns a wind plant and uses the power to serve its own load would not qualify.124 The credit is currently available to new wind, geothermal, and several other renewable energy sources. New solar energy systems do not qualify, and geothermal systems can take the production tax credit only if they do not use the renewable investment tax credit (discussed below). A nuclear energy production tax credit for new advanced nuclear plants of 1.8 cents per kWh. The credit applies to the first eight years of operation. Unlike the renewable production tax credit described above, the nuclear credit is not indexed to inflation and therefore drops in real value over time. This credit is subject to several limitations: • It is available to plants that begin construction before January 1, 2014, and enter service before January 1, 2021. • For each project the annual credit is limited to $125 million per thousand megawatts of generating capacity. • The full amount of the credit will be available to qualifying facilities only if the total capacity of the qualifying facilities is 6,000 megawatts or less. If the total qualifying capacity exceeds 6,000 megawatts the amount of the credit available to each plant will be prorated. For example, EIA assumes in its 2007 Annual Energy Outlook that 9,000 megawatts of new nuclear capacity qualifies; in this case the credit amount drops to 1.2 cents per kWh.125 The Base Case for this study follows EIA in using the 1.2 cent per kWh assumption for the effective value of the credit. Loan guarantees for carbon-control technologies, including nuclear power. Under final Department of Energy (DOE) rules the loan guarantees can cover up to 80% of the cost of a project. Guarantees are made available based on a case-by-case evaluation of applicants and are dependent on congressional authority (in April 2008, the Department of Energy announced plans to solicit up to $18.5 billion in loan guarantee applications for nuclear projects126). Entities receiving loan guarantees must make a “credit subsidy cost” payment to the federal treasury that reflects the net anticipated cost of the guarantee to the government, including a probability of default. The guarantees are, under current rules, unlikely to be available to public power entities.127 Energy Investment Tax Credit. Tax credits under this program are available to certain renewable energy systems, including solar and geothermal electricity generation, and some other innovative energy technologies. Wind energy systems do not qualify. The credit is 10% for systems installed after January 1, 2009. Geothermal projects that take the investment tax credit cannot take the renewable production tax credit.128

The results of the analysis are shown in the main body of the report. Note that these estimates are approximations subject to a high degree of uncertainty over such factors as future fuel and capital costs. The rankings of the technologies by cost are therefore also an approximation and should not be viewed as a definitive estimate of the relative cost-

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

35

competitiveness of each option. Also note that site-specific factors would influence an actual developer’s choice of generating technologies. For example, coal may be less costly if a plant is close to coal mines, and the economics of wind depend in part on the strength and consistency of the wind in a given area. Table A.1. Base Case Financial Factors Item Value Representative Bond Interest Rates Utility Aa 2010: 6.8% 2015: 7.0% 2020: 7.0% IPP High Yield 2010: 9.8% 2015: 10.0% 2020: 10.0% Public Power Aaa 2010: 5.1% 2015: 5.4% 2020: 5.4% Corporate Aaa 2010: 6.3% 2015: 6.5% 2020: 6.5%

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Cost of Equity — Utility Cost of Equity — IPP Debt Percent of Capital Structure

14.00% 15.19%

Utility: 50% IPP: 60% Utility or IPP with federal loan guarantee: 80% POU: 100% Federal Loan Guarantees Cost of equity 1.75 percentage premium for entities points using 80% financing. Credit Subsidy Cost 12.5% of loan value Long-Term Inflation Rate (change in the implicit price deflator) Composite Federal/State Income Tax Rate

1.9%

38%

Sources and Notes When available, interest rates for investment grade bonds with a rating of Baa or higher (i.e., other than high yield bonds) are Global Insight forecasts. When Global Insight does not forecast an interest rate for an investment grade bond the value is estimated based on historical relationships between bond interest rates (the historical data for this analysis is from the Global Finance website). High yield interest rates are estimated based on the differential between Merrill Lynch high yield bond indices and corporate Baa rates, as reported by WSJ.com (Wall Street Journal website). California Energy Commission, “Comparative Cost of California Cental Station Electricity Generating Technologies,” December 2007, Table 8. Northwest Power and Conservation Council, “The Fifth Northwest Electric Power and Conservation Plan,” May 2005, Table I-1.

Congressional Budget Office, Nuclear Power’s Role in Generating Electricity, May 2008, web supplement (“The Methodology Behind the Levelized Cost Analysis”), Table A.5 and page 9. Global Insight

EIA, National Energy Modeling System Documentation, Electricity Market Module, March 2006, p. 85.

Notes: EIA = Energy Information Administration; IOU = Investor Owned Utility; POU = Publicly Owned Utility; IPP = Independent Power Producer. For a summary of bond rating criteria see [http://www.bondsonline.com/ Bond_Ratings_Definitions.php]. “High yield” refers to bonds with a rating below Baa.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

36

Jeffrey Logan and Stan Mark Kaplan Table A.2. Base Case Fuel and Allowance Price Forecasts Delivered Fuel Prices, Constant 2008$ per Million Btus Coal Natural Gas Nuclear Fuel

2010 2020 2030 2040 2050

$1.93 $1.80 $1.87 $1.96 $2.06

$7.51 $6.41 $7.48 $9.17 $11.24

$0.58 $0.67 $0.67 $0.65 $0.63

Air Emission Allowance Price, 2008$ per Allowance Sulfur Nitrogen Dioxide Oxides $249 $2,636 $1,074 $3,252 $479 $3,360 $158 $3,180 $52 $3,009

Sources: Forecasts are from the assumptions to the Energy Information Administration’s 2008 Annual Energy Outlook, which assumes implementation of current law and regulation. The original values in 2006 dollars were converted to 2008 dollars using the Global Insight forecast of the change in the implicit price deflator. The EIA forecasts are to 2030; the forecasts are extended to 2050 using the 2025 to 2030 growth rates. The sulfur dioxide and nitrogen oxides allowance forecasts are for the eastern region of the United States (allowance prices are expected to vary regionally under the Clean Air Interstate Rule). Note: Btu = British thermal unit.

Wind

Onshore

$1,900

50

Coal

Supercritical Pulverized Coal Combined Cycle

$2,577

Generation III/III+

Natural Gas Nuclear

Capacity Factor

Fixed O&M, 2008$ per Megawatt

Variable O&M Cost, 2008$ per Mwh

Heat Rate for Units Entering Service in 2015 (Btus per kWh)

Capacity (Megawatts)

Overnight Construction Cost for Units Entering Service in 2015, 2008$ per kilowatt

Technology

Energy Source

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table A.3. Power Plant Technology Assumptions

$0.00

$30,921

34%

600

Not Applicable 8,742

$4.46

$28,100

85%

$1,186

400

6,506

$1.95

$11,936

70%

$3,682

1,350

10,400

$0.48

$69,279

90%

Sources: Heat rates, O&M costs, and nominal plant capacities are from the assumptions to EIA’s 2007 and 2008 Annual Energy Outlooks. Capital cost estimates are based on a CRS review of public information on current projects. Capital costs and heat rates are adjusted based on the learning rates used by EIA in the Annual Energy Outlook. EIA costs are adjusted to 2008 dollars using Global Insight’s forecast of the implicit price deflator. Capacity factor for coal plants is from Massachusetts Institute of Technology, The Future of Coal, 2007, p. 128. Natural gas plants are assumed to operate as baseload units with a capacity factor of 70%. Capacity factor for wind from California Energy Commission, “Comparative Costs of California Central Station Electricity Generation Technologies,” December 2007, Appendix B, p. 67. Nuclear plant capacity factor reflects the recent industry average performance as reported in EIA, Monthly Energy Review, Table 8.1. Notes: kWh = kilowatt-hour; Mwh = megawatt-hour.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

37

ENDNOTES

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

1

T. Gray, Proceedings of the Wind Energy and Birds/Bats Workshop: Understanding and Resolving Bird and Bat Impacts, American Wind Energy Association and American Bird Conservancy, September 2004, p. 6. 2 R. Wiser and M. Bolinger, Annual Report on U.S. Wind Power Installation, Cost and Performance Trends: 2007, U.S. Department of Energy (DOE), May 2008, p.14. 3 Investment tax credits in the 1980s offered incentives for the installation of wind equipment. They did not reward wind project developers for actually generating electricity. From the 1990s through today, production tax credits have encouraged builders to maximize the output of wind electricity since they earn credits for each kilowatt-hour generated. 4 This statement is supported by the economic analysis presented later in the report; by the fact that wind accounts for over 6% of total in-state electricity generation in Minnesota, Iowa, Colorado and South Dakota; and by the amount of proposed wind power projects under development (225,000 megawatts) in 2007 compared to all other power plants (212,000 megawatts) combined. See R. Wiser and M. Bolinger, Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2007, DOE, May 2008, pp. 710. 5 Electric generating capacity, measured in watts, is an expression of instantaneous power output. Electricity generation is measured in watt-hours and is an expression of energy produced over time. For example, a 1,000 watt generator that operates all day would produce 24,000 watt-hours (24 kilowatt-hours) of energy. Prefixes kilo (thousand), mega (million), giga (billion), and tera (trillion) are often used with these units. Capacity references are from: Energy Efficiency and Renewable Energy, “Wind Powering America Program,” DOE, January 2008. [http://www.eere.energy.gov/windandhydro/ windpoweringamerica/wind_installed_capacity.asp]. Generation references are from: Energy Information Administration (EIA), Supplement to the Electric Power Monthly March 2008, Table ES. 1.B, DOE, April 2008; and EIA, Electric Power Monthly March 2005, Table ES.1.B., DOE, April 2005. 6 New wind plants accounted for roughly 30% of total new power plant capacity installed in the United States in 2007. “Installed U.S. Wind Power Capacity Surged 45% in 2007,” American Wind Energy Association, January 17, 2008. 7 Global Wind 2007 Report, Global Wind Energy Council, 2008, p.64. 8 Global Wind 2007 Report, Global Wind Energy Council, 2008, p. 6. 9 Global Wind 2007 Report, Global Wind Energy Council, 2008, pp.8-10. 10 The PTC is an incentive for business developers of wind farms and other renewable energy projects that produce electricity. It is discussed in the Policy Issues section later in this report. Also see CRS Report RL34 162, Renewable Energy: Background and Issues for the 110th Congress, by Fred Sissine. 11 Twenty-six states and the District of Columbia currently have mandatory RPS programs, requiring utilities to provide a minimum percentage of their electricity from approved renewable energy sources. Five others have non-binding goals. These numbers are reported by the Federal Energy Regulatory Commission (FERC) and can be accessed at [http://www.ferc.gov/market-oversight/mkt-electric/overview/elec-ovr-rps.pdf].

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

38

Jeffrey Logan and Stan Mark Kaplan

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

12

Wind farms in the United States generated approximately 32 billion kilowatt-hours in 2007 compared to total power sector generation of 4,160 billion kilowatt-hours. Energy Information Administration (EIA), Electric Power Monthly, DOE, March 2008 Edition, Table ES 1.B. The American Wind Energy Association forecasts that the U.S. wind industry will generate 48 billion kilowatt-hours of electricity in 2008. 13 These issues are further discussed in the Wind Operation and Systems Integration Issues section of this report. 14 This is about 5-10% of the price of typical wholesale electric power, according to CRS calculations. R. Wiser and M. Bolinger, Annual Report on U.S. Wind Power Installation, Cost and Performance Trends: 2006, U.S. DOE, May 2007, p. 20. 15 “ERCOT Files Wind Transmission Options with Commission,” Electric Reliability Council of Texas (ERCOT) Press Release, April 2, 2008. 16 Energy Efficiency and Renewable Energy, 20% Wind Energy by 2030: Increasing Wind Energy’s Contribution to U.S. Electricity Supply, U.S. DOE, May 2008, p. 95. 17 EIA, Federal Financial Interventions and Subsidies in Energy Markets 2007, U.S. DOE, April 2008, Table ES5. 18 M. Barradale, “Impact of Policy Uncertainty on Renewable Energy Investment: Wind Power and PTC,” U.S. Association for Energy Economics Working Paper No. 08-003, January 2008. 19 Wind power does have “lifecycle emissions” associated with the materials that go into turbine and transmission line construction, operation and maintenance activities, and decommissioning. A study by the International Energy Agency estimated lifecycle carbon dioxide emissions for wind power at 7-9 grams of CO2 per kilowatt-hour. For comparison, coal- and natural gas-fired plants released 955 and 430 grams per kilowatthour, respectively. International Energy Agency, Benign Energy?: The Environmental Implications of Renewables, Table 3-1 and 3-2, 1998. 20 CRS calculation based on EIA data for 2006 and estimates for 2007. EIA, Electric Power Monthly, U.S. DOE, April 15, 2008, Table ES 1.B. For comparison, total U.S. electric power sector emissions of carbon dioxide in 2006 were over 2,500 million tonnes. EIA, Electric Power Annual, U.S. DOE, Table 5.1, October 2007. 21 “Wind Power’s Contribution to Electric Power Generation and Impact on Farms and Rural Communities,” Government Accountability Office, GAO-04-756, September 2004, p. 1. 22 According to the U.S. Department of Agriculture (USDA), projected revenue in 2008-09 for corn grown in the United States is $846 per acre. (See World Agricultural Supply and Demand Estimates, USDA, May 9, 2008, p. 12.) Total expenses per acre to produce this corn in 2006 were $410 (See “Commodity Costs and Returns: U.S. and Regional Cost and Return Data,” USDA Economic Research Service, available at [http://www.ers. usda.gov/ Data/CostsAndReturns/data/current/C-Corn.xls]. Expenses for 2008-09 have increased due to higher fuel and fertilizer costs. Assuming these expenses to be 25% higher in 2008-09 leads to $513 per acre, and net income of $333 per acre. According to NREL, about 0.5 acres of land is removed from production for each turbine, leading to a loss of corn production of about $165 dollars per turbine. (See “Power Technologies Energy Data Book: Wind Farm Area Calculator,” NREL. Available at [http://www.nrel.gov/analysis/ power_databook/calc_wind.php].) 23 S. Greenhouse, “Millions of Jobs of a Different Collar,” New York Times, March 26, 2008.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

24

39

“Economic Impacts of Tax Credit Expiration,” Navigant Consulting, prepared for the American Wind Energy Association and the Solar Energy Research and Education Foundation, February 2008, p. 21. 25 Typical new U.S. wind plants ranged from 100 to 300 megawatts of installed capacity in 2007. Horse Hollow (Texas) is the largest U.S. wind plant, at 736 megawatts. Although some wind plants have capacity on par with traditional fossil fuel power plants, they produce comparatively less electricity because winds blow inconsistently. 26 See Energy Efficiency and Renewable Energy, Small Wind Electric Systems: A U.S. Consumer’s Guide, DOE, March 2005. 27 Cubing a number requires multiplying it by itself 2 additional times (i.e, 23 = 2x2x2 = 8). The mathematical formula for wind turbine power output (P), usually measured in watts, is P = k DAV3, where k is a constant that depends on turbine design characteristics and physical limitations, D is the density of air, A is the area swept out by the turbine rotor blades (namely, Br2, with r being the length of the rotor blade), and V is the wind velocity. 28 For wind mapping resources, see NREL website [http://www.nrel.gov/wind]. 29 This is the theoretical potential. Energy Efficiency and Renewable Energy, Wind Powering America: Clean Energy for the 21st Century, DOE, September 2004. 30 Office of Energy Efficiency and Renewable Energy, 20% Wind Energy by 2030: Increasing Wind Energy’s Contribution to U.S. Electricity Supply, DOE, May 2008. 31 The U.S. Great Plains states include parts of Colorado, Kansas, Montana, Wyoming, North Dakota, South Dakota, Nebraska, Oklahoma, New Mexico, and Texas. From a geographical standpoint the region extends into the Canadian provinces of Alberta, Manitoba, and Saskatchewan. 32 See CRS Report RL33875, Electric Transmission: Approaches for Energizing a Sagging Industry, by Amy Abel. 33 This estimate excludes two-thirds of the offshore areas ranging from 5 to 20 nautical miles from the shoreline to account for shipping lanes and wildlife, and view shed concerns; and one-third of the areas from 20 to nautical 50 miles out. See Technology White Paper: Wind Energy Potential on the U.S. Outer Continental Shelf, DOI, May 2006, pp. 1-2. 34 R. Wiser and M. Bolinger, Annual Report on U.S. Wind Power Installation, Cost and Performance Trends: 2007, U.S. Department of Energy, May 2008, p. 9. 35 MMS manages the nation’s Outer Continental Shelf oil, natural gas, and other mineral resources. The Energy Policy Act of 2005 (EPACT05) granted MMS additional authority to act as the lead federal agency for offshore renewable energy projects. EPACT05 §388 stipulates that MMS authority does not supercede the existing authority of any other agency for project permitting, so a wind project on the OCS may also require other permits to operate, although leasing and environmental review would be conducted by MMS. 36 In 2006, the Senate considered a provision to the Coast Guard appropriations bill giving the governor of Massachusetts authority to veto the Cape Wind project. A compromise was reached that gave the Coast Guard greater authority over navigational safety related to the project, but denied gubernatorial veto power. See §414 of P.L. 209-241. 37 See [http://www.mms.gov/offshore/RenewableEnergy/RenewableEnergyMain.htm]. 38 See Offshore Wind Energy website [http://www.offshorewindenergy.org].

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

40

Jeffrey Logan and Stan Mark Kaplan

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

39

The German company Enercon is testing two different 6 megawatt turbines, although they are not yet available on commercial markets. The largest commonly used commercial wind turbines are the 3.6 megawatt offshore units produced by Siemens and General Electric. 40 This assumes a capacity factor (see following subsection) of 34% and an EIA estimate of the average U.S. household consumption of 11,000 kilowatt-hours per year. 41 Horizontal turbines are further divided into classes depending on generator placement, type of generator, and blade control. For example, downwind turbines have their blades behind the generator and upwind turbines, in front. Generators can be asynchronous with the grid, or operate at the same frequency. Blade speed can be fixed or variable, and controlled through pitch or stall aerodynamics. For a more complete discussion of wind turbine technical issues, see P. Carlin, A. Laxson, and E. Muljadi, The History and State of the Art of Variable-Speed Wind Turbines, NREL, February 2001. 42 Generally, the yaw control will position the turbine to face the wind at a perpendicular angle. The turbine can avoid damage from excessive wind speeds by yawing away from the wind or applying the brake. 43 The standard trailer for an 18-wheel tractor trailer is approximately 12.5 feet high and 8 feet wide. Gross vehicle weight limitations are 80,000 pounds, corresponding to a cargo weight of 42,000 pounds. According to NREL, the trailer limitations have the greatest impact on the base diameter of wind turbine towers. R. Thresher and A. Laxson, “Advanced Wind Technology: New Challenges for a New Century,” NREL, June 2006. 44 Renewable Energy Research Laboratory, “Wind Power: Capacity Factor, Intermittency, and What Happens When the Wind Doesn’t Blow?,” University of Massachusetts at Amherst, p. 1, November 2004. 45 Comparative Costs of California Central Station Electricity Generation Technologies, California Energy Commission, Appendix B, December 2007, p. 67. 46 B. Parsons, “Grid-Connected Wind Energy Technology: Progress and Prospects,” NREL, 1998, p. 5. 47 S. Butterfield, “Technology Overview: Fundamentals of Wind Energy,” NREL, 2005. 48 EIA, Annual Energy Review 2006, U.S. DOE, 2007, Table 8.2a. 49 For more information, see U.S. Climate Change Technology Program: Technical Options for the Near and Long Term, August 2005. [http://www.climatetechnology.gov] 50 For more information on U.S. R&D on wind power, see 20% Wind Energy by 2030: Increasing Wind Energy’s Contribution to U.S. Electricity Supply, DOE, May 2008. 51 T. Wright, “India Windmill Empire Begins to Show Cracks,” Wall Street Journal, April 18, 2008, P. A1. 52 Wind Power Outlook 2008, AWEA, 2008, p. 4. 53 According to one report, in early 2008 General Electric had a backlog of wind turbines on order equal to $12 billion, more than twice the backlog in early 2007. M. Kanellos, “GE Confirms That Wind Turbine Supply Is Getting Worse,” CNet News.com, April 13, 2008. 54 R. Wiser and M. Bolinger, Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2007, DOE, May 2008, p. 15. 55 AWEA 2007 Market Report, AWEA, January 2008, pp. 9-11. 56 R. Wiser and M. Bolinger, Annual Report on U.S. Wind Power Installation, Cost and Performance Trends: 2007, DOE, May 2008, p. 13. 57 Global Wind 2007 Report, Global Wind Energy Council, 2008, p. 6.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

58

41

According to GWEC, installed wind power capacity in China grew by an average annual rate of 56% between 2001 and 2007. Approximately 3,500 megawatts of new wind were installed in 2007. (Global Wind 2007 Report, GWEC, April 2008, p. 28.) According to a statement by Zhang Guobao, Vice Premier of the National Development and Reform Commission, China installed approximately 70,000 megawatts of new coal-fired generating capacity in 2007 as reported in Y. Wang, “China May Boost Power Capacity 40% in 3 Years as Demand Rises,” Bloomberg, May 12, 2008. 59 C. Fu, “Fanning Wind Power Capacity,” Shanghai Daily, April 28, 2008. 60 Variable O&M costs vary with the output of a generating station, such as the cost of the consumables used by pollution control equipment. Fixed O&M, which is insensitive to the level of plant output, includes such costs as the salaries of plant staff and scheduled maintenance. 61 S. Butterfield, “Fundamentals of Wind Technology,” NREL, presentation at American Wind Energy Association conference, May 15, 2005. 62 Capital intensive means that compared to some other generating sources, such as gas-fired plants, wind plants require a relatively large initial outlay to build the plant. This large outlay also translates into higher fixed costs, in the form of repayment of the debt portion of construction financing. 63 These data were gathered by analysts at Lawrence Berkeley National Lab from 227 completed wind projects totaling 12,998 megawatts of capacity. Reported in R. Wiser and M. Bolinger, Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2007, U.S. DOE, May 2008, pp. 21. 64 L. Flowers, “Wind Energy Update,” NREL, February 2008. 65 According to Cambridge Energy Research Associates, coal, gas, wind, and nuclear power plants were, on average, 131% more expensive to build in late 2007 compared to 2000. Sector-specific cost increases include wind 108%, nuclear 173%, coal 78% and gas 92%. See “Costs to Build Power Plants Pressure Rates,” Wall Street Journal, May 27, 2008. 66 R. Wiser, M. Bolinger, and G. Barbose, “Using the Production Tax Credit to Build a Durable Market for Wind Power in the United States,” Lawrence Berkeley National Laboratory, 2007. 67 Mike Mercer, “Power for a Calm Day,” Diesel & Gas Turbine Worldwide, October 2007. The station is Northwestern Energy’s Basin Creek plant, a 51.8 MW plant consisting of 9 gas-fired diesel generators. 68 B. Parsons, M. Milligan, et al. “Grid Impacts of Wind Power Variability: Recent Assessments from a Variety of Utilities in the United States,” conference paper presented at the European Wind Energy Conference. Athens, Greece, 2006 [http://www.nrel.gov/ docs/fy06osti/39955.pdf], p. 9. 69 This is equivalent to 0.282 cents per kilowatt-hour. Gail Kinsey Hill, “BPA Calculates Administrative Costs of Wind Power,” The Oregonian, March 29, 2008. 70 Assuming the natural gas combined cycle was built by a utility reduces the estimated cost in the Base Case by about $4 per megawatt-hour. This is due to the lower financing costs available to regulated utilities compared to IPPs. If the wind plant is built by a utility the estimated cost increases by about $1 per megawatt-hour. This is the net effect of the lower financing costs and the loss of the production tax credits. The renewable production tax credit applies to sales of electricity by the wind plant owner to another

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

42

Jeffrey Logan and Stan Mark Kaplan

entity. A utility which operates a wind plant to serve its own load cannot take the credit. See 10 C.F.R. § 451.4 71 Other factors, combinations of factors, and alternative cost forecasts could be evaluated. The economic analyses presented here consider just one subset of many potential alternative assumptions. The subset was chosen to highlight some of the important determinants of the competitiveness of wind power. 72 The nominal value of the nuclear production tax credit of $18 per megawatt-hour will be reduced if more than 6,000 megawatts of new nuclear capacity qualify for the credit. The Base Case follows EIA’s long-term forecast assumption that the effective rate will be reduced to $12 per megawatt-hour because 9,000 megawatts of new nuclear capacity will qualify. See EIA, Annual Energy Outlook 2007, pp. 20-21. 73 The status of the renewable PTC is discussed elsewhere in this report. 74 In 2008, the Congressional Budget Office (CBO) estimated the price of carbon dioxide allowances in 2013 at $30 per metric ton in nominal dollars. Given an estimated change in the implicit price deflator of 17.2% between 2005 and 2013, this converts to $25.60 per metric ton in constant 2005 dollars. This value was rounded to $26 per metric ton to simplify the presentation. See CBO, “Cost Estimate for S. 2191, America’s Climate Security Act of 2007,” April 10, 2008, p. 8. 75 EIA assumes that a 44% capacity factor would be achievable by 2010 for a wind plant located in the northwest. The wind capacity factor for this region actually declines over time, to 41% by 2030, presumably because wind plants are increasingly located in less favorable locations. See EIA, Assumptions to the Annual Energy Outlook 2007, Table 73. Planning consultants to the utility Westar Energy assumed that wind plants located in Kansas could achieve capacity factors of 42%. See Direct Testimony of Michael Elenbaas on behalf of Westar Energy, before the Kansas State Corporation Commission, Docket 08- WSEE-309-PRE, October 1, 2007, pp. 11 and 13. 76 The loan guarantee allows the nuclear plant to be financed with 80% debt at a low interest rate. In the absence of the loan guarantee the cost of debt increases and the debt portion of the financial structure drops to 50%. The balance of the financing is equity, which is more expensive than debt. Eliminating the loan guarantee, therefore, has a major impact on the cost of a nuclear project. The chief nuclear officer for Exelon, the power company with the largest fleet of nuclear reactors in the United States, stated that constructing new nuclear plants will be “impossible” in the absence of loan guarantees (S. Dolley, “Nuclear Power Key to Exelon’ s Low-Carbon Plan,” Nucleonics Week, February 14, 2008). For further discussion of the importance of loan guarantees, see Tom Tiernan, “Nuclear Interests, Wall Street Concerned about Loan Guarantee Program, Legislation,” Electric Utility Week, August 20, 2007. Wind power is not eligible for the loan guarantees provided in EPACT05 because it is not considered a commercial technology. 77 For example, see EIA, Annual Energy Outlook Retrospective Review: Evaluation of Projections in Past Editions (1982-2006), pp. 2, 3, and 5. 78 Carbon costs have less impact on the gas plant because gas emits about half as much carbon dioxide per unit burned than coal, and a combined cycle gas-fired plant requires less fuel to produce a unit of electricity than a pulverized coal plant. 79 Energy projects built on private land that receive federal grants or use federal transmission lines must also meet federal requirements in the National Environmental Policy Act (42 U.S.C. §4321).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power in the United States: Technology, Economic, and Policy Issues

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

80

43

Others might include the Bald and Golden Eagle Protection Act (16 U.S.C. §§668-668d), National Historic Preservation Act (16 USC §470), Clean Water Act (33 U.S.C. § 1251), Rivers and Harbors Act of 1899 (33 U.S.C. §401), Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA or Superfund, 42 U.S.C. §§96019675). 81 More comprehensive information on federal, state and local regulations related to wind energy projects is found in: Energy Efficiency and Renewable Energy, “Federal Wind Siting Information Center,” DOE [http://www1.eere.energy.gov/windandhydro/ federalwindsiting/], Wind Energy Siting Handbook, AWEA, 2008 and Permitting of Wind Energy Facilities: A Handbook, National Wind Coordinating Committee, Revised 2002. 82 National Research Council, Environmental Impacts of Wind-Energy Projects: Report in Brief, The National Academy of Sciences, 2007, p. 2. 83 These early turbines were not designed with avian populations in mind. The blades spun much more quickly than today’s turbines and the towers were often constructed of lattice steel, an enticing nesting feature for birds. 84 Wind Power: Impacts on Wildlife and Government Responsibilities for Regulating Development and Protecting Wildlife, Government Accountability Office, GAO-05-906, September 2005, pp. 10-13. 85 J. Layke, K. Porter, and A. Perera, “Diversifying Corporate Energy Purchasing with Wind Power,” World Resources Institute, February 2008, p. 14. 86 BWEC includes AWEA, Bat Conservation International, the U.S. Fish and Wildlife Service, and the U.S. Department of Energy’s National Renewable Energy Laboratory. “Wind Energy and Wildlife: Frequently Asked Questions,” AWEA, 2008, p. 2. 87 See, for example, “Bats and Wind Energy Cooperative” [http://www.batsandwind.org/]. 88 See, for example, National Research Council, Environmental Impacts of Wind-Energy Projects: Report in Brief, The National Academy of Sciences, 2007 89 J. Layke, K. Porter, A. Perera, “Diversifying Corporate Energy Purchasing with Wind Power,” World Resources Institute, 2008, p. 9. 90 See “Interim Guidelines to Avoid and Minimize Wildlife Impacts from Wind Turbines,” U.S. Department of the Interior, Fish and Wildlife Service, 2003, [http://www.fws.gov/ habitatconservation/wind.pdf]. 91 The Charter describing the committee’s formation is available on the FWS web site at [http://www.fws.gov/habitatconservation/Advisory_Committee_Charter_3_20_07.pdf]. 92 A. Rogers, J. Manwell, and S. Wright, Wind Turbine Acoustic Noise, University of Massachusetts at Amherst, Renewable Energy Research Laboratory, June 2002. 93 B. Voll, “Black Springs Wind Farm Shadow Flicker Study,” Energreen Wind, 2006, p. 6. 94 See also M. Brenner, et al., Wind Farms and Radar, The MITRE Corporation, JSR-08126, January 2008. 95 AWEA, “Wind Turbines and Radar: An Informational Resource,” June 2, 2006 [http://www.awea.org/pubs/factsheets/060602_Wind_Turbines_and%20_Radar_Fact_Sh eet.pdf]. 96 K. Kinsmore, and R. Wright, “Intent of March 21, 2006 Memorandum,” Department of Defense and Department of Homeland Security Joint Program Office, July 10, 2006. 97 The report was issues on September 27, 2006 and is available at [http://www.defense.gov/ pubs/pdfs/WindFarmReport.pdf]

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

44

Jeffrey Logan and Stan Mark Kaplan

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

98

Office of the Director of Defense Research and Engineering, The Effect of Windmill Farms on Military Readiness, DOD, September 2006, pp. 56-57. 99 FAA requirements on potential obstructions are discussed at [https://oeaaa.faa.gov/oeaaa/ external/portal.j sp]. 100 U.S. DOE, “Wind Powering America,” available at [http://www.eere.energy.gov/ windandhydro/windpoweringamerica/ne_issues_interference.asp]. 101 See CRS Report RL33875, Electric Transmission: Approaches for Energizing a Sagging Industry, by Amy Abel. 102 Actual costs are location dependent. Northwest Power Pool, “Canada — Northwest — California Transmission Options Study,” pp. 16-27, May 16, 2006. 103 L. Chaset, “Comments of the Public Utility Commission of California,” FERC Docket No. AD08-2-00, December 11, 2007; and S. Smith, “Wind on the Wires: Can Transmission Infrastructure Adapt?,” Utility Automation and Engineering T&D, May 2008. 104 P.L. 109-58, §1221. 105 P.L. 109-58, §1242. 106 Preventing Undue Discrimination and Preference in Transmission Service (Order 890), Federal Energy Regulatory Commission, February 16, 2007. 107 See CRS Report RS21407, Federal Energy Regulatory Commission’s Standard Market Design Activities, by Amy Abel. 108 According to a recent DOE report, there were 225,000 megawatts of proposed wind power capacity in interconnection queues within 11 RTO, ISO, and utility regions at the end of 2007. As noted in the report, being in the queue does not guarantee that a project will be built; many are at an early stage of development and may never achieve commercial operations. For comparison, the report noted that about 212,000 megawatts of natural gas, coal, nuclear, solar, and “other” projects were also in queues. R. Wiser and M. Bolinger, Annual Report on U.S. Wind Power Installation, Cost and Performance Trends: 2007, U.S. Department of Energy, May 2008, pp. 9-10. 109 Standardization of Generator Interconnection Agreements and Procedures (Order 2003), F ederal Energy Regulatory Commission, July 24, 2003; Interconnection for Wind Energy ( Order 661), Federal Energy Regulatory Commission, June 2, 2005. 110 Interconnection Queuing Practices (Docket No. AD08-2-000), Federal Energy Regulatory Commission, March 20, 2008. 111 For more information on recent electricity transmission issues that may relate to wind p ower, see CRS Report RL33875, Electric Transmission: Approaches for Energizing a Sagging Industry, by Amy Abel; and 20% Wind Energy by 2030: Increasing Wind Energy’s Contribution to U.S. Electricity Supply, U.S. DOE, 2008. 112 Testimony from this hearing is available at [http://energy.senate.gov/public/ index.cfm?FuseAction=Hearings.Hearing&HearingjD=7 34449 1e-df7f-9a28-80ce-47fe5 2e63f1b]. 113 U.S. Congress, House Committee on Ways and Means, Tax Credits for Electricity Production from Renewable Sources. Hearing held May 24, 2005. Testimony of Dean G osselin, FPL Energy. pp. 25-26. [http://waysandmeans.house.gov/hearings.asp? formmode= detail&hearing=4 11]. 114 Federal subsidies for conventional energy resources and technologies and for electric power facilities (including large hydroelectric power plants) have been traced back as far as the 1920s and 1930s. See DOE (Pacific Northwest Laboratory), An Analysis of

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wind Power in the United States: Technology, Economic, and Policy Issues

45

Federal Incentives Used to Stimulate Energy Production, 1980. p. 300. The EIA recently published the latest in a series on federal energy incentives and subsidies: EIA, Federal Financial Interventions and Subsidies in Energy Markets 2007, DOE, April 2008. 115 GAO. Petroleum and Ethanol Fuels: Tax Incentives and Related GAO Work. (GAO/RCED-00-30 1R) September 25, 2000. The report notes that from 1968 through 2000, about $150 billion (constant 2000 dollars) worth of tax incentives were provided to support the oil and natural gas industries. 116 CBO’s analysis was performed in accordance with S. 2191 (the Lieberman-Warner Climate Security Act of 2008). See CRS Report RL34515 Climate Change: Comparisons of S. 2191 as Reported (now S. 3036) with Proposed Boxer Amendment, by Brent Yacobucci and Larry Parker. 117 The summary is available at [http://www.eesi.org/briefings/2008/061808_hboell_rep/ Inslee_REJSA_06 1 808.pdf]. 118 Section 210 of the Public Utility Regulatory Policies Act (PURPA) of 1978 had guaranteed a market for the purchase of electric power produced from small renewable energy facilities. PURPA let states determine the avoided cost pricing of the electricity production from renewable energy facilities. The effectiveness of this mechanism lessened with the advent of electric industry restructuring. Provided that certain conditions are met in any given state, Section 1253 of the Energy Policy Act of 2005 retrospectively terminates the PURPA mandatory purchase requirements. 119 Federal Energy Regulatory Commission, Renewable Energy Portfolio Standards (RPS), DOE. For a map showing the status of state action on RPS, see [http://www.ferc.gov/ market-oversight/mkt-electric/overview/elec-ovr-rps.pdf]. 120 Details about eligible resources and other provisions of state RPS programs are available from the online Database of State Incentives for Renewable Energy and Energy Efficiency, [http://www.dsireusa.org/]. See also R. Wiser and G. Barbose, Renewables Portfolio Standards in the United States — A Status Report with Data Through 2007, Lawrence Berkeley National Laboratory, April 2008; and A. Selting, The Race for the Green: How Renewable Portfolio Standards Could Affect U.S. Utility Credit Quality, Standard & Poors, March 2008. 121 EIA, Impacts of a 15-Percent Renewable Portfolio Standard, DOE, June 2007. 24 p. 122 Converting a series of cash flows to a financially-equivalent uniform annual payment is a two-step process. First, the cash flows for the project are converted to a 2008 “present value.” The present value is the total cost for the analysis period, adjusted (“discounted” using a “discount factor”) to account for the time value of money and the risk that projected costs will not occur as expected. This lump-sum 2008 present value is then converted to an equivalent annual payment using a uniform payments factor (the “capital recovery factor”). For a more detailed discussion of the levelization method see, for example, Chan Park, Fundamentals of Engineering Economics, 2004, Chapter 6; or Eugene Grant, et al., Principles of Engineering Economy, 6th Ed., 1976, Chapter 7. 123 For additional information on capital charge rates see Hoff Stauffer, “Beware Capital Charge Rates,” The Electricity Journal, April 2006. The capital recovery factor is equivalent to the PMT function in the Excel spreadsheet program. For additional information on the calculation of capital recovery factors see Chan Park, Fundamentals of Engineering Economics, 2004, Chapter 2; or Eugene Grant, et al., Principles of Engineering Economy, 6th Ed., 1976, Chapter 4.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

46

Jeffrey Logan and Stan Mark Kaplan

124

See 10 CFR § 451.4. For a discussion of the credit see EIA, Annual Energy Outlook 2007, p. 21. 126 DOE Announces Plans for Future Loan Guarantee Solicitations, Department of Energy press release, April 11, 2008. Loan guarantee authority of $18.5 billion for nuclear power plants is provided by P.L. 110-161. 127 Entities receiving loan guarantees must make a substantial equity contribution to the project’s financing. Public power entities normally do not have the retained earnings needed to make such payments. The rules also preclude granting a loan guarantee if the federal guarantee would cause what would otherwise be tax exempt debt to become subject to income taxes. Under current law this situation would arise if the federal government were to guarantee public power debt. For further information on these and other aspects of the loan guarantee program see U.S. DOE, final rule, “Loan Guarantees for Projects that Employ Innovative Technologies,” 10 C.F.R. § 609 (RIN 1901-AB21), October 4, 2007 [http://www.lgprogram.energy.gov/keydocs.html]. 128 For additional information see the discussion of the investment tax credit in the federal incentives section of the Database of State Incentives for Renewable Energy website, [http://www.dsireusa.org/].

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

125

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

In: Wind Power: Technology, Economics and Policies ISBN 978-1-60692-323-8 Editor: Cedrick N. Osphey, pp. 47-98 © 2009 Nova Science Publishers, Inc.

Chapter 2

ANNUAL REPORT ON U.S. WIND POWER INSTALLATION, COST, * AND PERFORMANCE TRENDS: 2007 U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

INTRODUCTION The U.S. wind industry experienced unprecedented growth in 2007, surpassing even optimistic projections from years past. This rapid pace of development has made it difficult to keep up with trends in the marketplace. Yet, the need for timely, objective information on the industry and its progress has never been greater. This report— the second of an ongoing annual series —attempts to meet this need by providing a detailed overview of developments and trends in the U.S. wind power market, with a particular focus on 2007. As with the previous edition*, this report begins with an overview of key wind power development and installation-related trends, including trends in capacity growth, in turbine make and model, and among wind power developers, project owners, and power purchasers. It then reviews the price of wind power in the United States, and how those prices compare to the cost of fossil- fueled generation, as represented by wholesale power prices. Next, the report describes trends in installed wind project costs, wind turbine transaction prices, project performance, and operations and maintenance expenses. Finally, the report examines other factors impacting the domestic wind power market, including grid integration costs, transmission issues, and policy drivers. The report concludes with a brief preview of possible developments in 2008. This version of the Annual Report updates data presented in the previous edition, while highlighting key trends and important new developments from 2007. New to this edition is a section on the contribution of wind power to new capacity additions in the electric sector, data on the amount of wind in utility systems, a summary of trends in wind project size, a *

This is an edited, excerpted and augmented edition of an Energy Efficiency and Renewable Energy publication, dated May 2008. Primary authors: Ryan Wiser and Mark Bolinger, Lawrence Berkeley National Laboratory.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

48

U.S. Department of Energy

discussion of the quantity of wind power capacity in various interconnection queues in the United States, and a section that underscores domestic wind turbine manufacturing investments. A note on scope: this report concentrates on larger-scale wind applications, defined here as individual turbines or projects that exceed 50 kW in size. The U.S. wind power sector is multifaceted, however, and also includes smaller, customer-sited wind applications used to power the needs of residences, farms, and businesses. Data on these applications are not the focus of this report, though a brief discussion on Distributed Wind Power is provided on page 4. Much of the data included in this report were compiled by Berkeley Lab, and come from a variety of sources, including the American Wind Energy Association (AWEA), the Energy Information Administration (EIA), and the Federal Energy Regulatory Commission (FERC). The Appendix provides a summary of the many data sources used in the report. Data on 2007 wind capacity additions in the United States are based on preliminary information provided by AWEA; some minor adjustments to those data are expected. In other cases, the data shown here represent only a sample of actual wind projects installed in the United States; furthermore, the data vary in quality. As such, emphasis should be placed on overall trends, rather than on individual data points. Finally, each section of this document focuses on historical market information, with an emphasis on 2007; the report does not seek to forecast future trends.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

ACRONYMS AWEA BPA COD CREZ DOE EIA ERCOT FERC IOU IPP ISO LBNL MISO NREL POU PPA PTC PUC REC RPS RTO

American Wind Energy Association Bonneville Power Administration commercial operation date competitive renewable energy zone U.S. Department of Energy Energy Information Administration Electric Reliability Council of Texas Federal Energy Regulatory Commission investor-owned utility independent power producer independent system operator Lawrence Berkeley National Laboratory Midwest Independent System Operator National Renewable Energy Laboratory publicly owned utility power purchase agreement production tax credit public utility commission renewable energy certificate renewables portfolio standard regional transmission organization

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends SPP TVA WAPA

49

Southwest Power Pool Tennessee Valley Authority Western Area Power Administration

U.S. WIND POWER CAPACITY SURGED BY 46% IN 2007, WITH 5,329 MW ADDED AND $9 BILLION INVESTED The U.S. wind power market surged in 2007, shattering previous records, with 5,329 MW of new capacity added, bringing the cumulative total to 16,904 MW (Figure 1). This growth translates into roughly $9 billion (real 2007 dollars) invested in wind project installations in 2007, for a cumulative total of nearly $28 billion since the 1980s.1 Wind installations in 2007 were not only the largest on record in the United States, but were more than twice the previous U.S. record, set in 2006. No country, in any single year, has added the volume of wind capacity that was added to the United States electrical grid in 2007. Federal tax incentives, state renewables portfolio standards (RPS), concern about global climate change, and continued uncertainty about the future costs and liabilities of natural gas and coal facilities helped spur this intensified growth.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Distributed Wind Power Wind turbines installed on the distribution side of the electric grid can provide power directly to homes, farms, schools, businesses, and industrial facilities. Distributed wind turbines can also provide power to off-grid sites. Distributed wind turbines generally range in size from a few hundred watts up to 100 kW or more, and growth in this sector has been driven — at least in part—by a variety of state incentive programs. The table below summarizes sales of distributed wind turbines from 300 W to 100 kW in size into the U.S. market in 2007. As shown, nearly 10 MW of distributed wind turbines were sold in the U.S., with a slight majority (in capacity terms) used in grid-connected applications; 89% of this new capacity came from turbines manufactured by U.S. companies, including (but not limited to) Southwest Windpower, Bergey Windpower, Wind Turbine Industries, Entegrity Wind Systems, and Distributed Energy Systems. These installation figures represent a 14% growth in annual sales—in capacity terms—relative to 2006, yielding a cumulative installed capacity of distributed wind in the United States in this turbine size range of roughly 55-60 MW. Application

Off-grid On-grid Total

Annual Sales in 2007 Number of Turbines 7,800 1,292 9,092

Capacity Additions (MW) 4.0 5.7 9.7

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Sales Revenue (million $) 14 28 42

50

U.S. Department of Energy

Source: AWEA. Figure 1. Annual and Cumulative Growth in U.S. Wind Power Capacity.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The yearly boom-and-bust cycle that characterized the U.S. wind market from 1999 through 2004—caused by periodic, short- term extensions of the federal production tax credit (PTC)—has now been replaced by three consecutive years of sizable growth. With the PTC currently (as of early-May 2008) set to expire at the end of the year, 2008 is expected to be another year of sizable capacity additions. Unless the PTC is extended before mid-to-late 2008, however, a return to the boom-and-bust cycle can be expected in 2009.

WIND POWER CONTRIBUTED 35% OF ALL NEW U.S. ELECTRIC GENERATING CAPACITY IN 2007 Wind power now represents one of the largest new sources of electric capacity additions in the United States. For the third consecutive year, wind power was the second-largest new resource added to the U.S. electrical grid in terms of nameplate capacity, behind the 7,500 MW of new natural gas plants, but ahead of the 1,400 MW of new coal. New wind plants contributed roughly 35% of the new nameplate capacity added to the U.S. electrical grid in 2007, compared to 19% in 2006, 12% in 2005, and less than 4% from 2000 through 2004 (see Figure 2). The EIA projects that total U.S. electricity supply will need to increase at an average pace of 47 TWh per year from 2008 to 2030 in order to meet demand growth. On an energy basis, the annual amount of electricity generated by the new wind capacity added in 2007 (~1 6 TWh) represents roughly 35% of this average annual projected growth in supply.2 By extension, if wind capacity additions continued through 2030 at the same pace as set in 2007 (5,329 MW per year), then 35% of the nation’s projected additional electricity generation needs from 2008 through 2030 would be met with wind electricity. Although future growth trends are hard to predict, it is clear that a significant portion of the country’s new generation needs are already being met by wind power.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

Source: EIA, Ventyx, AWEA, IREC, Berkeley Lab. Figure 2. Relative Contribution of Generation Types to Annual Capacity Additions.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

THE UNITED STATES CONTINUED TO LEAD THE WORLD IN ANNUAL CAPACITY GROWTH Table 1. International Rankings of Wind Power Capacity Incremental Capacity (2007, MW) U.S. 5,329 China 3,287 Spain 3,100 Germany 1,667 India 1,617 France 888 Italy 603 Portugal 434 U.K. 427 Canada 386 Rest of World 2,138 TOTAL 19,876

Cumulative Capacity (end of 2007, MW) Germany 22,277 U.S. 16,904 Spain 14,714 India 7,845 China 5,875 Denmark 3,088 Italy 2,721 France 2,471 U.K. 2,394 Portugal 2,150 Rest of World 13,591 TOTAL 94,030

Source: BTM Consult; AWEA project database for U.S. capacity.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

51

52

U.S. Department of Energy

Source: Earth Policy Institute, BTM Consult, AWEA. Figure 3. The United States’ Contribution to Global Wind Capacity.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

On a worldwide basis, roughly 20,000 MW of wind capacity was added in 2007, the highest volume achieved in a single year, and up from about 15,000 MW in 2006, bringing the cumulative total to approximately 94,000 MW. For the third straight year, the United States led the world in wind capacity additions (Table 1), capturing roughly 27% of the worldwide market, up from 16% in 2006 (Figure 3). China, Spain, Germany, and India rounded out the top five countries in 2007 for annual wind capacity additions (Table 1 ).3

Source: Berkeley Lab estimates based on data from BTM Consult and elsewhere. Figure 4. Approximate Wind Power Penetration in the Twenty Countries with the Greatest Installed Wind Capacity.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

53

In terms of cumulative installed wind capacity, the United States ended the year with 18% of worldwide capacity, in second place behind Germany. So far this decade (i.e., over the past eight years), cumulative wind power capacity has grown an average of 27% per year in the United States, equivalent to the same 27% growth rate in worldwide capacity. Several countries are beginning to achieve relatively high levels of wind power penetration in their electricity grids. Figure 4 presents data on end-of-2007 (and end-of-2006) installed wind capacity, translated into projected annual electricity supply based on assumed country-specific capacity factors, and divided by projected 2008 (and 2007) electricity consumption. Using this rough approximation for the contribution of wind to electricity consumption, and focusing only on the 20 countries with the greatest cumulative installed wind capacity, end-of-2007 installed wind is projected to supply roughly 20% of Denmark’s electricity demand (somewhat less than last year), 12% of Spain’s (up by 2.2% from last year), 9% of Portugal’s (up by 1.6% from last year), 8% of Ireland’s (up by 0.4% from last year), and 7% of Germany’s (up by 0.4% from last year). In the United States, on the other hand, the cumulative wind capacity installed at the end of 2007 would, in an average year, be able to supply roughly 1.2% of the nation’s electricity consumption (up by 0.4% from last year) 4—the same as wind’s estimated 1.2% contribution to electricity consumption on a worldwide basis.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

TEXAS EASILY EXCEEDED OTHER STATES IN ANNUAL CAPACITY GROWTH New large-scale5 wind turbines were installed in 18 states in 2007. Texas dominated in terms of new capacity, with 1,708 MW installed in 2007 alone. As shown in Table 2 and Figure 5, other leading states in terms of new capacity include Colorado, Illinois, Oregon, Minnesota, Washington, and Iowa. Ten states added more than 100 MW each. On a cumulative basis, after surpassing California in 2006, Texas continued to build on its lead in 2007, with a total of 4,446 MW of wind capacity installed by the end of the year. In fact, Texas has more installed wind capacity than all but five countries worldwide. Following Texas are California, Minnesota, Iowa, Washington, and Colorado. Sixteen states had more than 100 MW of wind capacity as of the end of 2007, with nine topping 500 MW. Although all wind projects in the United States to date have been sited on land, offshore development activities continued in 2007, though not without some tribulations (see Offshore Wind Development Activities, page 9). Some states are beginning to realize relatively high levels of wind penetration. Table 2 lists the top-20 states based on an estimate of wind generation from end-of-2007 wind capacity, divided by total in-state generation in 2007.6 By this (somewhat- contrived) metric, two Midwestern states lead the list in terms of estimated wind power as a percentage of total in-state generation. Specifically, wind capacity installed as of the end of 2007 is estimated, in an average year, to generate approximately 7.5% of all in-state electricity generation in both Minnesota and Iowa. Four additional states—Colorado, South Dakota, Oregon, and New Mexico—surpass the 4% mark by this metric, while thirteen states exceed 2%. Some utilities are achieving even higher levels of wind penetration into their individual electric systems. Table 3 lists the top-20 utilities in terms of aggregate wind capacity on their

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

54

U.S. Department of Energy

systems at the end of 2007, based on data provided by AWEA. Included here are wind projects either owned by or under long-term contract with these utilities for use by their own customers; short-term renewable electricity and renewable energy certificate contracts are excluded. The table also lists the top-20 utilities based on an estimate of the percentage of retail sales that wind generation represents, using end-of-2007 wind capacity and wind capacity factors that are consistent with the state or region in which these utilities operate, and EIA-provided aggregate retail electricity sales for each utility in 2006.7 As shown, three of the listed utility systems are estimated to have achieved in excess of 10% wind penetration based on this metric, while 15 utilities are estimated to have exceeded 5%.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table 2. United States Wind Power Rankings: The Top-20 States Incremental Capacity (2007, MW) Texas 1,708 Colorado 776 Illinois 592 Oregon 444 Minnesota 403 Washington 345 Iowa 341 North Dakota 167 Oklahoma 155 Pennsylvania 115 California 63 Missouri 57 New York 55 South Dakota 54 Maine 33 Hawaii 21 Massachusetts 2 Montana 2

Rest of U.S. Total

0 5,329

Cumulative Capacity (end of 2007, MW) Texas 4,446 California 2,439 Minnesota 1,298 Iowa 1,271 Washington 1,163 Colorado 1,067 Oregon 882 Illinois 699 Oklahoma 689 New Mexico 496 New York 425 Kansas 364 North Dakota 345 Pennsylvania 294 Wyoming 288 Montana 147 South Dakota 98 Idaho 75 Nebraska 73 West Virginia 66 Rest of U.S. 277 TOTAL 16,904

Estimated Percentage of In-State Generation Minnesota 7.5% Iowa 7.5% Colorado 6.1% South Dakota 6.0% Oregon 4.4% New Mexico 4.0% North Dakota 3.8% Oklahoma 3.0% Texas 3.0% Washington 2.8% California 2.8% Kansas 2.3% Hawaii 2.3% Montana 1.9% Wyoming 1.7% Idaho 1.5% Illinois 0.8% Maine 0.8% New York 0.7% Nebraska 0.7% Rest of U.S. 0.05% Total 1.1%

Source: AWEA project database, EIA, Berkeley Lab estimates.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

55

Figure 5. Location of Wind Power Development in the United States.

Table 3. Top 20 Utility Wind Power Rankings

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Total Wind Capacity (end of 2007, MW) Xcel Energy 2,635 MidAmerican Energy 1,201 Southern California Edison 1,026 Pacific Gas & Electric 878 Luminant 704 American Electric Power 543 CPS Energy 501 Puget Sound Energy 428 Alliant Energy 378 Exelon Energy 342 Austin Energy 274 Portland General Electric 225 Great River Energy 218 Last Mile Electric Cooperative 205 Public Service New Mexico 204 MSR Public Power Agency 200 Reliant Energy 199 Seattle City Light 175 Oklahoma Gas & Electric 170 Empire District Electric Company 150 Source: AWEA, EIA, Berkeley Lab estimates.

Estimated Percentage of Retail Sales (for utilities with > 50 MW of wind) Minnkota Power Cooperative 11.2% Empire District Electric Company 10.2% Last Mile Electric Cooperative 10.0% Xcel Energy 9.3% MSR Public Power Agency 8.4% Public Service New Mexico 7.5% Oklahoma Municipal Power Authority 7.2% CPS Energy 7.1% Northwestern Energy 7.0% Austin Energy 6.6% Otter Tail Power 6.4% Great River Energy 6.3% Nebraska Public Power District 6.0% Puget Sound Energy 5.2% Seattle City Light 5.0% MidAmerican Energy 4.7% Alliant Energy 4.2% Western Farmers’ Electric Cooperative 3.8% Luminant Energy 3.6% Minnesota Power 3.5%

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

56

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Offshore Wind Development Activities In Europe, two offshore wind projects, totaling 200 MW, were installed in 2007, bringing total worldwide offshore wind capacity to 1,077 MW. In contrast, all wind projects built in the United States to date have been sited on land. Despite the slow pace of offshore activity, there is some interest in offshore wind in several parts of the United States due to the proximity of offshore wind resources to large population centers, advances in technology, and potentially superior capacity factors. The table on the right provides a listing, by state, of “active” offshore project proposals in the United States as of the end of 2007. Note that these projects are in various stages of development, and a number are either very early-stage proposals or reflect projects that are already in jeopardy of cancellation; clearly, considerable subjectivity is required in creating this list of “active” proposals. Several events in 2007 demonstrate that progress continues with offshore wind in the United States. Specifically, New Jersey issued a solicitation to provide financial incentives for an offshore wind project up to 350 MW in size, Ohio commissioned a study to investigate the feasibility of a 20-MW wind project in Lake Erie, the Texas General Land Office awarded the first four competitively bid leases for offshore wind power in the nation’s history, and the municipal utility serving the town of Hull, Massachusetts filed for (and in February 2008, received) initial state approval for four offshore turbines. More recently, Rhode Island has also issued an RFP for offshore wind. Also in 2007, the Draft Environmental Impact Statement for the highly publicized Cape Wind project in Massachusetts reached conclusions favorable to the project, and the U.S. Minerals Management Service made progress in executing its offshore wind regulatory responsibilities. Notwithstanding these developments, regulatory delays, turbine supply shortages, high and uncertain project costs, and public acceptance concerns have hampered progress in the offshore wind sector. In 2007 alone, for example, concerns about the high costs of offshore wind resulted in the cancellation of a 500-MW Texas project and the likely cancellation of a 150-MW New York facility, and put a 450-MW Delaware project in jeopardy (the latter two projects are included in the table on the right, as they remain at least somewhat “active”) State Massachusetts

Proposed Offshore Wind Capacity 783 MW

Delaware

450 MW

New Jersey

350 MW

New York

160 MW

Texas

150 MW

Ohio

20 MW

Georgia

10 MW

TOTAL

1,923 MW

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

57

Source: Exeter Associates review of interconnection queues. Figure 6. Nameplate Resource Capacity in Eleven Major Interconnection Queues.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

DATA FROM INTERCONNECTION QUEUES DEMONSTRATE THAT AN ENORMOUS AMOUNT OF WIND CAPACITY IS UNDER DEVELOPMENT One visible testament to the surging interest in wind is the amount of wind power capacity currently working its way through the major interconnection queues across the country. Figure 6 provides this information, for wind and other resources, aggregated across eleven wind-relevant independent system operators (ISOs), regional transmission organizations (RTOs), and utilities.8 These data should be interpreted with caution: though placing a project in the interconnection queue is a necessary step in project development, being in the queue does not guarantee that a project will actually be built. In fact, there is a growing recognition that many of the projects currently in interconnection queues are very early in the development process, and that a large number of these projects are unlikely to achieve commercial operations any time soon, if at all.9 Even with this important caveat, the amount of wind capacity in the nation’s interconnection queues is astounding, and provides some indication of the number and capacity of projects that are in the planning phase. At the end of 2007, there were 225 GW of wind power capacity within the eleven interconnection queues reviewed for this report—more than 13 times the installed wind capacity in the United States at the end of 2007. This wind capacity represents roughly half of all generating capacity within these queues at that time, and is twice as much capacity as the next-largest resource in these queues (natural gas). Moreover, wind’s prominent position is a relatively recent phenomenon: 64% of the total wind capacity in these eleven queues at the end of 2007 first entered the queue in 2007 (for the non-wind projects, in aggregate, the comparable figure is 52%). Much of this wind capacity is planned for the Midwest, Texas, and PJM regions: wind in the interconnection queues of MISO (66 GW), ERCOT (41 GW), and PJM (35 GW) account for nearly two-thirds of the aggregate 225 GW of wind in all eleven queues. At the other end of the spectrum, the Northeast exhibits the least amount of wind capacity in the pipeline, with

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

58

U.S. Department of Energy

the New York ISO (7 GW) and ISO-New England (2 GW) together accounting for about 4% of the aggregate 225 GW. The remaining six queues include SPP (21 GW), California ISO (19 GW), WAPA (10 GW), BPA (10 GW), PacifiCorp (9 GW), and Xcel’s Colorado service area (4 GW).

GE WIND REMAINED THE DOMINANT TURBINE MANUFACTURER, BUT A GROWING NUMBER OF OTHER MANUFACTURERS ARE CAPTURING MARKET SHARE GE Wind remained the dominant manufacturer of wind turbines supplying the U.S. market in 2007, with 44% of domestic turbine installations (down from 47% in 2006 and 60% in 2005).10 Vestas (18%) and Siemens (16%) vied for second place in 2007, with Gamesa (11%), Mitsubishi (7%), and Suzlon (4%) playing significant, but lesser, roles (Figure 7). Noteworthy developments in 2007 include the growth in Gamesa’s market share, from just 2% in 2005 and 2006 to 11% in 2007, and Siemens’ loss of market share after a banner year in 2006. Also significant is that newcomer Clipper installed 48 MW in New York, Illinois, and Iowa in 2007, marking the start of serial production of that firm’s 2.5-MW “Liberty” turbine. Nordex also re-entered the U.S. market in 2007, after a several-year hiatus, with 2.5 MW installed in Minnesota. Interestingly, though not reflected in the data shown here, U.S. developer GreenHunter announced in late 2007 an order for 108 1.5-MW Chinesemade turbines from Mingyang Wind Power Technology, for delivery in 2008.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table 4. Annual Turbine Installations, by Manufacturer Manufacturer

Turbine Installations (MW) 2006 2007 1,146 2,342

GE Wind

2005 1,433

Vestas

700

463

948

Siemens

0

573

863

Gamesa

50

50

574

Mitsubishi

190

128

356

Suzlon

25

92

197

Clipper

2.5

0

47.5

Nordex

0

0

2.5

Other

2

2

0

Total

2,402

2,454

5,329

Source: AWEA project database.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

59

Source: AWEA project database. Figure 7. Annual U.S. Market Share of Wind Manufacturers by MW, 2005-2007.

Market share, delineated in percentage terms, can be misleading in rapidly growing markets. As shown in Table 4, every manufacturer active in the U.S. market saw installations of their turbines grow between 2006 and 2007, in many cases dramatically. The most significant growth was experienced by GE (1,196 MW), Gamesa (524 MW), and Vestas (485 MW).

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

SOARING DEMAND FOR WIND SPURS EXPANSION OF U.S. WIND TURBINE MANUFACTURING The manufacturing of wind turbines and components in the United States remains somewhat limited, in part because of the continued uncertain availability of the federal PTC. As domestic demand for wind turbines continues to surge, however, a growing number of foreign turbine and component manufacturers have begun to localize operations in the United States, and manufacturing by U.S.-based companies is starting to expand. Figure 8 presents a (non-exhaustive) list of domestic wind turbine and component manufacturing facilities announced or opened in 2007, and identifies the location of those facilities as well as the location of manufacturing facilities that opened prior to 2007. Included in the figure are not only turbine assembly and component manufacturing facilities, but also facilities that meet the needs of other segments of the wind industry’s supply chain, such as wind project construction companies, anemometer suppliers, and crane and rigging providers. Among the list of facilities opened or announced in 2007 are three owned by major international turbine manufacturers: Vestas (blades in Windsor, Colorado), Acciona (turbine assembly in West Branch, Iowa), and Siemens (blades in Fort Madison, Iowa).11 Vestas is also known to be exploring sites for a U.S. R&D center. These plants are in addition to facilities opened by several other international turbine manufacturers in previous years, including: Gamesa (blades, towers, and nacelle assembly in Ebensburg and Fairless Hills, Pennsylvania), Suzlon (blades and nose cones in Pipestone, Minnesota), and Mitsubishi (gearboxes in Lake Mary, Florida). Among U.S.-based wind turbine manufacturers, GE remains dominant, and has maintained a significant domestic turbine manufacturing presence, in addition to its international facilities that serve both the U.S. and global markets. GE’s wind turbine manufacturing

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

60

U.S. Department of Energy

facilities in the United States include Tehachapi, California (turbine manufacturing); Pensacola, Florida (blade technology development, component assembly); Erie, Pennsylvania and Salem, Virginia (components); and Greenville, South Carolina (turbine assembly). Signaling the emergence of new players in the U.S. wind turbine industry, three other U.S.-based turbine manufacturers continued to scale-up their activities in 2007. •

•

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

Clipper Windpower is in the process of significant expansion, with 137 of its 2.5MW Liberty turbines produced in 2007, up from eight in 2006. Clipper expects to produce over 300 turbines in 2008 at its Cedar Rapids, Iowa, manufacturing facility, and cumulative firm turbine orders equaled 825 at the end of January, 2008. CTC/DeWind commissioned its first 2-MW D8.2 turbine in the United States in March, 2008. CTC acquired DeWind in 2006, and turbine production commenced in December, 2007 at a TECO Westinghouse manufacturing facility in Round Rock, Texas, with an initial capacity of 400 turbines per year and an order backlog of $140 million by the end of January, 2008. Nordic Windpower, a manufacturer of two-bladed turbines, announced that Goldman Sachs made a significant investment in the company in 2007. Nordic subsequently announced the opening of its North American headquarters in Berkeley, California, and in early 2008 announced the location of a planned manufacturing facility in Pocatello, Idaho.

Figure 8. Location of Existing and New Wind Manufacturing Facilities.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

61

Figure 8 also shows a considerable number of new component manufacturing facilities announced or opened in 2007, from both foreign and domestic firms. All told, the new turbine and compo-nent manufacturing facilities opened or announced in 2007 and listed in Figure 8 will, if fully implemented as planned, create more than 4,700 jobs. Notwithstanding the generally positive outlook for the turbine manufacturing sector, however, impediments faced by manufactur-ers due to rapid scale-up are apparent. Clipper Windpower, for example, has had to reinforce some blades, and has experienced problems with some of its drivetrains, slowing shipments in 2007. Blade quality and tower manufacturing problems also surfaced at Gamesa’s Pennsylvania manufacturing facilities in 2007 and early 2008; Suzlon has also recently faced blade problems. Turbine manufacturing by CTC/DeWind, meanwhile, has faced some delay, at least relative to that company’s initial expectations.

AVERAGE TURBINE SIZE CONTINUED TO GROW, ALBEIT AT A SLOWER PACE

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The average size of wind turbines installed in the United States in 2007 increased to roughly 1.65 MW (Figure 9), from 1.60 MW in 2006. Since 1998-99, average turbine size has increased by 130%.12 Table 5 shows how the distribution of turbine size has shifted over time; 40% of all turbines installed in 2007 had a nameplate capacity in excess of 1.5 MW, compared to 34% in 2006, 24% in 2004-2005, and 13% in 2002-2003. GE’s 1.5-MW wind turbine remained by far the nation’s most-popular turbine in 2007, with more than 1,500 units installed.

Source: AWEA project database. Figure 9. Average Turbine Size Installed During Period.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

62

U.S. Department of Energy

THE AVERAGE SIZE OF WIND PROJECTS EXPANDED SIGNIFICANTLY As the U.S. wind industry has matured and installations have increased, so too has the average size of installed wind projects. Projects installed in 2007 averaged nearly 120 MW, roughly double that seen in the 2004-05 period and nearly quadruple that seen in the 1998-99 period.13 This marked increase in average project size may reflect a number of interrelated trends highlighted elsewhere in this report: growing demand for wind driven by economics and policy; the upward march in turbine size; the large turbine orders that have become standard practice; consolidation among wind project developers to support these orders; and increasing turbine and project costs, which may require taking full advantage of any and all economies of scale. Whatever the specific cause, larger project sizes reflect an increasingly mature energy source that is beginning to penetrate into the domestic electricity market in a significant way. Taking this trend towards larger project size to a new level, several gigawatt-scale projects were announced in 2007. In Texas, Shell Wind Energy and Luminant are jointly planning a 3,000-MW wind project, while oilman T. Boone Pickens announced plans for a project of up to 4,000 MW. While these projects should be considered speculative at this early stage, a 1,500-MW wind project being developed by Allco and Oak Creek Energy Systems in Tehachapi, California, has already secured a power purchase agreement with Southern California Edison.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

DEVELOPER CONSOLIDATION CONTINUED AT A TORRID PACE Consolidation on the development end of the wind business continued the strong trend that began in 2005, and has been motivated, in part, by the increased globalization of the wind sector and the need for capital to manage wind turbine supply constraints. Table 6 provides a listing of major acquisition and investment activity among U.S. wind developers in the 2002 through 2007 timeframe.14 Table 5. Size Distribution of Number of Turbines Over Time Turbine Size Range 0.05-0.5 0.51-1.0 1.01-1.5 1.51-2.0 2.01-2.5 2.51-3.0

1998-99 1,018 MW 1,425 1.3% 98.5% 0.0% 0.3% 0.0% 0.0%

2000-01 1,758 MW 1,987 0.4% 73.9% 25.4% 0.4% 0.0% 0.0%

2002-03 2,125 MW 1,757 0.5% 43.4% 43.5% 12.5% 0.0% 0.1%

2004-05 2,776 MW 1,960 1.8% 18.5% 56.0% 23.6% 0.1% 0.0%

Source: AWEA project database. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

2006 2,454 MW 1,532 0.7% 10.7% 54.2% 17.6% 16.3% 0.5%

2007 5,329 MW 3,230 0.0% 11.0% 48.6% 24.1% 15.0% 1.3%

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

63

Source: Berkeley Lab analysis of AWEA project database.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 10. Average Project Size, by Commercial Operation Date (COD).

As shown, at least 11 significant transactions involving roughly 37,000 MW of indevelopment wind projects (also called the development “pipeline”) were announced in 2007, consistent with 2006 acquisition and investment activity of 12 transactions with a total 34,000 MW in the pipeline. In 2005, eight transactions totaling nearly 12,000 MW were announced, while only four transactions totaling less than 4,000 MW were completed from 2002 through 2004. A number of large companies have entered the U.S. wind development business in recent years, some through acquisitions, and others through their own development activity or through joint development agreements with others. Particularly striking in recent years has been the entrance of large European energy companies into the U.S. market. The two largest developer acquisitions in 2007, for example, were the purchase of Horizon Wind by Energias de Portugal (from Portugal) and the acquisition of Airtricity North America by E.ON AG (from Germany), summing to nearly $4 billion in aggregate.

COMFORT WITH AND USE OF INNOVATIVE FINANCING STRUCTURES INCREASED A variety of innovative financing structures have been developed by the U.S. wind industry in recent years to allow projects to fully access federal tax incentives. The two most common structures at the present time are corporate balance-sheet finance (e.g., historically used by FPL Energy) and the “institutional investor flip” structure involving institutional “tax equity” investors.15 With the record-shattering amount of new wind capacity installed in 2007 and the growing presence of foreign developers and owners with little appetite for U.S. tax incentives,16 the need to attract institutional tax equity to the U.S. wind sector has never been greater. The past year has brought both good and bad news on this front.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

64

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table 6. Acquisition and Investment Activity among Wind Developers*

* Select list of announced transactions; excludes joint development activity. Source: Berkeley Lab.

The wind industry received welcome news in October 2007, when the IRS issued “safe harbor” guidelines (i.e., Revenue Procedure 2007-65) for wind projects utilizing specialallocation partnership flip structures. Although various permutations of these types of structures have been used for a number of years to monetize the tax benefits provided to wind projects, tax equity investors have had to absorb the risk that these deals would be challenged

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

65

by the IRS. Revenue Procedure 2007-65 effectively removed this structural tax risk for projects that adhere to the prescribed investment and allocation limits, and has, through numerical example, legitimized the institutional investor flip structure.17 Comfort with this structure has grown to the point where even FPL Energy—which has financed the largest fleet of wind projects in the United States primarily on its balance sheet—conducted its first ever project refinancing using third-party tax equity in late 2007. While this event sparked rumors that the U.S. wind giant was running out of tax credit appetite, FPL’s own explanation is more benign: the institutional investor flip structure allows FPL to focus on its core strengths—developing and operating wind projects— while capitalizing on the relatively lower cost of institutional tax equity (pre-flip) and retaining long-term upside potential (post-flip). The year 2007 also saw the closing of a first-of-its-kind tax equity structure suitable for municipalities and cooperatives interested in long-term wind project ownership. The 205-MW White Creek Wind project was developed by four publicly owned, tax-exempt utilities in the Pacific Northwest, in cooperation with several institutional tax investors. By serving as power purchasers and pre-paying (up-front) for the minimum projected electricity output of the project over its initial 20 years of project operations, these four publicly owned utilities effectively enabled the project to take advantage of low-cost tax-exempt debt (used to finance the pre-payments) as well as the traditional tax benefits afforded to wind projects (available to the institutional tax investors). A post-flip buyout option allows for long-term ownership by the publicly owned utilities. Although institutional tax investors were plentiful in 2007, with more than a dozen active in the market,18 the growing dependence on such third-party investors has left the U.S. wind sector vulnerable to the broader credit crisis that began in earnest towards the end of 2007. As a result of the large losses incurred by the banking industry, institutional tax investors have less taxable income to shelter. This shortage is already being felt in the affordable housing sector—one of the wind sector’s main competitors for tax equity—where the yields on affordable housing credits have been driven sharply higher by lack of demand. It remains to be seen whether lackluster tax investor demand will spill over into the wind sector, but at the very least it seems unlikely that the cost of tax equity provided to wind projects will continue to fall in 2008. This is particularly notable because the sizable decline in the cost of tax equity over the past four or five years has partially offset (by roughly 45%, according to Berkeley Lab analysis) the impact of rising turbine and installed project costs on wind power prices. To the extent that the cost of tax equity has bottomed out or begins to rise, any further project cost increases will be felt more immediately and severely in wind power prices. Finally, project-level debt staged a comeback of sorts in 2007, with a number of projects announcing the use of term (as opposed to just construction) debt, even alongside institutional tax equity (this combination of term debt and tax equity has heretofore been quite rare), and in some cases, in quasi-merchant wind projects. One such deal involved three projects in New York State (scheduled for completion in 2008), aggregated into a single debt facility by the project sponsor. Other deals have featured increasingly aggressive terms, with debt providers willing to extend maturities 5 years or more into a project’s “merchant tail” (i.e., the period beyond which the project’s power sales have been contracted), and at least one deal featuring a 20-year loan term (including a 5-year merchant tail).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

66

U.S. Department of Energy

IPP PROJECT OWNERSHIP REMAINED DOMINANT, BUT UTILITY INTEREST IN OWNERSHIP CONTINUED, WHILE COMMUNITY WIND FALTERED

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Private independent power producers (IPPs) continued to dominate the wind industry in 2007, owning 83% of all new capacity (Figure 11). In a continuation of the trend begun several years ago, however, 16% of total wind additions in 2007 are owned by local electrical utilities, split between investor-owned utilities (IOUs) and publicly owned utilities (POUs) roughly two-to-one.19 Community wind power projects—defined here as projects using turbines over 50 kW in size and completely or partly owned by towns, schools, commercial customers, or farmers, but excluding publicly owned utilities—constitute the remaining 1% of 2007 projects. Of the cumulative 16,904 MW of installed wind capacity at the end of 2007, IPPs owned 84% (14,280 MW), with utilities contribut-ing 14% (1,790 MW for IOUs and 526 MW for POUs), and community ownership just 2% (308 MW). The community wind sector, in particular, has found it difficult to make much headway in the last couple of years, in part due to the difficulty of securing smaller turbine orders amidst the current turbine shortage. That said, state policies specifically targeting community wind and USDA Section 9006 grants may help boost the community wind numbers in future years.

THOUGH LONG-TERM CONTRACTED SALES TO UTILITIES REMAINED THE MOST COMMON OFF-TAKE ARRANGEMENT, MERCHANT PLANTS AND SALES TO POWER MARKETERS ARE BECOMING MORE PREVALENT Investor-owned utilities continued to be the dominant purchas-ers of wind power, with 48% of new 2007 capacity and 55% of cumulative capacity selling power to IOUs under long-term con-tracts (see Figure 12). Publicly owned utilities have also taken an active role, purchasing the output of 17% of new 2007 capacity and 15% of cumulative capacity. For both IOUs and POUs, power purchase agreement (PPA) terms for projects built in 2007 range from 15 to 25 years, with 20 years being the most common. The role of power marketers—defined here as corporate intermediaries that purchase power under contract and then re-sell that power to others, sometimes taking some merchant risk20– in the wind power market has increased dramatically since 2000, when such entities first entered the wind sector. In 2007, power marketers purchased the output of 20% of new wind power capacity and 17% of cumulative capacity. Among projects built in 2007, PPAs with power marketers range from 5 to 23 years in length, somewhat shorter than the range of utility PPAs. Increasingly, owners of wind projects are taking on some merchant risk, meaning that a portion of their electricity sales revenue is tied to short-term contracted and/or spot market prices (with the resulting price risk commonly hedged over a 5- to 10-year period via

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

67

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

financial transac-tions rather than through PPAs21). The owners of 15% of the wind power capacity added in 2007, for example, are accepting some merchant risk, bringing merchant/ quasi-merchant ownership to 12% of total cumulative U.S. wind capacity. The majority of this activity exists in Texas and New York—both states in which wholesale spot Markets exist, where wind power may be able to compete with these spot prices, and where additional revenue is possible from the sale of renewable energy certificates (RECs). Another interesting development in 2007 was the initiation of cross-border sales of wind electricity into the United States, despite the fact that those facilities are not eligible for U.S. tax incentives. A portion of the West Cape wind project, located in Price Edward Island (New Brunswick), began exporting power and renewable energy certificates (RECs) to New England in mid-2007. Later that year, Hydro-Quebec received permission to sell into New England from two of its wind facilities. Finally, San Diego Gas & Electric announced a 20year contract with the proposed 250-MW La Rumorosa wind project in Baja, Mexico.

Source: Berkeley Lab estimates based on AWEA project database. Figure 11. Cumulative and 2007 Wind Capacity Categorized by Owner Type.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

68

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Source: Berkeley Lab estimates based on AWEA project database. Figure 12. Cumulative and 2007 Wind Capacity Categorized by Power Off-Take Arrangement.

UPWARD PRESSURE ON WIND POWER PRICES CONTINUED IN 2007 Although the wind industry appears to be on solid footing, the weakness of the dollar, rising materials costs, a concerted movement towards increased manufacturer profitability, and a shortage of components and turbines continued to put upward pressure on wind turbine costs, and therefore wind power prices, in 2007. Berkeley Lab maintains a database of wind power sales prices, which currently contains price data for 128 projects installed between 1998 and the end of 2007. These wind projects total 8,303 MW, or 55% of the wind capacity brought on line in the United States over the 1998-2007 period. The prices in this database reflect the price of electricity as sold by the project owner, and might typically be considered busbar energy prices.22 The prices are suppressed by the receipt of any available state and federal incentives (e.g., the PTC), as well as by the value that might be received through the separate sale of renewable energy certificates (see REC Markets Remain Fragmented and Prices Volatile, page 18).23 The prices

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

69

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

reported here would therefore be higher if wind projects did not have access to these state and federal incentives and, as a result, these prices do not represent wind energy genera-tion costs. Based on this database, the capacity-weighted average power sales price from the sample of post-1997 wind projects remains low by historical standards. Figure 13 shows the cumulative capacity weighted average wind power price (plus or minus one standard deviation around that price) in each calendar year from 1999 through 2007. Based on the limited sample of seven projects built in 1998 or 1999 and totaling 450 MW, the weightedaverage price of wind in 1999 was nearly $63/MWh (expressed in 2007 dollars). By 2007, in contrast, the cumulative sample of projects built from 1998 through 2007 had grown to 128 projects totaling 8,303 MW, with an average price of just under $40/MWh (with the one standard deviation range extending from $24/MWh to $55/MWh).24 Although Figure 13 does show a modest increase in the weighted average wind power price in 2006 and 2007, reflecting rising prices from new projects, the cumulative nature of the graphic mutes the degree of increase.

Source: Berkeley Lab database. Figure 13. Cumulative Capacity-Weighted-Average Wind Power Prices Over Time.

Source: Berkeley Lab database. Figure 14. 2007 Wind Power Prices by Commercial Operation Date (COD).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

70

U.S. Department of Energy

Source: Berkeley Lab database.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 15. 2007 Wind Power Prices by Region: 2006-2007 Projects Only.

To better illustrate changes in the price of power from newly built wind projects, Figure 14 shows average wind power sales prices in 2007, grouped by each project’s initial commercial operation date (COD).25 Although the limited project sample and the considerable variability in price across projects installed in a given time period complicate analysis of national price trends (with averages subject to regional and other factors), the general trend exhibited by the capacity-weighted-average prices (i.e., the blue columns) neverthe-less suggests that, following a general decline since 1998, prices bottomed out for projects built in 2002 and 2003, and have since risen significantly.26 Given the year-on-year increase in project-level installed costs from 2006 to 2007 (see a later section of this report), however, it comes as some surprise that prices from projects installed in 2007 were, on average, somewhat lower than from projects installed in 2006. Specifically, the capacity- weighted average 2007 sales price for projects in the sample built in 2007 was roughly $45/MWh (with a range of $30 to $65/MWh).27 Although this price is (somewhat surprisingly) slightly less than the average of $48/MWh for the sample of projects built in 2006, it is still higher than the average price of $37/MWh for the sample of projects built in 2004 and 2005, as well as the $32/MWh for the sample of projects built in 2002 and 2003. Moreover, because ongoing turbine price increases are not fully reflected in 2007 wind project prices—many of these projects had locked in turbine prices and/ or negotiated power purchase agreements as much as 18 to 24 months earlier—prices from projects being built in 2008 and beyond may be higher still. The underlying variability in the price sample is caused in part by regional factors, which may affect not only project capacity factor (depending on the strength of the wind resource in a given region), but also development and installation costs (depending on a region’s physical geography, population density, or even regulatory processes).28 Figure 15 shows individual project and average 2007 wind power prices by region for just those wind projects installed in 2006 and 2007 (a period of time in which pricing was reasonably consistent), with regions as defined in Figure 16. Although sample size is extremely problematic in numerous regions,29 Texas and the Heartland region appear to be among the lowest cost on average, while the East, California, and New England are among the higher cost areas.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

71

WIND REMAINED COMPETITIVE IN WHOLESALE POWER MARKETS A simple comparison of the wind prices presented in the previous section to recent wholesale power prices throughout the United States demonstrates that wind power prices have been competitive with wholesale power market prices over the past few years. Figure 17 shows the range (minimum and maximum) of average annual wholesale power prices for a flat block of power30 going back to 2003 at twenty-three different pricing nodes located throughout the country (refer to Figure 16 for the names and approximate locations of the twenty-three pricing nodes repre-sented by the blue-shaded area31). The red dots show the cumula-tive capacity-weighted-average price received by wind projects in each year among those projects in the sample with commercial operation dates of 1998 through 2007 (consistent with the data first presented in Figure 13). At least on a cumulative basis within the sample of projects reported here, average wind power prices have consistently been at or below the low end of the wholesale power price range.

M aine Z o ne

M id -C

•

°

C OB

•

WAUE Inter face

•

°

•

Mead

• •

°

F our C o rners

•

M as s Hub

Michigan Hub

NYISO G •N YI SO•A •

• • PJ M W est • Cinergy Hub • Illinois H ub • DOM ° Z one

NI H ub Iowa Zone

NP -15

SP -15

°

M innes ota H ub

M is souri Z one

•

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Palo Ve rde

• ERCOT West

•Entergy

Northwest California Mountain Texas Heartland Great Lakes East New England Southeast

Figure 16. Map of Regions and Wholesale Price Hubs Used in Analysis.

Source: FERC 2006 and 2004 "State of the Market" reports, Berkeley Lab database, Ventyx. Figure 17. Average Cumulative Wind and Wholesale Power Prices over Time. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

72

U.S. Department of Energy REC Markets Remain Fragmented and Prices Volatile

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Most of the wind power transactions identified in Figures 13 through 15 reflect the bundled sale of both electricity and RECs, but for at least 10 of these projects, RECs may be sold sepa-rately to earn additional revenue. REC markets are highly fragmented in the United States, but consist of two distinct segments: compliance markets in which RECs are purchased to meet state RPS obligations, and green power markets in which RECs are purchased on a voluntary basis. The year 2007 saw the completion of two new regional electronic REC tracking systems: the Western Renewable Energy Generation Information System (WREGIS) and the Midwest Renewable Energy Tracking System (MRETS). As such, electronic REC tracking systems are now widespread, with operational systems in New England, the PJM Interconnection, Texas, the Western Electricity Coordinating Council, and the upper Midwest, and another system under development in New York.

Source: Evolution Markets.

Source: Evolution Markets. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

73

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The figures to the right present indicative monthly data on spot-market REC prices in both compliance and voluntary markets; data for compliance markets focus on the “Class I” or “Main Tier” of the RPS policies. Clearly, spot REC prices have varied substantially, both among states and over time within individual states. Key trends in 2007 compliance markets include continued high prices to serve the Massachusetts RPS, dramatically increasing prices under the Connecticut RPS, high initial prices to serve the Rhode Island RPS, and a large spike in the price for Class I certificates under the New Jersey RPS. Prices remained relatively low in Texas, Maryland, Pennsylvania, and Washington D.C. due to a surplus of eligible renewable energy supply relative to RPS-driven demand in those markets. Despite low REC prices in Texas, the combination of high wholesale power prices and the possibility of additional REC revenue increased merchant wind activity in that state in 2007. RECs offered in voluntary markets ranged from less than $5/MWh to more than $10/MWh in 2007, with strong upward movement in Western REC prices. Though Figure 17 shows that—on average—wind projects installed from 1998 through 2007 have, since 2003 at least, been priced at or below the low end of the wholesale power price range on a nationwide basis, there are clearly regional differences in wholesale power prices and in the average price of wind power. These variations are reflected in Figure 18, which focuses on 2007 wind and wholesale power prices in the same regions as shown earlier, based on the entire sample of wind projects installed from 1998 through 2007.32 Although there is quite a bit of variability within some regions, in most regions the average wind power price was below the range of average wholesale prices in 2007. To try to control for the fact that wind power prices have risen in recent years, Figure 19 focuses just on those projects in the sample that were built in 2006 and 2007 (as opposed to 1998 through 2007). At this level of granular-ity, sample size is clearly an issue in most regions. Nevertheless, while there is greater convergence between wind and wholesale prices in this instance, power prices from wind projects built in 2006 and 2007 still appear, for the most part, to be either within or below the range of 2007 wholesale power prices. Rising wholesale power prices since earlier in the decade have, to a degree, mitigated the impact of rising wind power prices on wind’s competitive position. Notwithstanding the comparisons made in Figures 17-19, it should be recognized that neither the wind nor wholesale power prices presented in this section reflect the full social costs of power generation and delivery. Specifically, the wind power prices are suppressed by virtue of federal and, in some cases, state tax and financial incentives (a few projects also receive additional revenue from unbundled REC sales). Furthermore, these prices do not fully reflect integration, resource adequacy, or transmission costs. At the same time, wholesale power prices do not fully reflect transmission costs, may not fully reflect capital and fixed operating costs, and are suppressed by virtue of any financial incentives provided to fossilfueled generation and by not fully accounting for the environmental and social costs of that generation. In addition, wind power prices—once established—are typically fixed and known, whereas wholesale power prices are short-term and therefore subject to change over time. Finally, the location of the wholesale pricing nodes and the assumption of a flat block of power are not perfectly consistent with the location and output profile of the sample of wind projects.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

74

U.S. Department of Energy

Source: Berkeley Lab database, Ventyx. Figure 18. Wind and Wholesale Power Prices by Region: 1998-2007 Projects.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

In short, comparing wind and wholesale power prices in this manner is spurious, if one’s goal is to fully account for the costs and benefits of wind relative to its competition. Another way to think of Figures 17-19, however, is as loosely representing the decision facing wholesale power purchasers—i.e., whether to contract long-term for wind power or buy a flat block of (non-firm) spot power on the wholesale market. In this sense, the costs represented in Figures 17-19 are reasonably comparable in that they represent (to some degree, at least) what the power purchaser would actually pay.

Source: Berkeley Lab database, Ventyx. Figure 19. Wind and Wholesale Power Prices by Region: 2006-2007 Projects only.

PROJECT PERFORMANCE AND CAPITAL COSTS DRIVE WIND POWER PRICES Wind power sales prices are affected by a number of factors, two of the most important of which are installed project costs and project performance.33 Figures 20 and 21 illustrate the importance of these two variables. Figure 20 shows the relationship between project-level installed costs and power sales prices in 2007 for a sample of more than 7,200 MW of wind projects installed in the United States from 1998 through 2007.34 Though the scatter is considerable, in general, projects with higher installed costs also have higher wind power prices. Figure 21 illustrates the

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

75

relationship between project-level capacity factors in 2007 and power sales prices in that same year for a sample of more than 5,700 MW of wind projects installed from 1998 through 2006. The inverse relationship shows that projects with higher capacity factors generally have lower wind power prices, though considerable scatter is again apparent. The next few sections of this report explore trends in installed costs and project performance in more detail, as both factors can have significant effects on wind power prices.

Source: Berkeley Lab database.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 20. 2007 Wind Power Price as a Function of Installed Project Costs.

Source: Berkeley Lab database. Figure 21. 2007 Wind Power Price as a Function of 2007 Capacity Factor.

INSTALLED PROJECT COSTS CONTINUED TO RISE IN 2007, AFTER A LONG PERIOD OF DECLINE Berkeley Lab has compiled a sizable database of the installed costs of wind projects in the United States, including data on 36 projects completed in 2007 totaling 4,079 MW, or 77% of the wind power capacity installed in that year. In aggregate, the dataset includes 227 completed wind projects in the continental United States totaling 12,998 MW, and equaling

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

76

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

roughly 77% of all wind capacity installed in the United States at the end of 2007. The dataset also includes cost projections for a sample of proposed projects. In general, reported project costs reflect turbine purchase and installation, balance of plant, and any substation and/or interconnection expenses. Data sources are diverse, however, and are not all of equal credibility, so emphasis should be placed on overall trends in the data, rather than on individual project-level estimates. As shown in Figure 22, wind project installed costs declined dramatically from the beginnings of the industry in California in the 1980s to the early 2000s, falling by roughly $2,700/kW over this period.35 More recently, however, costs have increased. Among the sample of projects built in 2007, reported installed costs ranged from $1,240/kW to $2,600/kW, with an average cost of $1,710/kW. This average is up $140/kW (9%) from the average cost of installed projects in 2006 ($1,570/kW), and up roughly $370/kW (27%) from the average cost of projects installed from 2001 through 2003. Project costs are clearly on the rise. Moreover, there is reason to believe that recent increases in turbine costs did not fully work their way into installed project costs in 2007, and therefore that even higher installed costs are likely in the near future. The average cost estimate for 2,950 MW of pro-posed projects in the dataset (not shown in Figure 22, but most of which are expected to be built in 2008), for example, is $1,920/kW, or $210/kW higher than for projects completed in 2007. Project costs may be influenced by a number of factors, including project size. Focusing only on those projects completed in 2006 and 2007 (to try to remove the confounding effect of rising costs over the past few years), Figure 23 tries to identify the existence of projectlevel economies of scale. There is clearly a wider spread in project-level costs among smaller wind projects than among larger projects, but Figure 23 does not show strong evidence of econo-mies of scale.36 Given the wide spread in the data, it is clear that other factors must play a major role in determining installed project costs.

Source: Berkeley Lab database (some data points suppressed to protect confidentiality). Figure 22. Installed Wind Project Costs Over Time.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

77

Differences in installed costs exist regionally due to variations in development costs, transpor-tation costs, siting and permit-ting requirements and timeframes, and balance-of plant and construction expendi-tures. Considering projects in the sample installed in 2004 through 2007, Figure 24 shows that average costs equaled $1,540/kW nationwide over this period, but varied somewhat by region. New England was the highest cost region, while the Heartland was the lowest.37 Finally, it is important to recognize that wind is not alone in seeing upward pressure on project costs—other types of power plants have seen similar increases in capital costs in recent years. In September 2007, for example, the Edison Foundation published a report showing increases in the installed cost of both natural gas and coal power plants that rival that seen in the wind industry.38

Source: Berkeley Lab database.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 23. Installed Wind Project Costs as a Function of Project Size: 2006-2007 Projects.

Source: Berkeley Lab database. Figure 24. Installed Wind Project Costs by Region: 2004-2007 Projects.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

78

U.S. Department of Energy

PROJECT COST INCREASES ARE A FUNCTION OF TURBINE PRICES, AND TURBINE PRICES HAVE INCREASED DRAMATICALLY

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Increases in wind power prices and overall installed project costs mirror increases in the cost of wind turbines. Berkeley Lab has gathered data on 49 U.S. wind turbine transactions totaling 16,600 MW, including 16 transactions summing to 7,600 MW in 2007 alone. Figure 25 depicts these reported wind turbine transac-tion prices. Increases in wind power prices and overall installed project costs mirror increases in the cost of wind turbines. Berkeley Lab has gathered data on 49 U.S. wind turbine transactions totaling 16,600 MW, including 16 transactions summing to 7,600 MW in 2007 alone. Figure 25 depicts these reported wind turbine transac-tion prices. Since hitting a nadir of roughly $700/kW in the 2000-2002 period, turbine prices appear to have increased by approximately $600/kW (85%), on average. Between 2006 and 2007, capacity-weighted average turbine prices increased by roughly $115/kW (10%), from $1,125/kW to $1,240/kW. Recent increases in turbine prices have likely been caused by several factors, including the declining value of the U.S. dollar relative to the Euro, increased materials and energy input prices (e.g., steel and oil), a general move by manufacturers to improve their profitability, shortages in certain turbine components, an up-scaling of turbine size (and hub height), and improved sophistication of turbine design (e.g., improved grid interactions). The shortage of turbines has also led to a secondary market in turbines, through which prices may be even higher than those shown in Figure 25. Though by no means definitive, Figure 25 also suggests that larger turbine orders (> 300 MW) may have generally yielded somewhat lower pricing than smaller orders (< 100 MW) at any given point in time. This is reflected in the fact that most of the larger turbine orders shown in Figure 25 are located below the polynomial trend line, while the majority of the smaller orders are located above that line.

Source: Berkeley Lab database. Figure 25. Reported U.S. Wind Turbine Transaction Prices over Time.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

79

This trend of increasing turbine prices suggests that virtually the entire recent rise in installed project costs reported earlier has come from turbine price increases (recognizing that these prices reflect the cost of turbines, towers, and erection). In fact, because project level installed costs have increased, on average, by roughly $370/kW during the last several years, while turbine prices appear to have increased by $600/kW over the same time span, further increases in project costs should be expected in the near future as the increases in turbine prices flow through to project costs.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

WIND PROJECT PERFORMANCE HAS IMPROVED OVER TIME Though recent turbine and installed project cost increases have driven wind power prices higher, improvements in wind project performance have mitigated these impacts to some degree. In particular, capacity factors have increased for projects installed in recent years, driven by a combination of higher hub heights, improved siting, and technological advancements. Figures 26 and 27, as well as Table 7, present excerpts from a Berkeley Lab compilation of wind project capacity-factor data. The sample consists of 170 projects built between 1983 and 2006, and totaling 10,564 MW (91% of nationwide installed wind capacity at the end of 2006).39 Though capacity factors are not an ideal metric of project performance due to variations in the design and rating of wind turbines, absent rotor diameter data for each project, this report is unable to present the arguably more-relevant metric of electricity generation per square meter of swept rotor area. Both figures and the table summa-rize project-level capacity factors in the year 2007, thereby limiting the effects of inter-annual fluctuations in the nationwide wind resource.40 Figure 26 shows individual project as well as capacity-weighted average 2007 capacity factors broken out by each project’s commercial operation date. The capacity-weightedaverage 2007 capacity factors in the Berkeley Lab sample increased from 22% for wind projects installed before 1998 to roughly 30%-32% for projects installed from 1998-2003, and to roughly 33%-35% for projects installed in 2004-2006.41

Source: Berkeley Lab database. Figure 26. 2007 Project Capacity Factors by Commercial Operation Date.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

80

U.S. Department of Energy

Source: Berkeley Lab database.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 27. 2007 Project Capacity Factors by Region: 2002-2006 Projects Only.

In the best wind resource areas, capacity factors in excess of 40% are increasingly common. Of the 112 projects in the sample installed prior to 2004, for example, only 4 (3.6%) had capacity factors in excess of 40% in 2007 (in capacity terms, 56 MW, or 1%, exceeded 40%). Of the 58 projects installed from 2004 through 2006, on the other hand, 15 (25.9%) achieved capacity factors in excess of 40% in 2007 (in capacity terms, 836 MW, or 16.7%, exceeded 40%). These increases in capacity factors over time suggest that improved turbine designs, higher hub heights, and/or improved siting are outweighing the otherwise-presumed trend towards lower-value wind resource sites as the best locations are developed. Further analysis would be needed to determine the relative importance of the variables influencing performance improvements. Although the overall trend is towards higher capacity factors, the project-level spread shown in Figure 26 is enormous, with capacity factors ranging from 18% to 48% among projects built in the same year, 2006. Some of this spread is attributable to regional variations in wind resource quality. Figure 27 shows the regional variation in 2007 capacity factors, based on a sub-sample of wind projects built from 2002 through 2006. For this sample of projects, capacity factors are the highest in Hawaii (though just two projects) and the Heartland (above 35% on average), and lowest in New England, the Great Lakes, and the East (below 30% on average). Given the small sample size in some regions, however, as well as the possibility that certain regions may have experienced a particularly good or bad wind resource year in 2007, care should be taken in extrapolating these results. Though limited sample size is again a problem for many regions, Table 7 illustrates trends in 2007 capacity factors for projects with different commercial operation dates, by region. In the Heartland region, with the largest sample of projects in terms of installed capacity, the average capacity factor of projects installed in 2006 (40.8%) is approximately 35% greater than that of the 1998-1999 vintage projects in the sample (30.2%).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

81

Table 7. Capacity-Weighted-Average 2007 Capacity Factors by Region and COD Capacity Factor Pre-1998

Heartland 28.9%

Texas

Northwest —

Mountain

East

11.9%

California 22.3%

1998-99

30.2%

2000-01

Hawaii

—

Great Lakes —

—

New England 19.8%

—

28.2%

29.8%

32.1%

34.4%

—

23.4%

33.4%

29.6%

34.5%

28.7%

—

—

29.3%

22.5%

23.5%

—

27.0%

2002-03

34.4%

33.5%

32.6%

2004-05

36.8%

34.5%

37.5%

30.5%

30.3%

28.5%

21.2%

—

—

34.0%

38.9%

26.7%

31.0%

—

2006

40.8%

30.4%

36.9%

—

31.3%

34.7%

29.4%

—

45.0%

22.1%

Sample

#

Pre-1998 1998-99

MW

#

MW

#

MW

#

1

26

8

470

1

34

17

870

3

139

5

190

2000-01

10

229

7

911

1

2002-03

20

2004-05

16 1,086

628

2

198

4

461

2006

7

3

944

Total

62 2,825 20 2,686 32 1,732 15 1,440 15

386

MW

#

MW

#

MW

#

MW

#

MW

#

MW

—

—

—

—

—

—

—

—

—

—

1

6

1

25

3

68

—

—

3

22

—

—

—

—

67

3

388

4

123

6

78

2

32

—

—

1

1

4

287

2

105

3

510

3

161

1

50

—

—

—

—

3

130

5

434

3

208

2

349

1

54

—

—

—

—

2

188

4

538

2

150

1

26

—

—

2

41

3

3

1,059 12

613

7

158

2

41

5

10

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

OPERATIONS AND MAINTENANCE COSTS ARE AFFECTED BY THE AGE AND SIZE OF THE PROJECT, AMONG OTHER FACTORS Operations and maintenance (O&M) costs are a significant component of the overall cost of wind projects, but can vary widely among projects. Market data on actual project-level O&M costs for wind plants are scarce. Even where these data are available, care must be taken in extrapolating historical O&M costs given the dramatic changes in wind turbine technology that have occurred over the last two decades, not least of which has been the upscal-ing of turbine size (see Figure 9, earlier). Berkeley Lab has compiled O&M cost data for 95 installed wind plants in the United States, totaling 4,319 MW of capacity, with commercial operation dates of 1982 through 2006. These data cover facilities owned by both independent power producers and utilities, though data since 2004 is exclusively from utility-owned plants. A full-time series of O&M cost data, by year, is available for only a small number of projects; in all other cases, O&M cost data are available for just a subset of years of project operations. Although the data sources do not all clearly define what items are included in O&M costs, in most cases the reported values appear to include the costs of wages and materials associated with operating and maintaining the facility, as well as rent (i.e., land lease payments). Other ongoing expenses, including taxes, property insurance, and workers’ com-pensation insurance, are generally not included. Given the scarcity and varying quality of the data, caution should be taken when interpreting the results shown below. Note also that the available data are presented in $/MWh terms, as if O&M represents a variable cost. In fact, O&M costs are in part variable and in part fixed. 42

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

82

U.S. Department of Energy

Figure 28 shows project-level O&M costs by year of project installation (i.e., the last year that original equipment was installed, or the last year of project repowering). Here, O&M costs represent an average of annual project-level data available for the years 2000 through 2007. For example, for projects that reached commercial operations in 2006, only year 2007 data are available, and that is what is shown in the figure.43 Many other projects only have data for a subset of years during the 2000-2007 period, either because they were installed after 2000 or because a full-time series is not available, so each data point in the chart may represent a different averaging period over the 2000-07 timeframe. The chart also identifies which of the data points contain the most-updated data, from 2007. The data exhibit considerable spread, demonstrating that O&M costs are far from uniform across projects. However, Figure 28 suggests that projects installed more recently have, on average, incurred much lower O&M costs. Specifically, capacity-weighted average 2000-2007 O&M costs for projects in the sample con-structed in the 1980s equal $30/MWh, dropping to $20/MWh for projects installed in the 1990s, and to $9/MWh for projects installed in the 2000s. This drop in O&M costs may be due to a combination of at least two factors: (1) O&M costs generally increase as turbines age, component failures become more common, and as manufac-turer warranties expire44; and (2) projects installed more recently, with larger turbines and more sophisticated designs, may experi-ence lower overall O&M costs on a per-MWh basis. To help tease out the possible influence of these two factors, Figure 29 shows annual O&M costs over time, based on the number of years since the last year of equipment installation. Annual data for projects of similar vintages are averaged together, and data for projects under 5 MW in size are excluded (to help control for the confounding influence of economies of scale). Note that, for each group, the number of projects used to compute the average annual values shown in the figure is limited, and varies substantially (from 3 to 21 data points per project-year for projects installed in 1998 through 2000; 10 data points per project-year for projects installed in 2001 through 2003; and from 3 to 6 data points for projects installed in 2004 through 2006). With this limitation in mind, the figure appears to show that projects installed in 2001 and later have had lower O&M costs than those installed from 1998 through 2000, at least during the initial two years of operation. In addition, the data for projects installed from 1998 through 2000 show a quite modest upward trend in project-level O&M costs after the third year of project operation, though the sample size after year four is quite limited. Another variable that may impact O&M costs is project size. Figure 30 presents average O&M costs for 2000 through 2007 (as in Figure 28) relative to project size. Though substantial spread in the data exists and the sample is too small for definite conclusions, project size does appear to have some impact on average O&M costs, with higher costs typically experienced by smaller projects. More data would be needed to confirm this inference. Though interesting, the trends noted above are not necessarily useful predictors of long-term O&M costs for the latest turbine models. The U.S. DOE, in collaboration with the wind industry, is currently funding additional efforts to better understand the drivers for O&M costs and component failures, and to develop models to project future O&M costs and failure events.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

83

Source: Berkeley Lab database; five data points suppressed to protect confidentiality Figure 28. Average O&M Costs for Available Data Years from 2000-2007, by Last Year of Equipment Installation.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

NEW STUDIES CONTINUED TO FIND THAT INTEGRATING WIND INTO POWER SYSTEMS IS MANAGEABLE, BUT NOT COSTLESS During the past several years, there has been a considerable amount of analysis on the potential impacts of wind energy on power systems, typically responding to concerns about whether the electrical grid can accommodate significant new wind additions, and at what cost. The sophistication of these studies has increased in recent years, resulting in a better accounting of wind’s impacts and costs. Key trends among some of the more recent studies include evaluating even higher levels of wind penetration, evaluating the integration of wind within larger electricity market areas, and identifying approaches to mitigate integration concerns.

Source: Berkeley Lab database; averages shown only for groups of three or more projects. Figure 29. Annual Average O&M Costs, by Project Age and Last Year of Equipment Installation. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

84

U.S. Department of Energy

Source: Berkeley Lab database; averages shown only for groups of three or more projects.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 30. Average O&M Costs for Available Data Years from 2000-2007, by Project Size.

Table 8 provides a selective listing of results from major wind integration studies completed from 2003 through 2007.45 Because methods vary and a consistent set of operational impacts has not been included in each study, results from the different analyses are not entirely comparable. Nonetheless, key conclusions that continue to emerge from the growing body of integration literature include: (1) wind integration costs are well below $10/ MWh—and typically below $5/ MWh—for wind capacity penetra-tions46 of as much as 30% of the peak load of the system in which the wind power is delivered47; (2) regulation impacts are often found to be relatively small, whereas the impacts of wind on load-following and unit commitment are typically found to be more signifi-cant; (3) larger balancing areas, such as those found in RTOs and ISOs, make it possible to integrate wind more easily and at lower cost than is the case in small balancing areas48; and (4) the use of wind power forecasts can significantly reduce integration challenges and costs. Additional wind integration research is planned for 2008. Perhaps of greatest import is that the National Renewable Energy Laboratory is in the process of examining higher levels of wind penetration in larger electrical footprints. The Western Wind and Solar Integration Study (WWSIS), in collaboration with GE and WestConnect, is analyzing wind penetration levels of up to 30% on an energy basis in the WestConnect footprint, which includes parts of Wyoming, Colorado, New Mexico, Arizona, and Nevada. The Eastern Wind Integration Study, to be conducted in collaboration with the Joint Coordinated System Plan (whose participants include MISO, SPP, TVA, and PJM), will examine a similar wind penetration in the combined footprint of these RTOs and ISOs49 Finally, in 2008, ERCOT will issue a study by GE on the potential impact of wind development on ERCOT’s ancillary service requirements.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

85

SOLUTIONS TO TRANSMISSION BARRIERS BEGAN TO EMERGE, BUT CONSTRAINTS REMAIN After a prolonged period of relatively little transmission invest-ment, expenditures on new transmission are on the rise. The Edison Electric Institute, for example, projects that its member companies will invest $37 billion in transmission from 2007-2010, a 55% increase from the 2003-2006 period. Nonetheless, lack of transmission availability remains a primary barrier to wind development. New transmission facilities are particularly important for wind power because wind projects are constrained to areas with adequate wind speeds, which are often located at a distance from load centers. In addition, there is a mismatch between the short lead time needed to develop a wind project and the lengthier time often needed to develop new transmission lines. Moreover, the relatively low capacity factor of wind can lead to underutilization of new transmission lines that are intended to only serve this resource. The allocation of costs for new transmission investment is also of critical importance for wind development, as are issues of transmission rate “pancaking” when power is wheeled across multiple utility systems, charges imposed for inaccurate scheduling of wind generation, and interconnection queuing procedures. Table 8. Key Results from Major Wind Integration Studies Completed 2003-2007

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Date

2003 2003 2004 2005 2006 2006 2006 2007 2007 2007 2007

Study

Xcel-UWIG We Energies XcelMNDOC PacifiCorp CA RPS (multi-year)* Xcel-PSCo MN-MISO** Puget Sound Energy Arizona Public Service Avista Utilities*** Idaho Power

Wind Capacity Penetration 3.5% 29% 15%

Cost ($/MWh) Regu- Load Unit lation Following Commitment 0 0.41 1.44 1.02 0.15 1.75 0.23 na 4.37

Gas Supply na na na

Total

20% 4%

0 0.45

1.60 trace

3.00 trace

na na

4.60 0.45

15% 31% 10%

0.20 na na

na na na

3.32 na na

1.45 na na

4.97 4.41 5.50

15%

0.37

2.65

1.06

na

4.08

30%

1.43

4.40

3.00

na

8.84

20%

na

na

na

na

7.92

* regulation costs represent 3-year average ** highest over 3-year evaluation period *** unit commitment includes cost of wind forecast error. Source: Berkeley Lab based, in part, on data from NREL.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

1.85 2.92 4.60

86

U.S. Department of Energy

A number of federal, state, and regional developments occurred in 2007 that may help ease the transmission barrier for wind over time. At the federal level, the U.S. DOE issued its National Electric Transmission Congestion Report, which desig-nates two constrained corridors: the Southwest Area National Interest Electric Transmission Corridor and the MidAtlantic Area National Interest Electric Transmission Corridor. Under the Energy Policy Act of 2005, FERC can approve proposed new transmission facilities in these corridors if states fail to do so within one year, among other conditions. The U.S. DOE’s designations have proven controversial, however, and multiple efforts to reverse these designations have occurred or are underway. Also at the federal level, in February 2007, FERC issued Order 890, which includes several provisions of importance to wind. First, the order adopts a cost-based energy imbalance policy that replaces the penalty-based energy imbalance charges that applied under FERC Order 888 and that were much more punitive for wind. Second, the order requires transmission providers to participate in an open transmission planning process at the local and regional level. Third, if transmission capacity is unavailable to service a firm point-to-point transmission application, then the transmission provider is required to examine redispatch and conditional firm service as alternative transmission service options. More recently, FERC has begun to investigate ways to ease barriers imposed by current interconnection queuing procedures; more activity on this topic is expected in 2008. States and grid operators are also increasingly taking more proactive steps to encourage transmission investment, often within the context of growing renewable energy demands. Several examples of these initiatives are presented below:

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

•

•

Texas: In October 2007, the Texas public utilities commission (PUC) issued an interim order designating five competitive renewable energy zones (CREZ), defined as areas of high-quality renewable resources to which transmission could be built in advance of installed generation. These CREZs could stimulate as much as 22,806 MW of new wind power capacity, and ERCOT has subsequently completed a transmission study for these areas. Colorado: Legislation enacted in January 2007 requires utilities to submit biennial reports designating energy resource zones (ERZs) and to submit applications for certificates of public convenience and necessity (CPCN) for these areas. In October 2007, Xcel Energy identified four potential ERZ areas, created in large measure to support renewable energy development, and the Colorado PUC recently approved Xcel’s application for a 345-kV line in northeastern Colorado.50 California: In late 2007, the California ISO received FERC approval for a new transmission interconnection category for location constrained resources, such as renewable energy facilities. Once a resource area has been identified, transmission would be built in advance of generation being developed, and costs would be initially recovered through the California ISO transmis-sion charge. California also started the Renewable Energy Transmission Initiative to help define renewable energy zones in and around the state, and to prepare transmission plans for those zones.

Progress was also made in 2007 on a number of specific trans-mission projects that are designed to, in part, support wind power. In March 2007, for example, the California PUC Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

87

approved the first three of ultimately 11 segments of Southern California Edison’s Tehachapi transmission project. Fully developed, the project will transmit up to 4,500 MW of wind power. In Minnesota, meanwhile, utilities that are part of the CapX 2020 statewide transmission planning group filed applications at the Minnesota PUC for four 345-kV lines that will collectively increase transmission capacity in southwestern Minnesota by 800 MW, to about 2,000 MW total. Finally, a number of states have created transmission infrastructure authorities to support new transmission investment;51 two of these states—Colorado and New Mexico—created transmission authori-ties in 2007 in large measure to support renewable energy.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

POLICY EFFORTS CONTINUED TO AFFECT THE AMOUNT AND LOCATION OF WIND DEVELOPMENT A variety of policy drivers have been important to the recent expansion of the wind power market in the United States. Most obviously, the continued availability of the federal PTC has sustained industry growth. First established by the Energy Policy Act of 1992, the PTC provides a 10-year credit at a level that equaled 2.0¢/kWh in 2007 (adjusted annually for inflation). The importance of the PTC to the U.S. wind industry is illustrated by the pronounced lulls in wind capacity additions in the three years—2000, 2002, and 2004—in which the PTC lapsed (see Figure 1). With the PTC cur-rently (as of early-May 2008) scheduled to expire at the end of 2008, the U.S. wind industry may experience another quiet year in 2009 absent an imminent extension. A number of other federal policies also support the wind industry. Wind power property, for example, may be depreciated for tax purposes over an accelerated 5-year period, with bonus depreciation allowed for certain projects completed in 2008. Because tax-exempt entities are unable to take direct advantage of tax incentives, the Energy Policy Act of 2005 created the Clean Renewable Energy Bond (CREB) program, effectively offering interest-free debt to eligible renewable projects (though not without certain additional transaction costs).52 Finally, the USDA provides grants to certain renewable energy applications. State policies also continue to play a substantial role in directing the location and amount of wind development. From 1999 through 2007, for example, more than 55% of the wind power capacity built in the U.S. was located in states with RPS policies; in 2007 alone, this proportion was more than 75%. Utility resource planning require-ments in Western and Midwestern states have also helped spur wind additions in recent years, as has growing voluntary customer demand for “green” power, especially among commercial custom-ers. State renewable energy funds provide support for wind projects, as do a variety of state tax incentives. Finally, concerns about the possible impacts of global climate change are fueling interest by states, regions, and the federal government to imple-ment carbon reduction policies, a trend that is likely to increasingly underpin wind power expansion in the years ahead. Key policy developments in 2007 included:

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

88

U.S. Department of Energy •

•

•

•

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

In February 2008, the IRS announced the distribution of roughly $400 million in CREBs, based on applications received in 2007, including $170 million for 102 wind power projects. In September 2007, a total of more than $18 million in grant and loan awards were announced under the USDA’s Section 9006 grant program, including $2.7 million for 7 “large wind” projects totaling 8.2 MW in capacity. Illinois, New Hampshire, North Carolina, and Oregon enacted mandatory RPS policies in 2007, while Ohio established an RPS in early 2008, bringing the total to 26 states and Washington D.C. (see Figure 31). A large number of additional states strengthened previously established RPS programs in 2007. A variety of states and regions continued to make progress in implementing carbon reduction policies, and a rising number of electric utilities considered the possible implementation of carbon regulation in their resource planning and selection processes. State renewable energy funds, state tax incentives, utility resource planning requirements, and green power markets all helped contribute to wind expansion in 2007.

Source: Berkeley Lab. Figure 31. State RPS Policies and Non-Binding Renewable Energy Goals (as of May 2008).

COMING UP IN 2008 Though transmission availability, siting and permitting conflicts, and other barriers remain, 2008 is, by all accounts, expected to be another banner year for the U.S. wind industry. Another year of capacity growth in excess of 5,000 MW appears to be in the offing, and past installation records may again fall. Local manufacturing of turbines and components

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

89

is also anticipated to continue to grow, as announced manufacturing facilities come on line and existing facilities reach capacity and expand. And all of this is likely to occur despite the fact that wind power pricing is projected to continue its upwards climb in the near term, as increases in turbine prices make their way through to wind power purchasers. Supporting continued market expansion, despite unfavorable wind pricing trends, are the rising costs of fossil generation, the mounting possibility of carbon regulation, and the growing chorus of states interested in encouraging wind power through policy measures. If the PTC is not extended, however, 2009 is likely to be a difficult year of industry retrenchment. The drivers noted above should be able to underpin some wind capacity additions even in the absence of the PTC, and some developers may continue to build under the assumption that the PTC will be extended and apply retroac-tively. Nonetheless, most developers are expected to “wait it out,” re-starting construction activity only once the fate of the PTC is clear.

APPENDIX: SOURCES OF DATA PRESENTED IN THIS REPORT

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wind Installation Trends Data on wind power additions in the United States come from AWEA. Annual wind capital investment estimates derive from multiplying these wind capacity data by weightedaverage capital cost data, provided elsewhere in the report. Data on non-wind electric capacity additions come primarily from the EIA (for years prior to 2007) and Ventyx’s Energy Velocity database (for 2007), except that solar data come from the Interstate Renewable Energy Council (IREC) and Berkeley Lab. Data on the distributed wind segment come primarily from AWEA and, to a lesser extent, NREL. Information on offshore wind development activity in the United States was compiled by NREL. Global cumulative (and 2007 annual) wind capacity data come from BTM Consult, but are revised to include the most recent AWEA data on U.S. wind capacity. Historical cumulative and annual worldwide capacity data come from BTM Consult and the Earth Policy Institute. Wind as a percentage of country-specific electricity consumption is based on end-of-2007 wind capacity data and country-specific assumed capacity factors that primarily come from BTM Consult’s World Market Update 2007. For the United States, the performance data presented in this report are used to estimate wind production. Countryspecific projected wind generation is then divided by projected electricity consumption in 2008 (and 2007), based on actual 2005 consumption and a country-specific growth rate assumed to be the same as the rate of growth from 2000 through 2005 (these data come from the EIA’s International Energy Annual). The wind project installation map of the United States was created by NREL, based in part on AWEA’s database of wind power projects and in part on data from Platts on the location of individual wind power plants. Effort was taken to reconcile the AWEA project database and the Platts-provided project locations, though some discrepancies remain. Wind as a percentage contribution to statewide electricity generation is based on AWEA installed capacity data for the end of 2007 and the underlying wind project performance data presented

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

90

U.S. Department of Energy

in this report. Where necessary, judgment was used to estimate state-specific capacity factors. The resulting state wind generation is then divided by in-state total electricity generation in 2007, based on EIA data. Data on wind capacity in various interconnection queues come from a review of publicly available data provided by each ISO, RTO, or utility. Only projects that were active in the queue at the end of 2007, but that had not yet been built, are included. Suspended projects are not included in these listings.

Wind Capacity Serving Electric Utilities

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The listing of wind capacity serving specific electric utilities comes from AWEA’s 2008 Annual Rankings Report. To translate this capacity to projected utility-specific annual electricity generation, regionally appropriate wind capacity factors are used. The resulting utility-specific projected wind generation is then divided by the aggregate national retail sales of each utility in 2006 (based on EIA data). Only utilities with 50 MW or more of wind capacity are included in these calculations. In the case of G&T cooperatives and power authorities that provide power to other cooperatives and municipal utilities (but do not directly serve load themselves), this report uses 2006 retail sales from the electric utilities served by those G&T cooperatives and power authorities. In some cases, these individual utilities may be buying additional wind directly from other projects, or may be served by other G&T cooperatives or power authorities that supply wind. In these cases, the penetration percentages shown in the report may be understated. Finally, some of the entities shown in Table 3 are wholesale power marketing companies that are affiliated with electric utilities. In these cases, estimated wind generation is divided by the retail sales of the power marketing company and any affiliated electric utilities.

Turbine Manufacturing, Turbine Size, and Project Size Turbine manufacturer market share, average turbine size, and average project size are derived from the AWEA wind project database. Information on wind turbine and component manufacturing come from NREL, AWEA, and Berkeley Lab, based on a review of press reports, personal communications, and other sources. The listings of manufacturing and supply chain facilities are not intended to be exhaustive. Information on wind developer consolidation and financing trends were compiled by Berkeley Lab. Wind project ownership and power purchaser trends are based on a Berkeley Lab analysis of the AWEA project database.

Wind Power Prices and Wholesale Market Prices Wind power price data are based on multiple sources, including prices reported in FERC’s Electronic Quarterly Reports (in the case of non-qualifying-facility projects), FERC Form 1, avoided cost data filed by utilities (in the case of some qualifying-facility projects),

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

91

pre-offering research conducted by Standard & Poor’s and other bond rating agencies, and a Berkeley Lab collection of power purchase agreements. Wholesale power price data were compiled by Berkeley Lab from FERC’s 2006 State of the Markets Report and 2004 State of the Markets Report, as well as from Ventyx’s Energy Velocity database of wholesale power prices (which itself derives data from the IntercontinentalExchange—ICE—and the various ISOs). REC price data were compiled by Berkeley Lab based on a review of Evolution Markets’ monthly REC market tracking reports.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Installed Project and Turbine Costs Berkeley Lab used a variety of public and some private sources of data to compile capital cost data for a large number of U.S. wind power projects. Data sources range from preinstallation corporate press releases to verified post-construction cost data. Specific sources of data include: EIA Form 412, FERC Form 1, various Securities and Exchange Commission filings, various filings with state public utilities commissions, Windpower Monthly magazine, AWEA’s Wind Energy Weekly, DOE/EP RI’s Turbine Verification Program, Project Finance magazine, various analytic case studies, and general web searches for news stories, presentations, or information from project developers. Some data points are suppressed in the figures to protect data confidentiality. Because the data sources are not equally credible, little emphasis should be placed on individual project-level data; instead, it is the trends in those underlying data that offer insight. Only wind power cost data from the contiguous lower-48 states are included. Wind turbine transaction prices were compiled by Berkeley Lab. Sources of transaction price data vary, but most derive from press releases and press reports. In part because wind turbine transactions vary in the services offered, a good deal of intra-year variability in the cost data is apparent.

Wind Project Performance Wind project performance data are compiled overwhelmingly from two main sources: FERC’s Electronic Quarterly Reports and EIA Form 906. Additional data come from FERC Form 1 filings and, in several instances, other sources. Where discrepancies exist among the data sources, those discrepancies are handled based on the judgment and experience of Berkeley Lab staff.

Wind Project Operations and Maintenance Costs Wind project operations and maintenance costs come primarily from two sources: EIA Form 412 data from 2001-2003 for private power projects and projects owned by POUs, and FERC Form 1 data for IOU-owned projects. Some data points are suppressed in the figures to protect data confidentiality.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

92

U.S. Department of Energy

Wind Integration, Transmission, and Policy The wind integration, transmission, and policy sections were written by staff at Berkeley Lab, NREL, and Exeter Associates, based on publicly available information.

ACKNOWLEDGEMENTS For their support of this project, the authors thank Drew Ronneberg, Steve Lindenberg, Phil Dougherty, and Alejandro Moreno of the U.S. DOE’s Wind & Hydropower Technologies Program. For providing information or reviewing elements of this paper, we thank: Karlynn Cory (NREL), Dennis Lin (U.S. DOE), Brad Nickell (U.S. DOE), Drew Ronneberg (U.S. DOE), Liz Salerno (AWEA), Linda Silverman (U.S. DOE), Charlie Smith (UWIG), and Larry Willey (GE). Special thanks to the American Wind Energy Association for the use of their database of wind power projects, and for providing other data as discussed in the Appendix. We also thank Bruce Green, Kathleen O’Dell, Susan Sczepanski, and Billy Roberts of NREL for assistance with editing, layout, formatting, and production. Berkeley Lab’s contributions to this report were funded by the Wind & Hydropower Technologies Program, Office of Energy Efficiency and Renewable Energy of the U.S. Department of Energy under Contract No. DE-AC02-05CH1 1231. The authors are solely responsible for any omissions or errors contained herein.

ENDNOTES Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

1

These investment figures are based on an extrapolation of the average project-level capital costs reported later in this report. Annual O&M, R&D, and manufacturing expenditures, which are not included here, would add to these figures. 2 Given the relatively low capacity factor of wind, one might initially expect that wind’s percentage contribution on an energy basis would be lower than on a capacity basis. This is not necessarily the case, in part because even though combined-cycle gas plants can be operated as baseload facilities with high capacity factors, those facilities are often run as intermediate plants with capacity factors that are not dissimilar from that of wind. Combustion turbine facilities run at even lower capacity factors. 3 Yearly and cumulative installed wind capacity in the United States are from AWEA, while global wind capacity comes from BTM Consult (but updated with the most recent AWEA data for the United States) and, for earlier years, from the Earth Policy Institute. Modest disagreement exists among these data sources and others, e.g., Windpower Monthly and the Global Wind Energy Council. 4 In terms of actual 2007 deliveries, wind represented 0.77% of net electricity generation in the United States, and roughly 0.72% of national electricity consumption. These figures are below the 1.2% figure provided above because 1.2% is a projection based on end-ofyear 2007 wind capacity. 5 “Large-scale” turbines are defined consistently with the rest of this report—over 50 kW.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

6

93

To estimate these figures, end-of-2007 wind capacity is translated into estimated annual wind electricity production based on state-specific capacity factors that derive from the project performance data reported later in this report. The resulting state-specific wind production estimates are then divided by the latest data on total in-state electricity generation available from the EIA (i.e., 2007). The resulting wind penetration estimates shown in Table 2 differ from what AWEA provided in its Annual Rankings Report. The most significant source of these differences is that AWEA estimates wind generation based on end of-2006 wind capacity, while this report uses end-of-2007 capacity. In addition, Berkeley Lab uses state-specific wind capacity factor assumptions that differ from those applied by AWEA. 7 A variety of caveats deserve note with respect to these calculations. First, the utility-specific capacity data that AWEA released in its Annual Ranking Report are assumed accurate, and are used without independent verification. Second, only utilities with 50 MW or more of wind capacity are included in the calculation of wind as a proportion of retail sales. Third, projected wind generation based on each utility’s installed wind capacity at the end of 2007 is divided by the aggregate national retail sales of that utility in 2006 (which is the latest full year of utility-specific retail sales data provided by EIA). Fourth, in the case of generation and transmission (G&T) cooperatives and power authorities that provide power to other cooperatives and municipal utilities (but do not directly serve retail load themselves), 2006 retail sales from the electric utilities served by those G&T cooperatives and power authorities are used. In some cases, these individual utilities may be buying additional wind power directly from other projects, or may be served by other G&T cooperatives or power authorities that supply wind. In these cases, the penetration percentages shown here may be understated (or at least somewhat misleading). As an example, the “MSR Public Power Agency” (MSR) is a joint powers agency created to procure power for municipal utilities in the California cities of Modesto, Santa Clara, and Redding. The 200 MW of wind capacity associated with MSR in the first column of Table 3 (and the corresponding 8.4% penetration rate shown in the second column) represents MSR’s power purchase agreement with the Big Horn wind project in Washington state. However, two of the three municipal utilities participating in MSR purchase additional wind power from California wind projects. The result is that if one were to look at these three municipal utilities individually rather than as a group through MSR, their penetration rates would be considerably higher than the 8.4% shown in Table 3, and all three utilities would be at the top of the rankings: Redding would be roughly 24.2%, Santa Clara 12.3%, and Modesto 11.8%. Finally, some of the entities shown in Table 3 are wholesale power marketing companies that are affiliated with electric utilities. In these cases, estimated wind generation is divided by the retail sales of the power marketing company and any affiliated electric utilities. 8 The queues surveyed include PJM Interconnection, Midwest Independent System Operator (MISO), New York ISO, ISO-New England, California ISO, Electricity Reliability Council of Texas (ERCOT), Southwest Power Pool (SPP), Western Area Power Administration (WAPA), Bonneville Power Administration (BPA), PacifiCorp, and Xcel Energy (Colorado). To provide a sense of sample size and coverage, roughly 60% of the total installed generating capacity (both wind and non-wind) in the United States is located within these ISOs, RTOs, and utility service territories. Figure 6 only includes

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

94

U.S. Department of Energy

projects that were active in the queue at the end of 2007 but that had not yet been built; suspended projects are not included. 9 FERC held a technical conference in November 2007 focusing on the burgeoning interconnection queues and potential reforms. 10 Market share reported here is in MW terms, and is based on project installations—not turbine shipments or orders—in the year in question. 11 In addition, in 2008, Fuhrlander announced its decision to build a turbine assembly plant in Butte, Montana, with an expected 150 jobs. 12 Except for 2006 and 2007, Figure 9 (as well as a number of the other figures and tables included in this report) combines data into two-year periods in order to avoid distortions related to small sample size in the PTC lapse years of 2000, 2002, and 2004. Though not a PTC lapse year, 1998 sample size is also small, and is therefore combined with 1999. 13 Projects less than 2 MW in size are excluded from Figure 10 so that a large number of single-turbine “projects” (that, in practice, may have been developed as part of a larger, aggregated project) do not end up skewing the average. For projects defined in phases, each phase is considered to be a separate project. Projects that are partially constructed in two different years are counted as coming online in the year in which a clear majority of the capacity was completed. If roughly equal amounts of capacity are built in each year, then the full project is counted as coming online in the later year. 14 Only transactions that are known to involve 500 MW or more of in-development wind projects are included. 15 For more information on these and other structures, see Wind Project Financing Structures: A Review & Comparative Analysis, downloadable from http://eetd.lbl.gov/ea/ems/reports/ 63434.pdf. 16 In a telling move, Spanish wind giant Iberdrola announced in June 2007 that it intended to buy Energy East—an investor-owned utility holding company in the Northeastern United States—in part to generate U.S. income tax liability that would better enable it to use the production tax credits and depreciation deductions generated by its U.S. wind project investments. 17 In contrast to its favorable implications for the institutional investor flip structure, Revenue Procedure 2007-65 is less-favorable to the pay-as-you-go (PAYGO) structure, under which the tax investor injects equity into the project over time, but only as PTCs are generated. Specifically, the Revenue Procedure limits the amount of PTC-contingent equity to 25% of the total anticipated tax equity (prior to the Revenue Procedure, the general assumption was that up to 50% of the tax equity could be PTC-contingent). 18 Institutional tax investors active in the wind market include GE Financial Services, JP Morgan Capital, Morgan Stanley, Lehman Brothers, Fortis Capital, Wachovia, Wells Fargo, Union Bank of California, Prudential Capital, Northwestern Mutual, New York Life, Babcock & Brown, Meridian Clean Fuels, and AEGON USA Realty Advisors. 19 Compared to the recent past, the growth in publicly owned utility ownership in 2007 is striking. This growth is, arguably, inflated by the categorization of the 205-MW White Creek Wind project as a POU-owned project. Although the four POUs involved with the White Creek project do not technically own any part of the project unless and until they exercise their purchase option (after the project’s tenth year), by pre-paying for a substantial portion of the project’s power, these utilities have nevertheless contributed roughly half of the capital required to build the project. This, plus the fact that the

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

95

financing structure is specifically designed to result in long-term POU ownership (through the buyout option), favors the categorization of this project as POU-owned. 20 Power marketers are defined here to include not only traditional marketers such as PPM Energy, but also the wholesale power marketing affiliates of large investor-owned utilities (e.g., PPL Energy Plus or FirstEnergy Solutions), which may buy wind power on behalf of their load-serving affiliates. 21 Hedge providers active in the market in 2007 include Fortis, Credit Suisse, Barclay’s, J. Aron & Company, and Coral Energy Holding (a division of Shell). These hedges are often structured as a “fixed-for-floating” power price swap—a purely financial arrangement whereby the wind project swaps the “floating” revenue stream that it earns from spot power sales for a “fixed” revenue stream based on an agreed-upon strike price. For at least one project in Texas (where natural gas is virtually always the marginal supply unit), the hedge has been structured in the natural gas market rather than the power market, in order to take advantage of the greater liquidity and longer terms available in the forward gas market. 22 These prices will typically include interconnection costs and, in some cases, transmission expansion costs that are needed to ensure delivery of the energy to the purchaser. 23 For most of the wind power sales prices reported here, the wind generator is selling electricity and RECs in a bundled fashion, and the price reported here therefore reflects the delivery of that bundled product. For at least 10 of the 128 projects in the sample, however, the wind project appears to receive additional revenue (beyond the power price reported) from the separate sale of RECs. The prices provided in this report do not include this separate REC revenue stream, and therefore understate total sales revenue for these projects. Because a minority of projects (10 out of 128) fall in this category, however, this factor is unlikely to significantly bias the overall results presented in this report. 24 All wind power pricing data presented in this report exclude the few projects located in Hawaii. Such projects are considered outliers in that they are significantly more expensive to build than projects in the continental United States, and receive a power sales price that is significantly higher than normal, in part because it is linked to the price of oil. For example, the three major wind projects located in Hawaii (totaling 62 MW) earned revenue in 2007 that ranged from $112/MWh to $177/MWh on average, which is considerably higher than the price received by most wind projects built on the mainland. 25 Prices from two individual projects built during the 2000-2001 period are not shown in Figure 14 (due to the scale of the y-axis), but are included in the capacity-weighted average for that period. The omitted prices are roughly $91/MWh and $150/MWh. 26 Although it may seem counterintuitive, the weighted-average price in 1999 for projects built in 1998 and 1999 (shown in Figure 13 to be about $63/MWh) is significantly higher than the weighted-average price in 2007 for projects built in 1998 and 1999 (shown in Figure 14 to be $39/MWh) for three reasons: (1) the sample size is larger in Figure 14, due to the fact that 2007 prices are presented, rather than 1999 prices as in Figure 13 (i.e., we were unable to obtain early-year pricing for some of the projects built in 1998-1999); (2) two of the larger projects built in 1998 and 1999 (for which both 1999 and 2007 prices are available, meaning that these projects are represented within both figures) have nominal PPA prices that actually decline, rather than remaining flat or escalating, over

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

96

.

U.S. Department of Energy

time; and (3) inflating all prices to constant 2007 dollar terms impacts older (i.e., 1999) prices more than it does more recent (i.e., 2007) prices. 27 If the federal PTC was not available, wind power prices for 2007 projects would range from approximately $50/MWh to $85/MWh, with an average of roughly $65/MWh. 28 It is also possible that regions with higher wholesale power prices will, in general, yield higher wind contract prices due to arbitrage opportunities on the wholesale market. 29 It may be surprising to some that relatively little pricing data are available for Texas, despite the enormous growth in wind capacity in that state. The reason is simple: because ERCOT is not electrically connected to the remainder of the U.S. grid, generators located within ERCOT are not required to file pricing information with FERC. The pricing information for Texas provided in this report comes primarily from projects located in the Texas panhandle, which is covered by the Southwest Power Pool rather than ERCOT. 30 Though wind projects do not provide a perfectly flat block of power, as a common point of comparison, a flat block is not an unreasonable starting point. In other words, the timevariability of wind generation is often such that its wholesale market value is not too dissimilar from that of a flat block of (non-firm) power. 31 The five pricing nodes represented in Figure 16 by an open rather than closed bullet do not have complete pricing history back through 2003. 32 Although their prices are factored into the capacity-weighted-average wind power price (depicted by the red dash), two individual projects are not shown in Figure 18, due to scale limitations: one in the Great Lakes region, at roughly $91/MWh; and one in the East, at roughly $150/MWh. 33 Operations and maintenance (O&M) costs are another important variable that affects wind power prices. A later section of this report covers trends in project-level O&M costs. 34 In both Figures 20 and 21, two project outliers (the same two described earlier) are obscured by the compressed scales, yet still influence the trend lines. 35 Limited sample size early on – particularly in the 1980s – makes it difficult to pin down this number with a high degree of confidence. 36 This may simply be an artifact of the limited quantity and quality of available data, and the influence of other confounding factors. Alternatively, it may be that economies of scale are evident in turbine transactions (larger turbine orders yielding lower prices), but those economies do not necessarily correspond with project size because a large turbine order could be used for either one large project or allocated among multiple smaller projects. 37 Graphical presentation of the data in this way should be viewed with some caution, as numerous factors influence project costs (e.g., whether projects are repowered vs. “greenfield” development, etc.). As a result, actual cost differences among some regions may be more (or less) significant than they appear in Figure 24. 38 See: www.edisonfoundation.net/Rising_Utility_Construction_Costs.pdf 39 Though some performance data for wind projects installed in 2007 are available, those data do not span an entire year of operations. As such, for the purpose of this section, the focus is on project-level 2007 capacity factors for projects with commercial online dates in 2006 and earlier. 40 Focusing just on 2007 means that the absolute capacity factors shown in Figure 26 may not be representative if 2007 was not a representative year in terms of the strength of the wind resource. Note also that by including only 2007 capacity factors, variations in the

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends

97

quality of the wind resource year in 2007 across regions could skew the regional results presented in Figure 27 and Table 7. 41 The capacity-weighted-average 2007 capacity factor for projects installed in 2006 (33.4%) is down slightly from that for projects installed in 2004-2005 (34.8%), in large part due to the impact of a single large project. Specifically, a very large 2006 project in Texas achieved a capacity factor of just 28.7% in 2007; if this single project were excluded from the sample, the capacity-weighted-average 2007 capacity factor from projects built in 2006 would rise to 35.7% (up from 34.8% for projects built in 2004-2005). The impact of this single project is also evident in Figure 27 (where the capacity-weighted-average for Texas is at the low end of the individual project range) and Table 7 (where the steady upward march of average capacity factors in Texas is abruptly reversed in 2006). 42 Although not presented here, expressing O&M costs in units of $/kW-yr was found to yield qualitatively similar results. 43 Projects installed in 2007 are not shown because only data from the first full year of project operations (and afterwards) are used, which in the case of projects installed in 2007 would be year 2008 (for which data are not yet available). 44 Many of the projects installed more recently may still be within their turbine manufacturer warranty period, in which case the O&M costs reported here may or may not include the costs of the turbine warranty, depending on whether the warranty is paid up-front as part of the turbine purchase, or is paid over time. 45 Some of the studies included in the table also address capacity valuation for resource adequacy purposes; those results are not presented here. Two major integration studies for California were also completed in 2007: one conducted by the California ISO and another by the California Energy Commission’s Intermittency Analysis Project. Neither of these studies sought to comprehensively calculate integration costs, however, so neither is listed in the table. 46 Wind penetration on a capacity basis (defined as nameplate wind capacity serving a region divided by that region’s peak electricity demand) is frequently used in integration studies. For a given amount of wind capacity, penetration on a capacity basis is typically higher than the comparable wind penetration in energy terms. 47 The relatively low cost estimate in the 2006 Minnesota study, despite an aggressive level of wind penetration, is partly a result of relying on the overall Midwest Independent System Operator (MISO) market to accommodate certain elements of integrating wind into system operations. The low costs found in the 2006 California study arise because of the large electrical market in which wind power is integrated, as well as the relatively low penetration level analyzed. Conversely, the higher integration costs found by Avista and Idaho Power are, in part, caused by the relatively smaller markets in which the wind is being absorbed and, in part, by those utilities’ operating practices (specifically, that subhourly markets are not used, as is common in ISOs and RTOs). Note also that the rigor with which the various studies have been conducted has varied, as has the degree of peer review. 48 Even outside of ISOs and RTOs, there is increasing interest in collaborative system control actions among balancing areas to address market operations inefficiencies, including helping to mitigate the impact of wind variability on systems operation and cost. In the West, for example, the Area Control Error (ACE) Diversity Interchange project has

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

98

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

sought to pilot the pooling of individual ACEs to take advantage of control error diversity. 49 Note that the two NREL studies are not expected to be complete until 2009. 50 In 2008, Xcel Energy reached a settlement with interveners to submit CPCN applications for new transmission facilities in all four ERZ areas by March 2009. 51 These include Colorado, Idaho, Kansas, North Dakota, New Mexico, South Dakota, and Wyoming. 52 Such entities have also been eligible to receive the Renewable Energy Production Incentive (REPI), which offers a 10-year cash payment equal in face value to the PTC, but the need for annual appropriations and insufficient funding have limited the effectiveness of the REPI.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

In: Wind Power: Technology, Economics and Policies ISBN 978-1-60692-323-8 Editor: Cedrick N. Osphey, pp. 99-334 © 2009 Nova Science Publishers, Inc.

Chapter 3

20% WIND ENERGY BY 2030. INCREASING WIND ENERGY'S CONTRIBUTION * TO U.S. ELECTRICITY SUPPLY U.S. Department of Energy ABBREVIATIONS AND ACRONYMS

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

ACE AEO AEP AGATE AGC ALA AMA API APPA ATTU AWEA AWST BACI Berkeley Lab BLM BPA BSH BTM Btu BWEC *

area control error Annual Energy Outlook American Electric Power Advanced General Aviation Transport Experiments automatic generation control American Lung Association American Medical Association American Petroleum Institute American Public Power Association Annual Turbine Technology Update American Wind Energy Association AWS Truewind before-and-after-control impact Lawrence Berkeley National Laboratory Bureau of Land Management Bonneville Power Administration Bundesamt für Seeschiffahrt und Hydrographie BTM Consult ApS British thermal unit Bat and Wind Energy Cooperative

This is an edited, excerpted and augmented edition of an Energy Efficiency and Renewable Energy publication, dated May 2008.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

100

U.S. Department of Energy CAA CAIR CAISO CAMR CapX 2020 CBO CDEAC CEC CEQA CESA CF CFRP CNV CO2 Coal-IGCC Coal-new COD COE CREZ CT dB DEA DEIS DOD DOE DOI DWT ECAR EEI EERE EFTA EIA EIR EIS ELCC EPA EPAct EPC EPRI ERCOT ERO EU EUI EWEA FAA FACTS

Clean Air Act Clean Air Interstate Rule California Independent System Operator Clean Air Mercury Rule Capacity Expansion Plan for 2020 Congressional Budget Office Clean and Diversified Energy Advisory Committee California Energy Commission California Environmental Quality Act Clean Energy States Alliance capacity factor carbon filament-reinforced plastic California/Nevada carbon dioxide integrated gasification combined cycle coal plants new pulverized coal plants commercial operation date cost of energy Competitive Renewable Energy Zones combustion turbine decibels Danish Energy Authority draft environmental impact statement U.S. Department of Defense U.S. Department of Energy U.S. Department of Interior distributed wind technology East Central Area Reliability Coordinating Agreement Edison Electric Institute Office of Energy Efficiency and Renewable Energy European Free Trade Agreement Energy Information Administration environmental impact review environmental impact statement effective load-carrying capability U.S. Environmental Protection Agency Energy Policy Act engineering, procurement, and construction Electric Power Research Institute Electric Reliability Council of Texas Electric Reliability Organization European Union Energy Unlimited Inc. European Wind Energy Association Federal Aviation Administration flexible AC transmission system

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

20% Wind Energy by 2030 FEIR FERC FL FRCC FTE GaAs Gas-CC Gas-CT GE GHG GIS GRP GS3C GVW GW GWh Hg HSIL HVDC Hz IEA IEC IEEE IGCC IOU IPCC IRP ISET ISO ISO-NE ITC JEDI kg km2 kV kW kWh lb LC LDC LIDAR LLC LNG LOLP m

final environmental impact report Federal Energy Regulatory Commission Florida Florida Reliability Coordinating Council full-time equivalent gallium arsenide combined cycle natural gas plants gas combustion turbine General Electric International greenhouse gas geographic information system glass fiber-reinforced-plastic Grassland/Shrub-Steppe Species Collaborative gross vehicle weight gigawatt gigawatt-hour mercury high-surge impedance-loading (transmission line) high-voltage direct current hertz International Energy Agency International Electrotechnical Commission Institute of Electrical and Electronics Engineers integrated gasification combined cycle investor-owned utility Intergovernmental Panel on Climate Change integrated resource planning Institute for Solar Energy Technology (Institut Energieversorgungstechnik) independent system operator ISO New England investment tax credit Jobs and Economic Development Impact (model) kilogram square kilometers kilovolt kilowatt kilowatt-hour pound levelized cost load duration curve light detection and ranging Limited Liability Company liquefied natural gas loss of load probability meter

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

101

für

Solare

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

102

U.S. Department of Energy m2 MAAC MACRS MAIN MAPP Midwest ISO MMBtu MMS MMTCE MNDOC MOU MRO MTEP MVA MW MWh MW-mile NAICS NAS NCAR NCEP NE NEMS NEPA NERC NESCAUM NGOs nm NOAA NOI NOx NPCC NPV NRC NRECA NREL NSTC NWCC NWF NWS NY NYISO NYSERDA O3 O&M OE

square meter Mid-Atlantic Area Council Modified Accelerated Cost Recovery System Mid-American Interconnected Network Mid-Continent Area Power Pool Midwest Independent System Operator million British thermal units Minerals Management Service million metric tons of carbon equivalent Minnesota Department of Commerce Memorandum of Understanding Midwest Reliability Organization MISO Transmission Expansion Plan megavolt amperes megawatt megawatt-hour megawatt-mile North American Industrial Classification System National Academy of Sciences National Center for Atmospheric Research National Commission on Energy Policy New England National Energy Modeling System National Environmental Policy Act North American Electric Reliability Corporation Northeast States for Coordinated Air Use Management nongovernmental organizations nautical mile National Oceanic and Atmospheric Administration notice of intent nitrogen oxides Northeast Power Coordinating Council net present value National Research Council National Rural Electric Cooperative Association National Renewable Energy Laboratory National Science and Technology Council National Wind Coordinating Collaborative National Wildlife Federation National Weather Service New York New York Independent System Operator New York State Energy Research and Development Authority ozone operations and maintenance Office of Electricity Delivery and Energy Reliability

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

20% Wind Energy by 2030 OCS OMB PBF PGE PJM PMA PNM POI PPA PSE PTC PUC PURPA QF R&D RMA RD&D REC REPI REPP RFC RGGI RMATS RPS RTO s Sandia SCADA SEAC SEPA SERC SF6 SiC SO2 SODAR SOx SPP ST Std. Dev. SWPA TRE TVA TWh UCTE UKERC

103

Outer Continental Shelf Office of Management and Budget Public Benefits Fund Portland General Electric Pennsylvania-New Jersey-Maryland Interconnection Power Marketing Administration Public Service Company of New Mexico point of interconnection power purchase agreement Puget Sound Energy production tax credit Public Utility Commission Public Utility Regulatory Policies Act qualifying or qualified facility research and development Rocky Mountain Area research, development & demonstration renewable energy credit Renewable Energy Production Incentive Renewable Energy Policy Project ReliabilityFirst Corporation Regional Greenhouse Gas Initiative Rocky Mountain Area Transmission Study Renewable Portfolio Standards Regional Transmission Organization second Sandia National Laboratories supervisory control and data acquisition Strategic Energy Analysis Center Southeastern Power Administration Southeastern Electric Reliability Council sulfur hexafluoride (one of six greenhouse gases identified in the Kyoto Protocol) silicon carbide sulfur dioxide sonic detection and ranging sulfur oxides Southwest Power Pool steam turbine standard deviation Southwestern Power Administration Texas Regional Entity Tennessee Valley Authority terawatt-hours Union for the Co-ordination of Transmission of Electricity UK Energy Research Centre

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

104

U.S. Department of Energy USACE US CAP USDA USFS USFWS USGS UWIG V VAR W WEST Western WCI WECC WGA Wh WinDS WindPACT WPA WRA WRCAI WWG

U.S. Army Corps of Engineers U.S. Climate Action Partnership U.S. Department of Agriculture U.S. Department of Agriculture Forest Service U.S. Fish & Wildlife Service U.S. Geological Survey Utility Wind Integration Group volt volt-ampere-reactive watt Western EcoSystems Technology Western Area Power Administration (formerly WAPA) Western Climate Initiative Western Electricity Coordinating Council Western Governors’ Association watt-hour Wind Energy Deployment System Model Wind Partnerships for Advanced Component Technology Wind Powering America Western Resource Advocates Western Regional Climate Action Initiative Wildlife Workgroup

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

SECTION 1. EXECUTIVE SUMMARY AND OVERVIEW 1.1. Introduction and Collaborative Approach Energy prices, supply uncertainties, and environmental concerns are driving the United States to rethink its energy mix and develop diverse sources of clean, renewable energy. The nation is working toward generating more energy from domestic resources—energy that can be cost-effective, and replaced or “renewed” without contributing to climate change or major adverse environmental impacts. In 2006, President Bush emphasized the nation’s need for greater energy efficiency and a more diversified energy portfolio. This led to a collaborative effort to explore a modeled energy scenario in which wind provides 20% of U.S. electricity by 2030. Members of this 20% wind collaborative (see 20% Wind Scenario sidebar) produced this report to start the discussion about issues, costs, and potential outcomes associated with the 20% Wind Scenario. A 20% Wind Scenario in 2030, while ambitious could be feasible if the significant challenges identified in this report are overcome. This report was prepared by DOE in a joint effort with industry, government, and the Nation’s national laboratories (primarily the National Renewable Energy Laboratory and Lawrence Berkeley National Laboratory). The report considers some associated challenges, estimates the impacts and considers specific needs and outcomes in the areas of technology, manufacturing and employment, transmission and grid integration,

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

105

markets, siting strategies, and potential environmental effects associated with a 20% Wind Scenario.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

20% Wind Scenario: Wind Energy Provides 20% of U.S. Electricity Needs by 2030 Key Issues to Examine: • Does the nation have sufficient wind energy resources? • What are the wind technology requirements? • Does sufficient manufacturing capability exist? • What are some of the key impacts? • Can the electric network accommodate 20% wind? • What are the environmental impacts and benefits? • Is the scenario feasible? Assessment Participants: • U.S. Department of Energy (DOE) − Office of Energy Efficiency and Renewable Energy (EERE), Office of Electricity Delivery and Energy Reliability (OE), and Power Marketing − Administrations (PMAs) − National Renewable Energy Laboratory (NREL) − Lawrence Berkeley National Laboratory (Berkeley Lab) − Sandia National Laboratories (SNL) • Black & Veatch engineering and consulting firm • American Wind Energy Association (AWEA) − Leading wind manufacturers and suppliers − Developers and electric utilities − Others in the wind industry In its Annual Energy Outlook 2007, the U.S. Energy Information Agency estimates that U.S. electricity demand will grow by 39% from 2005 to 2030, reaching 5.8 billion megawatthours (MWh) by 2030. To meet 20% of that demand, U.S. wind power capacity would have to reach more than 300 gigawatts (GW) or more than 300,000 megawatts (MW). This growth represents an increase of more than 290 GW within 23 years.1 The data analysis and model runs for this report were concluded in mid-2007. All data and information in the report are based wind data available through the end of 2006. At the time this report was written (2007), the U.S. wind power fleet numbered 11.6 GW and spanned 34 states.2 American wind farms are expected to generate an estimated 48 billion kilowatt-hours of wind energy in 2008, more than 1% of U.S. electricity supply. This capacity addition of 5,244 MW in 2007 exceeds the more conservative growth trajectory developed for the 20% Wind Scenario of about 4,000 MW/year in 2007 and 2008. The wind industry is on track to grow to a size capable of installing 16,000 MW/year, consistent with the latter years in the 20% Wind Scenario, more quickly than the trajectory used for this analysis.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

106

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

1.1.1. Scope This report examines some of the costs, challenges, and key impacts of generating 20% of the nation’s electricity from wind energy in 2030. Specifically, it investigates requirements and outcomes in the areas of technology, manufacturing, transmission and integration, markets, environment and siting. The modeling done for this report estimates that wind power installations with capacities of more than 300 gigawatts (GW) would be needed for the 20% wind in 2030 scenario. Increasing U.S. wind power to this level from today’s 11.6 GW level would require significant changes in transmission, manufacturing and markets. This report presents an analysis of one specific scenario for reaching the 20% level and contrasts it to a scenario of no wind growth beyond the level in 2006. Major assumptions in the analysis have been highlighted throughout the document and have been summarized in the appendices. These assumptions may be considered optimistic. In this report, no sensitivity analyses have been done to estimate the impact that changes in the assumptions would have on the information presented here. As summarized at the end of this section, the analysis provides an overview of some potential impacts of these two scenarios by 2030. This report does not compare the Wind Scenario to other energy portfolio options, nor does it outline an action plan. To successfully address energy security and environmental issues, the nation needs to pursue a portfolio of energy options. None of these options by itself can fully address these issues; there is no “silver bullet.” This technical report examines one potential scenario in which wind power serves as a significant element in the portfolio. However, the 20% Wind Scenario is not a prediction of the future. Instead, it paints a picture of what a particular 20% Wind Scenario could mean for the nation. 1.1.2. Contributors Report contributors include a broad cross section of key stakeholders, including leaders from the nation’s utility sector, environmental communities, wildlife advocacy groups, energy industries, the government and policy sectors, investors, and public and private businesses. In all, the report reflects input from more than 50 key energy stakeholder organizations and corporations. Appendix D contains a list of contributors. Research and modeling was conducted by experts within the electric industry, government, and other organizations. This report is not an authoritative expression of policy perspectives or opinions held by representatives of DOE. 1.1.3. Assumptions and Process To establish the groundwork for this report, the engineering company Black & Veatch (Overland Park, Kansas) analyzed the market potential for significant wind energy growth, quantified the potential U.S. wind supply, and developed cost supply curves for the wind resource. In consultation with DOE, NREL, AWEA, and wind industry partners, future wind energy cost and performance projections were developed. Similar projections for conventional generation technologies were developed based on Black & Veatch experience with power plant design and construction (Black and Veatch, forthcoming 2008). To identify a range of challenges, possible solutions, and key impacts of providing 20% of the nation’s electricity from wind, the stakeholders in the 20% Wind Scenario effort convened seven expert task forces to examine specific areas critical to this endeavor:

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

107

Technology and Applications, Manufacturing and Materials, Environmental and Siting Impacts, Electricity Markets, Transmission and Integration, and Supporting Analysis. These teams conducted in-depth analyses of potential impacts, using related studies and various analytic tools to examine the benefits and costs. (See Appendix D for the task force participants.)

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wind Energy Deployment System Model Assumptions (See Appendices A and B) • Assumes that the contributions to U.S. electricity supplies from other renewable sources of energy would remain at 2006 levels in both scenarios. • Assumes capital costs would be reduced by 10% over the next two decades and capacity factors would be increased by about 15% (corresponding to a 15% increase in annual energy generation by a wind plant) • Assumes future environmental study and permit requirements are not expected to add significant costs to wind technology. • The assumptions used for the WinDS model were obtained from a number of sources, including technical experts (see Appendix D), the WinDS base case (Denholm and Short 2006), AEO 2007 (EIA 2007), and a study performed by Black & Veatch (2007). These assumptions include projections of future costs and performance for all generation • technologies, transmission system expansion costs, wind resources as a function of geographic location within the continental United States, and projected growth rates for wind generation. • Assumes cost of new transmission is generally split between the originating project, be it wind or conventional generation, and the ratepayers within the region. • Assumes that 10% of existing grid capacity is available for wind energy. • Current long-term power purchase agreements are not implemented in WinDS. The model assumes that local load is met by the generation technologies in a given region. • Wind energy generation prescribed annually at national level to reach 20% wind energy by 2030 − A stable policy environment that supports accelerated wind deployment − Balance of generation economically optimized with no policy changes from those in place today (e.g., no production tax credit [PTC] beyond 12/31/08) − Technology cost and performance assumptions as well as electric grid expansion and operation assumptions that affect the direct electric system cost. • Land-based and offshore wind energy technology cost reductions and performance improvements expected by 2030 (see tables A.1, B.10, and B.11) • Fossil fuel technology costs and performance generally flat between 2005 and 2030 (see tables A.1 and B.13) • Nuclear technology cost reductions expected by 2030 (see tables A.1 and B.13) • Reserve and capacity margins calculated at the North American Electric Reliability Corporation (NERC) region level, and new transmission capacity added as needed (see sections A.2.2 and B.3) • Wind resource as a function of geographic location from various sources (see Table B.8) • Projected electricity demand, financing assumptions, and fuel prices based on Annual Energy Outlook (EIA 2007; see sections B. 1, B.2, and B.4.2).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

108

U.S. Department of Energy

NREL’s Wind Deployment System (WinDS) model3 was employed to create a scenario that paints a “picture” of this level of wind energy generation and evaluates some impacts associated with wind. Assumptions about the future of the U.S. electric generation and transmission sector were developed in consultation with the task forces and other parties. Some assumptions in this analysis could be considered optimistic. Examples of assumptions used in this analysis are listed in the text box and are presented in detail in Appendix A and B. For comparison, the modeling team contrasted the 20% Wind Scenario impacts to a reference case characterized by no growth in U.S. wind capacity or other renewable energy sources after 2006. In the course of the examination, two workshops were held to define and refine the work plan, present and discuss preliminary results, and obtain relevant input from key stakeholders external to the report preparation effort.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

1.1.4. Report Structure A 20% wind energy scenario in 2030 would require improved turbine technology to generate wind power, significant changes in transmission systems to deliver it through the electric grid, and large expanded markets to purchase and use it. In turn, these essential changes in the power generation and delivery process would involve supporting changes and capabilities in manufacturing, policy development, and environmental regulation. As shown in Figure 1.1, the sections of this report address some of the requirements and impacts in each of these areas. Detailed discussions of the modeling process, assumptions, and results can be found in appendices A through C. 1.1.5. Setting the Context: Today’s U.S. Wind Industry After experiencing strong growth in the mid-1980s, the U.S. wind industry hit a plateau during the electricity restructuring period in the 1990s, then regained momentum in 1999. Industry growth has since responded positively to policy incentives when they are in effect (see Figure 1.2). Today, the U.S. wind industry is growing rapidly, driven by sustained production tax credits (PTCs), rising concerns about climate change, and renewable portfolio standards (RPS) or goals in roughly 50% of the states. U.S. turbine technology has advanced steadily to offer improved performance. In 2006 alone, average turbine size increased by more than 11% over the 2005 level to an average size of 1.6 MW. In addition, average capacity factors have improved 11% over the past two years. To meet the growing demand for wind energy, U.S. manufacturers have expanded their capacity to produce and assemble the essential components. Despite this growth, U.S. components continue to represent a relatively small share of total turbine and tower materials, and U.S. manufacturers are struggling to keep pace with rising demand (Wiser & Bolinger, 2007).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 1.1. Report sections.

Figure 1.2. Cumulative U.S. wind capacity, by year (in megawatts [MW]).

Figure 1.3. Required growth in U.S. capacity (GW) to implement the 20% Wind Scenario.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

109

110

U.S. Department of Energy Initiatives to Improve Wind Turbine Performance

Avoid problems before installation • Improve reliability of turbines and components • Full-scale testing prior to commercial introduction • Development of appropriate design criteria, specifications and standards • Validation of design tools Monitor Performance • Monitor and evaluate turbine and wind-plant performance • Performance tracking by independent parties • Early identification of problems Rapid Deployment of Problem Resolution • Develop and communicate problem solutions • Focused activities with stakeholders to address critical issues, e.g., Gearbox Reliability Collaborative

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

A Brief History of the U.S. Wind Industry The U.S. wind industry got its start in California during the 1970s, when the oil shortage increased the price of electricity generated from oil. The California wind industry benefited from federal and state investment tax credits (ITCs) as well as state-mandated standard utility contracts that guaranteed a satisfactory market price for wind power. By 1986, California had installed more than 1.2 GW of wind power, representing nearly 90% of global installations at that time. Expiration of the federal ITC in 1985 and the California incentive in 1986 brought the growth of the U.S. wind energy industry to an abrupt halt in the mid-1980s. Europe took the lead in wind energy, propelled by aggressive renewable energy policies enacted between 1974 and 1985. As the global industry continued to grow into the 1990s, technological advances led to significant increases in turbine power and productivity. Turbines installed in 1998 had an average capacity 7 to 10 times greater than that of the 1 980s turbines, and the price of windgenerated electricity dropped by nearly 80% (AWEA 2007). By 2000, Europe had more than 12,000 MW of installed wind power, versus only 2,500 MW in the United States, and Germany became the new international leader. Energy Policy Act of 1992 The PTC gave power producers 1.5 cents (increased annually with inflation) for every kilowatt-hour (kWh) of electricity produced from wind during the first 10 years of operation. With low natural gas prices and U.S. utilities preoccupied by industry restructuring during the 1990s, the federal PTC enacted in 1992 (as part of the Energy Policy Act [EPAct]) did little to foster new wind installations until just before its expiration in June 1999. Nearly 700 MW of new wind generation were installed in the last year before the credit expired—more than in any previous 12-month period since 1985. After the PTC expired in 1999, it was extended for two brief periods, ending in 2003. It was then reinstated in late 2004. Although this intermittent policy support led to sporadic growth, business inefficiencies inherent in serving this choppy market inhibited investment

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

111

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

and restrained market growth. To promote renewable energy systems, many states began requiring electricity suppliers to obtain a small percentage of their supply from renewable energy sources, with percentages typically increasing over time. With Iowa and Texas leading the way, more than 20 states have followed suit with RPS, creating an environment for stable growth. After a decade of trailing Germany and Spain, the United States reestablished itself as the world leader in new wind energy in 2005. This resurgence is attributed to increasingly supportive policies, growing interest in renewable energy, and continued improvements in wind technology and performance. The United States retained its leadership of wind development in 2006 and, because of its very large wind resources, is likely to remain a major force in the highly competitive wind markets of the future.

In 2005 and 2006, the United States led the world in new wind installations. By early 2007, global wind power capacity exceeded 74 GW, and U.S. wind power capacity totaled 11.5 GW. This domestic wind power has been installed across 35 states and delivers roughly 0.8% of the electricity consumed in the nation (Wiser and Bolinger, 2007). The 20% Wind Scenario presented here would require U.S. wind power capacity to grow from the current 11.5 GW to more than 300 GW over the next 23 years (see Figure 1.3). This ambitious growth could be achieved in many different ways, with varying challenges, impacts, and levels of success. The 20% Wind Scenario would require an installation rate of 16 GW per year after 2018 (See Figure 1.4). This report examines one particular scenario for achieving this dramatic growth and contrasts it to another scenario that—for analytic simplicity—assumes no wind growth after 2006. The authors recognize that U.S. wind capacity is currently growing rapidly (although from a very small base), and that wind energy technology will be a part of any future electricity generation scenario for the United States. At the same time, a great deal of uncertainty remains about the level of contribution that wind could or is likely to make. In the 2007 Annual Energy Outlook (EIA 2007), an additional 7 GW beyond the 2006 installed capacity of 11.6 GW is forecast by 2030.4 Other organizations are projecting higher capacity additions, and it would be difficult to develop a “most likely” forecast given today’s uncertainties. The analysis presented here sidesteps these uncertainties and contrasts some of the challenges and impacts of producing 20% of the nation’s electricity from wind with a scenario in which no additional wind is added after 2006. This results in an estimate, expressed in terms of parameters, of the impacts and benefits associated with increased reliance on wind energy generation under given assumptions. The analysis was also simplified by assuming that the contributions to U.S. electricity supplies from other renewable sources of energy would remain at 2006 levels in both scenarios (see Figure A.6 for resource mix). The 20% Wind Scenario has been carefully defined to provide a base of common assumptions for detailed analysis of all impact areas. Broadly stated, this 20% scenario is designed to consider incremental costs while recognizing realistic constraints and considerations (see the Considerations in the 20% Scenario sidebar in Appendix A). Specifically, the scenario describes the mix of wind resources that would need to be captured, the geographic distribution of wind power installations, estimated land needs, the required utility and transmission infrastructure, manufacturing requirements, and the pace of growth that would be necessary.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

112

U.S. Department of Energy

1.2.1. Wind Geography The United States possesses abundant wind resources. As shown in Figure 1.5, current “bus-bar” energy costs for wind (based on costs of the wind plant only, excluding transmission and integration costs and the PTC) vary by type of location (land-based or offshore) density (higher classes offer greater productivity). Transmission and integration will add additional costs which are discussed in Chapter 4. The nation has more than 8,000 GW of available land-based wind resources (Black and Veatch, forthcoming 2008) that industry estimates can be captured economically. NREL periodically classifies wind resources by wind speed which forms the basis of the Black and Veatch study. See Appendix B for further details. Electricity must, however, be transmitted from where it is generated to areas of high electricity demand, using the existing transmission system or new transmission lines where necessary. As shown in Figure 1.6 on the next page, the delivered cost of wind power increases when costs associated with connecting to the existing electric grid are included. The assumptions used in this report are different than EIA’s assumptions and are documented in Appendix A &B. The cost and performance assumptions of the 20% Wind Scenario are based on real market data from 2007. Cost and performance for all technologies either decrease or remain flat over time. The models suggest that as much as 600 GW of wind resources could be available for $60 to $100 per megawatt-hour (MWh), including the cost of connecting to the existing transmission system. Including the PTC reduces the cost by about $20/MWh, and costs are further reduced if technology improvements in cost and performance are projected. In some cases, new transmission lines connecting high- wind resource areas to load centers could be costeffective, and in other cases, high transmission costs could offset the advantage of land-based generation, as in the case of large demand centers along wind-rich coastlines. NREL’s WinDS model estimated the overall U.S. generation capacity expansion required to meet projected electricity demand growth through 2030. Both wind technology and conventional generation technology (i.e., coal, nuclear) were included in the modeling but other renewables were not. Readers should refer to Appendices A and B to see a more complete list of the modeling assumptions. Wind energy development for this 20% Wind Scenario optimized the total delivered costs, including future reductions in cost per kilowatthour for wind sites both near to and remote from demand sites from 2000 through 2030.5 Section 2 presents additional discussion of wind technology potential. Of the 293 GW that would be added, the model specifies more than 50 GW of offshore wind energy, mostly along the northeastern and southeastern seaboards. Based on this least-cost optimization algorithm (which incorporates future cost per kilowatt-hour of wind and cost of transmission), the WinDS model further specified the wind capacity needed by state by 2030. As shown in Figure 1.6, most states would have the opportunity to develop their wind resources. Total land requirements are extensive, but only about 2% to 5% of the total would be dedicated entirely to the wind installation. In addition, the visual impacts and other siting concerns of wind energy projects must be taken into account in assessing land requirements. Section 5 contains additional discussion of land use and visual impacts. Again, the 20% Wind Scenario presented here is not a prediction. Figure 1.6 simply shows one way in which a 20% wind future could evolve.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

113

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 1.4. 20% Cumulative installed wind power capacity required to produce 20% of projected electricity by 2030.

See Appendix B for wind technology cost and performance projections; PTC and transmission and integration costs are excluded. Figure 1.5. Supply curve for wind energy—current bus-bar energy costs.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

114

U.S. Department of Energy

Note: See Appendix B for wind technology cost and performance projections. Excludes PTC, includes transmission costs to access existing electric transmission within 500 miles of wind resource.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 1.6. Supply curve for wind energy—energy costs including connection to 10% of existing transmission grid capacity.

1.2.2. Wind Power Transmission and Integration Development of 293 GW of new wind capacity would require expanding the U.S. transmission grid in a manner that not only accesses the best wind resource regions of the country but also relieves current congestion on the grid including new transmission lines to deliver wind power to electricity consumers. Figure 1.7 conceptually illustrates the optimized use of wind resources within the local areas as well as the transmission of wind-generated electricity from high-resource areas to high-demand centers. This data was generated by the WinDS model given prescribed constraints. The figure does not represent proposals for specific transmission lines. Figure 1.8 displays transmission needs in the form of one technically feasible transmission grid as a 765 kV overlay. A complete discussion of transmission issues can be found in Section 4. Until recently, concerns had been prevalent in the electric utility sector about the difficulty and costs of dealing with the variability and uncertainty of energy production from wind plants and other weather-driven renewable technologies. But utility engineers in some parts of the United States now have extensive experience with wind plant impacts, and their analyses of these impacts have helped to reduce these concerns. As discussed in detail in Section 4, wind’s variability is being accommodated, and given optimistic assumptions, studies suggest the cost impact could be as little as the current level - 10% or less of the value of the wind energy generated.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

115

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

1.2.3. Electrical Energy Mix The U.S. Energy Information Administration (EIA) estimates that U.S. electricity demand will grow by 39% from 2005 to 2030, reaching 5.8 billion MWh by 2030. The 20% Wind Scenario would require delivery of nearly 1.16 billion MWh of wind energy in 2030, altering U.S. electricity generation as shown in Figure 1.9. In this scenario, wind would supply enough energy to displace about 50% of natural gas electric utility consumption and 18% of coal consumption by 2030. This amounts to an 11% reduction in natural gas across all industries. (Gas-fired generation would probably be displaced first, because it typically has a higher cost.)

Land Requirements Altogether, new land- based installations would require approximately 50,000 square kilometers (km2) of land, yet the actual footprint of land-based turbines and related infrastructure would require only about 1,000 to 2,500 km2 of dedicated land—slightly less than the area of Rhode Island. The 20% scenario envisions 241 GW of land-based and 54 GW of shallow offshore wind resource to optimize delivered costs, which include both generation and transmission. Wind capacity levels in each state depend on a variety of assumptions and the national optimization of electricity generation expansion. Based on the perspectives of industry experts and near-term wind development plans, wind capacity in Ohio was modified and offshore wind development in Texas was included. In reality, each state’s wind capacity level will vary significantly as electricity markets evolve and state policies promote or restrict the energy production of electricity from wind and other renewable and conventional energy sources. Figure 1.7. 46 States would have substantial wind development by 2030.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

116

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 1.8. All new electrical generation including wind energy would require expansion of U.S. transmission by 2030.

The increased wind development in this scenario could reduce the need for new coal and combined cycle natural gas capacity, but would increase the need for additional combustion turbine natural gas capacity to maintain electric system reliability. These units, though, would be run only as needed.6

1.2.4. Pace of New Wind Installations Manufacturing capacity would require some time to ramp up to support rapid growth in new U.S. wind installations. The 20% Wind Scenario estimates that the installation rate would need to increase from installing 3 GW per year today to more than 16 GW per year by 2018 and continue at roughly that rate through 2030, as seen in Figure 1.10. This increase in installation rate, although quite large, is comparable to the recent annual installation rate of natural gas units, which totaled more than 16 GW in 2005 alone (EIA 2005). The assumptions of the 20% Wind Scenario form the foundation for the technical analyses presented in the remaining sections. This overview is provided as context for the potential impacts and technical challenges discussed in the next sections.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 1.9. Conceptual transmission plan to accommodate 400 GW of wind energy (AEP 2007).

Figure 1.10. U.S. electrical energy mix.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

117

118

U.S. Department of Energy

1.3. Impacts

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The 20% Wind Scenario presented here offers potentially positive impacts in terms of GHG reductions, water conservation, and energy security, as compared to the base case of no wind growth in this analysis. However, tapping this resource at this level would entail large front-end capital investments to install wind capacity and expanded transmission systems. The impacts described in this section are based largely on the analytical tools and methodology discussed in detail in appendices A, B, and C. Wind power would be a critical part of a broad and near-term strategy to substantially reduce air pollution, water pollution, and global climate change associated with traditional generation technologies (see Wind versus Traditional Electricity Generation sidebar). As a domestic energy resource, wind power would also stabilize and diversify national energy supplies.

1.3.1. Greenhouse Gas Reductions Supplying 20% of U.S. electricity from wind could reduce electric sector carbon dioxide (CO2) emissions by 825 million metric tons. The threat of climate change and the growing attention to it are helping to position wind power as an increasingly attractive option for new power generation. U.S. electricity demand is growing rapidly, and cleaner power sources (e.g., renewable energy) and energy-saving practices (i.e., energy efficiency) could help meet much of the new demand while reducing GHG emissions. Today, wind energy represents approximately 30% of new capacity additions (AWEA 2008). Greater use of wind energy, therefore, presents an opportunity for reducing emissions today as the nation develops additional clean power options for tomorrow. Concerns about climate change have spurred many industries, policy makers, environmentalists, and utilities to call for reductions in GHG emissions. Although the cost of reducing emissions is uncertain, the most affordable near-term strategy likely involves wider deployment of currently available efficiency and clean energy technologies. Wind power is one of the potential supply- side solutions to the climate change problem (Socolow and Pacala 2006).

Wind vs. Traditional Electricity Generation Wind power avoids several of the negative effects of traditional electricity generation from fossil fuels: • • • • • •

Emissions of mercury or other heavy metals into the air. Emissions associated with extracting and transporting fuels. Lake and streambed acidification from acid rain or mining. Water consumption associated with mining or electricity generation. Production of toxic solid wastes, ash, or slurry. Greenhouse gas (GHG) emissions.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

119

20% Wind Scenario: Projected Impacts •

• • • •

•

Environment: Avoids air pollution, reduces GHG emissions, and reduces water use in electricity generation. Reduces electric sector CO2 emissions by 825 million metric tons. U.S. energy security: Diversifies our electricity portfolio and represents an indigenous energy source with stable prices not subject to fuel volatility Energy consumers: Wind potentially reduces demand for fossil fuels, in turn reducing fuel prices and stabilizing electricity rates Local economics: Creates new income source for rural landowners and tax revenues for local communities in wind development areas. American workers: Generates well-paying jobs in sectors that support wind development, such as manufacturing, engineering, construction, transportation, and financial services. The new manufacturing will cause significant growth in the wind industry supply chain. Water savings: Reduce cumulative water use in the electric sector by 8% (4 trillion gallons)

20% Wind Scenario: Major Challenges •

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

• •

Investment in the nation’s transmission system so the power generated is delivered to urban centers that need the increased supply; Larger electric load balancing areas, in tandem with better regional planning, so that regions can depend on a diversity of generation sources, including wind power; Continued reduction in wind capital cost and improvement in turbine performance through technology advancement and improved manufacturing capabilities; and Addressing potential concerns about local siting, wildlife, and environmental issues within the context of generating electricity.

GHG Reduction Under the 20% Wind Scenario, a cumulative total of 7,600 million tons of CO2 would be avoided by 2030, and more than 15,000 million tons of CO2 would be avoided through 2050.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

120

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 1.11. Annual and cumulative wind installations by 2030.

Governments at many levels have enacted policies to actively support clean electricity generation, including the renewable energy PTC and state RPS. A growing number of energy and environmental organizations are calling for expanded wind and other renewable power deployment to try to reduce society’s carbon footprint. According to EIA, The United States annually emits approximately 6,000 million metric tons of CO2.7 These emissions are expected to increase to nearly 7,900 million metric tons by 2030, with the electric power sector accounting for approximately 40% of the total (AEO, 2007). As shown in Figure 1.11, based on the analysis completed for this report, generating 20% of U.S. electricity from wind could avoid approximately 825 million metric tons of CO2 in the electric sector in 2030. The 20% scenario would also reduce cumulative emissions from the electric sector through that same year by more than 7,600 million metric tons of CO2 (2,100 million metric tons of carbon equivalent). See Figures 1.12 and 13. In general, CO2 emission reductions are not only a wind energy benefit but could be achieved under other energy mix scenarios. The Fourth Assessment Report of the United Nations Environment Programme and World Meteorological Organization’s Intergovernmental Panel on Climate Change (IPCC) notes that, “Renewable energy generally has a positive effect on energy security, employment, and air quality. Given costs relative to other supply options, renewable electricity can have a 30% to 35% share of the total electricity supply in 2030. Deployment of low-GHG (greenhouse gas) emission technologies... would be required for achieving stabilization and cost reductions” (IPCC 2007). More than 30 U.S. states have created climate action plans. The Regional Greenhouse Gas Initiative (RGGI) is a 10-state collaborative in the Northeast to address CO2 emissions. All of these state and regional efforts include wind energy as part of a portfolio strategy to reduce overall emissions from energy production (RGGI 2006). Wind turbines typically have a service life of at least 20 years and transmission lines can last more than 50 years, meaning that investments in 20% wind by 2030 would continue to

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

121

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

supply clean energy at least through 2050. As a result, cumulative climate change impacts could grow to more than 15,000 million tons of CO2 avoided by mid-century (4,182 million metric tons of carbon equivalent). The 20% Wind Scenario constructed here would displace a significant amount of fossil fuel generation. According to the WinDS model, by 2030, wind generation is projected to displace 50% of electricity generated from natural gas and 18% of that generated from coal. Coal displacement is of particular interest because the carbon emissions reduction opportunity is relatively higher. Recognizing that coal power will continue to play a major role in future electricity generation, a large increase in total wind capacity could potentially defer the need to build some new coal capacity, avoiding or postponing the associated carbon emissions. Current DOE projections anticipate construction of approximately 140 GW of new coal plant capacity by 2030 (EIA 2007); the 20% Wind Scenario could avoid more than 80 GW of new coal capacity.8 Wind energy that displaces fossil fuel generation can also help meet existing regulations for emissions of conventional pollutants, including sulfur dioxide, nitrogen oxides, and mercury.

1.3.2. Water Conservation The 20% scenario would potentially reduce cumulative water consumption in the electric sector by 8% from 2007 through 2030, or 4 trillion gallons—significantly reducing water consumption in the arid states of the interior West. In 2030, annual water consumption in the electric sector would be reduced by 17%. Water scarcity is a significant problem in many parts of the country. Even so, few realize that electricity generation accounts for nearly half of all water withdrawals in the nation, with irrigation coming in second at 34% (USGS 2005). Water is used for cooling of natural gas, coal, and nuclear power plants and is an increasing part of the challenge in developing those resources.

Figure 1.12. Annual CO2 emissions avoided (vertical bars) would reach 825 million tons by 2030.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

122

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 1.13. Avoided emissions would nearly level projected growth in CO2 emissions from the electricity sector.

Although a significant portion of the water withdrawn for electricity production is recycled back through the system, approximately 2% to 3% of the water withdrawn is consumed through evaporative losses. Even this small fraction adds up to approximately 1.6 to 1.7 trillion gallons of water consumed for power generation each year. As additional wind generation displaces fossil fuel generation, each megawatt-hour generated by wind could save as much as 600 gallons of water that would otherwise be lost to fossil plant cooling.9 Because wind energy generation uses a negligible amount of water, the 20% Wind Scenario would avoid the consumption of 4 trillion gallons of water through 2030, with annual reductions shown in Figure 1.14. The annual savings in 2030 is approximately 450 billion gallons. This reduction would reduce the expected annual water consumption for electricity generation in 2030 by 17%. The projected water discussed further in Appendix A. Wind Reduces Vulnerability Continued reliance on natural gas for new power generation is likely to put the United States in growing competition in world markets for liquefied natural gas (LNG)—some of which will come from Russia, Qatar, Iran, and other nations in less-than stable regions.

Based on the WinDS modeling results, nearly 30% of the projected water savings from the 20% Wind Scenario would occur in western states, where water resources are particularly scarce. The Western Governors Association (WGA) highlights this concern in its Clean and Diversified Energy Initiative, which recognizes increased water consumption as a key challenge in accommodating rapid growth in electricity demand. In its 2006 report on water needs, the WGA states that “difficult political choices will be necessary regarding future

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

123

economic and environmental uses of water and the best way to encourage the orderly transition to a new equilibrium” (WGA 2006).

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

1.3.3. Energy Security and Stability There is broad and growing recognition that the nation should diversify its energy portfolio so that a supply disruption affecting a single energy source will not significantly disrupt the national economy. Developing domestic energy sources with known and stable costs would significantly improve U.S. energy stability and security. When electric utilities have a Power Purchase Agreement or own wind energy turbines, the price of energy is expected to remain relatively flat and predictable for the life of the wind project, given that there are no fuel costs and assuming that the machines are well maintained. In contrast, a large part of the cost of coal- and gas- fired electricity is in the fuel, for which prices are often volatile and unpredictable. Fuel price risks reduce security and stability for U.S. manufacturers and consumers, as well as for the economy as a whole. Even small reductions in the amount of energy available or changes in the price of fuel can cause large economic disruptions across the nation. This capacity to disrupt was clearly illustrated by the 1973 embargo imposed by the Organization of Arab Petroleum Exporting Countries (the “Arab oil embargo”); the 2000–2001 California electricity market problems; and the gasoline and natural gas shortages and price spikes that followed the 2005 hurricane damage to oil refinery and natural gas processing facilities along the Gulf Coast. Using wind energy increases security and stability by diversifying the national electricity portfolio. Just as those investing for retirement are advised to diversify investments across companies, sectors, and stocks and bonds, diversification helps distribute the risks and stabilize rates for electricity consumers.

Figure 1.14. National water savings from the 20% Wind Scenario. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

124

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wind energy reduces reliance on foreign energy sources from politically unstable regions. As a domestic energy source, wind requires no imported fuel, and the turbine components can be either produced on U.S. soil or imported from any friendly nation with production capabilities. Energy security concerns for the electric industry will likely increase in the foreseeable future as natural gas continues to be a leading source of new generation supply. With declining domestic natural gas sources, future natural gas supplies are expected to come in the form of LNG imported on tanker ships. U.S. imports of LNG could quadruple by 2030 (EIA 2007). Almost 60% of uncommitted natural gas reserves are in Iran, Qatar, and Russia. These countries, along with others in the Middle East, are expected to be major suppliers to the global LNG market. Actions by those sources can disrupt international energy markets and thus have indirect adverse effects on our economy. Additional risks arise from competition for these resources caused by the growing energy demands of China, India, and other developing nations. Under the 20% scenario, according to the WinDS model results, wind energy could displace approximately 11% of natural gas consumption which is equivalent to 60% of expected LNG imports in 2030.10 This shift would reduce the nation’s energy vulnerability to uncertain natural gas supplies. Please see Appendix A for gas demand reduction assumptions and calculations. Continued reliance on fossil energy sources exposes the nation to price risks and supply uncertainties. Although the electric sector does not rely heavily on petroleum, which represents one of the nation’s biggest energy security threats, diversifying the electric generation mix with increased domestic renewable energy would still enhance national energy security by increasing energy diversity and price stability.

1.3.4. Cost of the 20% Wind Scenario The overall economic cost of the 20% Wind Scenario accrues mainly from the incremental costs of wind energy relative to other generation sources. This is impacted by the assumptions behind the scenario, listed in table A.6. Also, some incremental transmission would be required to connect wind to the electric power system. This transmission investment would be in addition to the significant investment in the electric grid that will be needed to serve continuing load growth, whatever the mix of new generation. The market cost of wind energy remains higher than that of conventional energy sources in many areas across the country. In addition, the transmission grid would have to be expanded and upgraded from wind- rich areas and across the existing system to deliver wind energy to many demand centers. Compared to other generation sources, the 20% Wind Scenario entails higher initial capital costs (to install wind capacity and associated transmission infrastructure) in many areas, yet offers lower ongoing energy costs than conventional power plants for operations, maintenance and fuel. Given the optimistic cost and performance assumptions of wind and conventional energy sources (detailed in Appendix B), the 20% Wind Scenario could require an incremental investment of as little as $43 billion NPV more than the base-case no new Wind Scenario. This would represent less than 0.06 cent (6 one-hundredths of 1 cent) per kilowatt-hour of total generation by 2030, or roughly 50 cents per month per household. Figure 1.18 shows this cost comparison. The base-case costs are calculated under the assumption of no major changes in fuel availability or environmental restrictions. In this

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

125

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

scenario, the cost differential would be about 2% of a total NPV expenditure exceeding $2 trillion. This analysis intended to identify the incremental cost of pursuing the 20% Wind Scenario. In regions where the capital costs of the 20% scenario exceed those of building little or no additional wind capacity, the differential could be offset by the operating cost and benefits discussed earlier. For example, even though Figure 1.18 shows that under optimistic assumptions the 20% Wind Scenario could increase total capital cost by nearly $197 billion, most of that cost would be offset by the nearly $155 billion in decreased fuel expenditure, resulting in a net incremental cost of approximately $43 billion in NPV. These monetary cost do not reflect other potential offsetting positive impacts. An integrated approach to expanding the transmission system would need to include furnishing access to wind resources as well as meeting other system needs. As estimated by the NREL WinDS model, given optimistic assumptions, the specific cost of the proposed transmission expansion for the 20% Wind Scenario is $20 billion in NPV. The actual required grid investment could also involve significant costs for permitting delays, construction of grid extensions to remote areas with wind resources, and investments in advanced grid controls, integration and training to enable regional load balancing of wind resources. The total installed costs for wind plants include costs associated with siting and permitting of these plants. It has become clear that wind power expansion would require careful, logical, and fact-based consideration of local and environmental concerns, allowing siting issues to be addressed within a broad risk framework. Experience in many regions has shown that this can be done, but efficient, streamlined procedures will likely be needed to enable installation rates in the range of 16 GW per year. Section 5 covers these issues in more detail.

Figure 1.15. Incremental investment cost of 20% wind is modest; a difference of 2%.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

126

U.S. Department of Energy

1.4. Conclusion There are significant costs, challenges, and impacts associated with the 20% Wind Scenario presented in this report. There are also substantial positive impacts from wind power expansion on the scale and pace described in this section are not likely to be realized in a business-as-usual future. Achieving this scenario would involve a major national commitment to clean, domestic energy sources with minimal emissions of GHGs and other environmental pollutants.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

1.5. References and other Suggested Reading AWEA 2007. American Wind Energy Association Web site, Oct.1, 2007: http://www. awea.org/faq/cost.html. BTM Consult. 2007. International Wind Energy Development, World Market Update 2006. Ringkøbing, Denmark: BTM. Edmonds, J.A., M.A. Wise, J.J. Dooley, S.H. Kim, S.J. Smith, P.J. Runci, L.E. Clarke, E.L. Malone, and G.M. Stokes. 2007. Global Energy Technology Strategy: Addressing Climate Change. Richland, WA: Global Energy Strategy Technology Project. http:// www.pnl.gov/gtsp/docs/gtsp_2007_final.pdf EIA (Energy Information Administration). 2005. Electric Power Annual. Washington, DC: EIA. Table 2.6. http://www.eia.doe.gov/cneaf/electricity/epa/epat2p6.html. EIA. 2007. Annual Energy Outlook. Washington, DC: EIA. http://www.eia.doe.gov/oiaf/ aeo/index.html. IPCC (Intergovernmental Panel on Climate Change). 2007. Climate Change 2007: Impacts, Adaptation and Vulnerability: Working Group II Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate change. PCC Report presented at 8th session of Working Group II of the IPCC, April 2007, Brussels, Belgium. http://www.ipcc.ch/ipccreports/ar4 wg2.htm Johnston, L., E. Hausman, A. Sommer, B. Biewald, T. Woolf, D. Schlissel, A. Roschelle, and D. White. 2006. Climate Change and Power: Carbon Dioxide Emissions Costs and Electricity Resource Planning. Cambridge, MA: Synapse Energy Economics, Inc. O'Connell, R., R. Pletka, et al. 2007. 20% Wind Energy Penetration in the United States: A Technical Analysis of the Energy Resource. Overland Park, KS: Black & Veatch. RGGI (Regional Greenhouse Gas Initiative). 2006. “About RGGI.” http://www.rggi.org/ about.htm. Socolow, R.H., and S.W. Pacala. 2006. “A Plan to Keep Carbon in Check,” Scientific American, September. Teske, S., A. Zervos, and O. Schafer. 2007. Energy [R]evolution: A Blueprint for Solving Global Warming, USA National Energy Scenario. Amsterdam: Greenpeace International. http://www.greenpeace.org/raw/content/usa/press center/reports4/ energy-r-evolution-introduc.pdf USCAP (U.S. Climate Action Partnership). 2007. A Call for Action. http://www.us cap.org/USCAPCallForAction.pdf USGS (U.S. Geological Survey). 2005. Estimated Use of Water in the United States in 2000. http://pubs.usgs.gov/circ/2004/circ1268/htdocs/figure01.html

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

127

WGA (Western Governors’ Association). 2006. Water Needs and Strategies for a Sustainable Future, p. 4. http://www.westgov.org/wga/publicat/Water06.pdf Wiser, R., M. Bolinger, and M. St. Clair. 2005. Easing the Natural Gas Crisis: Reducing Natural Gas Prices through Increased Deployment of Renewable Energy and Energy Efficiency. Berkeley, CA: Berkeley Lab. Report No. LBNL-56756. http://eetd.lbl.gov/ EA/EMP/reports/56756.pdf Wood Mackenzie. 2007. Impact of a Federal Renewable Portfolio Standard. Edinburgh, Scotland: Wood Mackenzie.

SECTION 2. WIND TURBINE TECHNOLOGY Today’s wind technology has enabled wind to enter the electric power mainstream. Continued technological advancement would be required under the 20% Wind Scenario.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

2.1. Introduction Current turbine technology has enabled wind energy to become a viable power source in today’s energy market. Even so, wind energy provides approximately 1% of total U.S. electricity generation. Advancements in turbine technology that have the potential to increase wind energy’s presence are currently being explored. These areas of study include reducing capital costs, increasing capacity factors, and mitigating risk through enhanced system reliability. With sufficient research, development, and demonstration (RD&D), these new advances could potentially have a significant impact on commercial product lines in the next 10 years. A good parallel to wind energy evolution can be derived from the history of the automotive industry in the United States. The large-scale production of cars began with the first Model T production run in 1910. By 1940, after 30 years of making cars and trucks in large numbers, manufacturers had produced vehicles that could reliably move people and goods across the country. Not only had the technology of the vehicle improved, but the infrastructure investment in roads and service stations made their use practical. Yet 30 years later, in 1970, one would hardly recognize the vehicles or infrastructure as the same as those in 1940. Looking back at the automobiles produced more than 30 years ago, we see how RD&D led to the continuous infusion of modern electronics; improved combustion and manufacturing processes; and ultimately, safer, more reliable cars with higher fuel efficiency. In a functional sense, wind turbines now stand roughly where the U.S. automotive fleet stood in 1940. Gradual improvements have been made in the past 30 years over several generations of wind energy products. These technology advances enable today’s turbines to reliably deliver electricity to the grid at a reasonable cost. Through continued RD&D and infrastructure development, great strides will be made to produce even more advanced machines supporting future deployment of wind power technology. This section describes the status of wind technology today and provides a brief history of technology development over the past three decades. Prospective improvements to

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

128

U.S. Department of Energy

utility-scale land-based wind turbines as well as offshore wind technology are discussed. Distributed wind technology (100 kilowatts (kW) or less) are also addressed in this section.

2.2. Today’s Commercial Wind Technology

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Beginning with the birth of modern wind-driven electricity generators in the late 1970s, wind energy technology has improved dramatically up to the present. Capital costs have decreased, efficiency has increased, and reliability has improved. High- quality products are now routinely delivered by major suppliers of turbines around the world and complete wind generation plants are being engineered into the grid infrastructure to meet utility needs. In the 20% scenario outlined in this report, it is assumed that capital costs would be reduced by 10% over the next two decades and capacity factors would be increased by about 15% (corresponding to a 15% increase in annual energy generation by a wind plant).

Figure 2.1. The wind resource potential at 50 m above ground on land and offshore.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 2.2. Comparison of the wind energy resource at 50 m, 70 m, and 100 m for Indiana.

Figure 2.3. A modern 1.5-MW wind turbine installed in a wind power plant.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

129

130

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

2.2.1. Wind Resources Wind technology is driven by the nature of the resource to be harvested. The United States, particularly the Midwestern region from Texas to North Dakota, is rich in wind energy resources as shown in Figure 2.1, which illustrates the wind resources measured at a 50 meter (m) elevation. Measuring potential wind energy generation at 100-m elevation, the projected operating hub height of the next generation of modern turbines, greatly increases the U.S land area that could be used for wind deployment, as shown in Figure 2.2 for the state of Indiana. Taking these measurements into account, current U.S. land-based and offshore wind resources are estimated to be sufficient to supply the electrical energy needs of the entire country several times over. For a description of U.S. wind resources, see Appendix B. Identifying the good wind potential at high elevations in states such as Indiana and off the shore of both coasts is important because it drives developers to find ways to harvest this energy. Many of the opportunities being pursued through advanced technology are intended to achieve higher elevations where the resource is much greater, or to access extensive offshore wind resources. 2.2.2. Today’s Modern Wind Turbine Modern wind turbines, which are currently being deployed around the world, have threebladed rotors with diameters of 70 m to 80 m mounted atop 60-m to 80-m towers, as illustrated in Figure 2.3. Typically installed in arrays of 30 to 150 machines, the average turbine installed in the United States in 2006 can produce approximately 1.6 megawatts (MW) of electrical power. Turbine power output is controlled by rotating the blades about their long axis to change the angle of attack with respect to the relative wind as the blades spin about the rotor hub. This is called controlling the blade pitch. The turbine is pointed into the wind by rotating the nacelle about the tower. This is called controlling the yaw. Wind sensors on the nacelle tell the yaw controller where to point the turbine. These wind sensors, along with sensors on the generator and drivetrain, also tell the blade pitch controller how to regulate the power output and rotor speed to prevent overloading the structural components. Generally, a turbine will start producing power in winds of about 5.36 m/s and reach maximum power output at about 12.52 m/s–13.41 m/s. The turbine will pitch or feather the blades to stop power production and rotation at about 22.35 m/s. Most utility-scale turbines are upwind machines, meaning that they operate with the blades upwind of the tower to avoid the blockage created by the tower. The amount of energy in the wind available for extraction by the turbine increases with the cube of wind speed; thus, a 10% increase in wind speed creates a 33% increase in available energy. A turbine can capture only a portion of this cubic increase in energy, though, because power above the level for which the electrical system has been designed, referred to as the rated power, is allowed to pass through the rotor. In general, the speed of the wind increases with height above the ground, which is why engineers have found ways to increase the height and the size of wind turbines while minimizing the costs of materials. But land-based turbine size is not expected to grow as dramatically in the future as it has in the past. Larger sizes are physically possible; however, the logistical constraints of transporting the components via highways and of obtaining cranes large enough to lift the components present a major economic barrier that is difficult to overcome. Many turbine designers do not expect the rotors of land-based turbines to become

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

131

much larger than about 100 m in diameter, with corresponding power outputs of about 3 MW to 5 MW.

2.2.3. Wind Plant Performance and Price The performance of commercial turbines has improved over time, and as a result, their capacity factors have slowly increased. Figure 2.4 shows the capacity factors at commercial operation dates (CODs) ranging from 1998 to 2005. The data shows that turbines in the Lawrence Berkeley National Laboratory (Berkeley Lab) database (Wiser and Bolinger 2007) that began operating commercially before 1998 have an average capacity factor of about 22%. The turbines that began commercial operation after 1998, however, show an increasing capacity factor trend, reaching 36% in 2004 and 2005. The cost of wind-generated electricity has dropped dramatically since 1980, when the first commercial wind plants began operating in California. Since 2003, however, wind energy prices have increased. Figure 2.5 (Wiser and Bolinger 2007) shows that in 2006 the price paid for electricity generated in large wind farms was between 3.0 and 6.5 cents/kilowatt-hour (kWh) with an average near 5 cents/kWh(1 cent/kWh = $10/megawatthour [MWh]). This price includes the benefit of the federal production tax credit (PTC), state incentives, and revenue from the sale of any renewable energy credits. Wind energy prices have increased since 2002 for the following reasons (Wiser and Bolinger 2007) •

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

• •

Shortages of turbines and components resulting from the dramatic recent growth of the wind industry in the United States and Europe The weakening U.S. dollar relative to the euro (many major turbine components are imported from Europe and there are relatively few wind turbine component manufacturers in the United States) A significant rise in material costs such as steel and copper as well as transportation fuels over the last three years The on-again, off-again cycle of the wind energy PTC (uncertainty hinders investment in new turbine production facilities and encourages hurried and expensive production, transportation, and installation of projects when the tax credit is available).

Expected future reductions in wind energy costs would come partly from expected investment in the expansion of manufacturing volume in the wind industry. In addition, a stable U.S. policy for renewable energy and a heightened RD&D effort could also lower costs.

2.2.4. Wind Technology Development Until the early 1970s, wind energy filled a small niche market, supplying mechanical power for grinding grain and pumping water, as well as electricity for rural battery charging. With the exception of battery chargers and rare experiments with larger electricity-producing machines, the windmills of 1850 and even 1950 differed very little from the primitive devices from which they were derived. Increased RD&D in the latter half of the twentieth century, however, greatly improved the technology.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

132

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 2.4. Turbine capacity factor by commercial operation date (COD) using 2006 data.

Figure 2.5. Wind energy price by commercial operation date (COD) using 2006 data.

In the 1980s, the practical approach of using low-cost parts from agricultural and boatbuilding industries produced machinery that usually worked, but was heavy, highmaintenance, and grid-unfriendly. Little was known about structural loads caused by turbulence, which led to the frequent and early failure of critical parts, such as yaw drives. Additionally, the small-diameter machines were deployed mostly in densely packed arrays in the California wind corridors that were not aesthetically pleasing in such a rural setting. These densely packed arrays also often blocked the wind from neighboring turbines, producing a great deal of turbulence for the downwind machines. Reliability and availability suffered as a result. Recognizing these issues, wind operators and manufacturers have worked to develop better machines with each new generation of designs. Drag-based devices and simple liftbased designs gave way to experimentally designed and tested high-lift rotors, many with full-span pitch control. Blades that had once been made of sail or sheet metal progressed

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

133

through wood to advanced fiberglass composites. The DC alternator gave way to the gridsynchronized induction generator, which has now been replaced by variable-speed designs employing high-speed solid-state switches of advanced power electronics. Designs moved from mechanical cams and linkages that feathered or furled a machine to high-speed digital controls. A 50-kW machine, considered large in 1980, is now dwarfed by the 1.5-MW to 2.5MW machines being routinely installed today. Many RD&D advances have contributed to these changes. Airfoils, which are now tested in wind tunnels, are designed for insensitivity to surface roughness and dirt. Increased understanding of aeroelastic loads and the ability to incorporate this knowledge into finite element models and structural dynamics codes make the machines of today more robust but also more flexible and lighter on a relative basis than those of a decade ago. As with any maturing technology, however, many of the simpler and easier improvements have already been incorporated into today’s turbines. Increased RD&D efforts and innovation will be required to continue to expand the wind energy industry.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

2.2.5. Current Turbine Size Throughout the past 20 years, average wind turbine ratings have grown almost linearly, as illustrated by Figure 2.6. Each group of wind turbine designers has predicted that its latest machine is the largest that a wind turbine will ever be. But with each new generation of wind turbines (roughly every five years), the size has grown along the linear curve and has achieved reductions in life-cycle cost of energy (COE).

Figure 2.6. The development path and growth of wind turbines.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

134

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

As discussed in Section 2.2.2, this long-term drive to develop larger turbines is a direct result of the desire to improve energy capture by accessing the stronger winds at higher elevations. (The increase in wind speed with elevation is referred to as wind shear.) Although the increase in turbine height is a major reason for the increase in capacity factor over time, there are economic and logistical constraints to this continued growth to larger sizes. The primary argument for limiting the size of wind turbines is based on the square- cube law. This law roughly states that “as a wind turbine rotor grows in size, its energy output increases as the rotor swept area (the diameter squared), while the volume of material, and therefore its mass and cost, increases as the cube of the diameter.” In other words, at some size, the cost for a larger turbine will grow faster than the resulting energy output revenue, making scaling a losing economic game. Engineers have successfully skirted this law by either removing material or using it more efficiently as they increase size. Turbine performance has clearly improved and cost per unit of output has been reduced, as illustrated in Figures 2.4 and 2.5. A Wind Partnerships for Advanced Component Technology (WindPACT) study has also shown that in recent years, blade mass has been scaling at an exponent of about 2.3 as opposed to the expected 3 (Ashwill 2004), demonstrating how successive generations of blade design have moved off the cubic weight growth curve to keep weight down (see Figure 2.7). The latest designs continue to fall below the cubic line of the previous generation, indicating the continued infusion of new technology into blade design. If advanced RD&D were to result in even better design methods, as well as new materials and manufacturing methods that allow the entire turbine to scale as the diameter squared, continuing to innovate around this size limit would be possible.

Figure 2.7. Growth in blade weight.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

135

Land transportation constraints can also limit wind turbine growth for turbines installed on land. Cost-effective road transportation is achieved by remaining within standard over-theroad trailer dimensions of 4.1 m high by 2.6 m wide and a gross vehicle weight (GVW) under 80,000 pounds (lb; which translates to a cargo weight of about 42,000 lb). Loads that exceed 4.83 m in height trigger expensive rerouting to avoid obstructions and often require utility and law enforcement assistance along the roadways. These dimension limits have the most impact on the base diameter of wind turbine towers. Rail transportation is even more dimensionally limited by tunnel and overpass widths and heights. Overall widths should remain within 3.4 m and heights are limited to 4.0 m. Transportation weights are less of an issue in rail transportation with GVW limits of up to 360,000 lb (Ashwill 2004). Once turbines arrive at their destination, their physical installation poses other practical constraints that limit their size. Typically, 1.5-MW turbines are installed on 80-m towers to maximize energy capture. Crane requirements are quite stringent because of the large nacelle mass in combination with the height of the lift and the required boom extension. As the height of the lift to install the rotor and nacelle on the tower increases, the number of available cranes with the capability to make this lift is fairly limited. In addition, cranes with large lifting capacities are difficult to transport and require large crews, leading to high operation, mobilization, and demobilization costs. Operating large cranes in rough or complex hilly terrain can also require repeated disassembly to travel between turbine sites (NREL 2002).

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

2.2.6. Current Status of Turbine Components The Rotor Typically, a modern turbine will cut in and begin to produce power at a wind speed of about 5.37 m/s (see Figure 2.8 below). It will reach its rated power at about 12.52 m/s to 13.41 m/s, where the pitch control system begins to limit power output and prevent generator and drivetrain overload. At around 22.35 m/s, the control system pitches the blades to stop rotation, feathering the blades to prevent overloads and damage to the turbine’s components. The job of the rotor is to operate at the absolute highest efficiency possible between cut-in and rated wind speeds, to hold the power transmitted to the drivetrain at the rated power when the winds go higher, and to stop the machine in extreme winds. Modern unitility-scale wind turbines generally extract about 50% of the energy in this stream below the rated wind speed, compared to the maximum energy that a device can theoretically extract, which is 59% of the energy stream (see The Betz Limit sidebar). Most of the rotors on today’s large-scale machines have an individual mechanism for pitch control; that is, the mechanism rotates the blade about its long axis to control the power in high winds. This device is a significant improvement over the first generation of fixedpitch or collective-pitch linkages because the blades can now be rotated in high winds to feather them out of the wind. This reduces the maximum loads on the system when the machine is parked. Pitching the blades out of high winds also reduces operating loads, and the combination of pitchable blades with a variable-speed generator allows the turbine to maintain generation at a constant rated power output. The older generation of constant-speed rotors sometimes had instantaneous power spikes up to twice the rated power. Additionally, this pitch system operates as the primary safety system because any one of the three independent actuators is capable of stopping the machine in an emergency.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

136

U.S. Department of Energy The Betz Limit

Not all of the energy present in a stream of moving air can be extracted; some air must remain in motion after extraction. Otherwise, no new, more energetic air can enter the device. Building a wall would stop the air at the wall, but the free stream of energetic air would just flow around the wall. On the other end of the spectrum, a device that does not slow the air is not extracting any energy either. The maximum energy that can be extracted from a fluid stream be a device with the same working area as the stream cross section is 59% of the energy in the stream. Because it was first derived by wind turbine pioneer Albert Betz, this maximum is known as the Betz Limit.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Blades As wind turbines grow in size, so do their blades—from about 8 m long in 1980 to more than 40 m for many land-based commercial systems and more than 60 m for offshore applications. Rigorous evaluation using the latest computer analysis tools have improved blade designs, enabling weight growth to be kept to a much lower rate than simple geometric scaling (see Figure 2.7). Designers are also starting to work with lighter and stronger carbon fiber in highly stressed locations to stiffen blades and improve fatigue resistance while reducing weight. (Carbon fiber, however, costs about 10 times as much as fiberglass.) Using lighter blades reduces the load-carrying requirements for the entire supporting structure and saves total cost far beyond the material savings of the blades alone.

Figure 2.8. Typical power output versus wind speed curve.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

137

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

By designing custom airfoils for wind turbines, developers have improved blades over the past 20 years. Although these airfoils were primarily developed to help optimize lowspeed wind aerodynamics to maximize energy production while limiting loads, they also help prevent sensitivity to blade fouling that is caused by dirt and bug accumulation on the leading edge. This sensitivity reduction greatly improves blade efficiency (Cohen et al. 2008). Current turbine blade designs are also being customized for specific wind classes. In lower energy sites, the winds are lighter so design loads can be relaxed and longer blades can be used to harvest more energy in lower winds. Even though blade design methods have improved significantly, there is still much room for improvement, particularly in the area of dynamic load control and cost reduction.

Controls Today’s controllers integrate signals from dozens of sensors to control rotor speed, blade pitch angle, generator torque, and power conversion voltage and phase. The controller is also responsible for critical safety decisions, such as shutting down the turbine when extreme conditions are encountered. Most turbines currently operate in variable-speed mode, and the control system regulates the rotor speed to obtain peak efficiency in fluctuating winds. It does this by continuously updating the rotor speed and generator loading to maximize power and reduce drivetrain transient torque loads. Operating in variable-speed mode requires the use of power converters, which offer additional benefits (discussed in the next subsection). Research into the use of advanced control methods to reduce turbulence-induced loads and increase energy capture is an active area of work. Electrical controls with power electronics enable machines to deliver fault-ride through control, voltage control, and volt-ampere-reactive (VAR) support to the grid. In the early days of grid-connected wind generators, the grid rules required that wind turbines go offline when any grid event was in progress. Now, with penetration of wind energy approaching 10% in some regions of the United States, more than 8% nationally in Germany, and more than 20% of the average generation in Denmark, the rules are being changed (Wiser and Bolinger, 2007). Grid rules on both continents are requiring more support and fault-ride-through protection from the wind generation component. Current electrical control systems are filling this need with wind plants carefully engineered for local grid conditions The Drivetrain (Gearbox, Generator, and Power Converter) Generating electricity from the wind places an unusual set of requirements on electrical systems. Most applications for electrical drives are aimed at using electricity to produce torque instead of using torque to produce electricity. The applications that generate electricity from torque usually operate at a constant rated power. Wind turbines, on the other hand, must generate at all power levels and spend a substantial amount of time at low power levels. Unlike most electrical machines, wind generators must operate at the highest possible aerodynamic and electrical efficiencies in the low-power/low-wind region to squeeze every kilowatt- hour out of the available energy. For wind systems, it is simply not critical for the generation system to be efficient in above-rated winds in which the rotor is letting energy flow through to keep the power down to the rated level. Therefore, wind systems can afford inefficiencies at high power, but they require maximum efficiency at low power—just the opposite of almost all other electrical applications in existence.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

138

U.S. Department of Energy

Torque has historically been converted to electrical power by using a speed- increasing gearbox and an induction generator. Many current megawatt-scale turbines use a three-stage gearbox consisting of varying arrangements of planetary gears and parallel shafts. Generators are either squirrel-cage induction or wound- rotor induction, with some newer machines using the doubly fed induction design for variable speed, in which the rotor’s variable frequency electrical output is fed into the collection system through a solid-state power converter. Full power conversion and synchronous machines are drawing interest because of their fault ridethrough and other grid support capacities. As a result of fleet-wide gearbox maintenance issues and related failures with some designs in the past, it has become standard practice to perform extensive dynamometer testing of new gearbox configurations to prove durability and reliability before they are introduced into serial production. The long-term reliability of the current generation of megawatt-scale drivetrains has not yet been fully verified with long-term, real-world operating experience. There is a broad consensus that wind turbine drivetrain technology will evolve significantly in the next several years to reduce weight and cost and improve reliability.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The Tower The tower configuration used almost exclusively in turbines today is a steel monopole on a concrete foundation that is custom designed for the local site conditions. The major tower variable is the height. Depending on the wind characteristics at the site, the tower height is selected to optimize energy capture with respect to the cost of the tower. Generally, a turbine will be placed on a 60-m to 80-m tower, but 100-m towers are being used more frequently. Efforts to develop advanced tower configurations that are less costly and more easily transported and installed are ongoing. Balance of Station The balance of the wind farm station consists of turbine foundations, the electrical collection system, power-conditioning equipment, supervisory control and data acquisition (SCADA) systems, access and service roads, maintenance buildings, service equipment, and engineering permits. Balance-of-station components contribute about 20% to the installed cost of a wind plant. Operations and Availability Operating and maintenance (O&M) costs have also dropped significantly since the 1980s as a result of improved designs and increased quality. O&M data from the technology installed well before 2000 show relatively high annual costs that increase with the age of the equipment. Annual O&M costs are reported to be as high as $30-$50/MWh for wind power plants with 1980s technology, whereas the latest generation of turbines has reported annual O&M costs below $1 0/MWh (Wiser and Bolinger 2007). Figure 2.9 shows annual O&M expenses by wind project age and equipment installation year. Relative to wind power prices shown in Figure 2.5, the O&M costs can be a significant portion of the price paid for windgenerated electricity. Since the late 1990s, modern equipment operation costs have been reduced for the initial operating years. Whether annual operation costs grow as these modern turbines age is yet to be determined and will depend greatly on the quality of these new machines.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

139

Figure 2.9. Operation and maintenance costs for large-scale wind plants installed within the last 10 years for the early years of operation (Wiser and Bolinger 2007).

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

SCADA systems are being used to monitor very large wind farms and dispatch maintenance personnel rapidly and efficiently. This is one area where experience in managing large numbers of very large machines has paid off. Availability, defined as the fraction of time during which the equipment is ready to operate, is now more than 95% and often reported to exceed 98%. These data indicate the potential for improving reliability and reducing maintenance costs (Walford 2006).

2.3. Technology Improvements on the Horizon Technology improvements can help meet the cost and performance challenges embedded in this 20% Wind Scenario. The required technological improvements are relatively straightforward: taller towers, larger rotors, and continuing progress through the design and manufacturing learning curve. No single component or design innovation can fulfill the need for technology improvement. By combining a number of specific technological innovations, however, the industry can introduce new advanced architectures necessary for success. The 20% Wind Scenario does not require success in all areas; progress can be made even if only some of the technology innovations are achieved.

2.3.1. Future Improvements to Turbine Components Many necessary technological advances are already in the active development stages. Substantial research progress has been documented and individual companies are beginning the development process for these technologies. The risk of introducing new technology at the same time that manufacturing production is scaling up and accelerating to unprecedented levels is not trivial. Innovation always carries risk. Before turbine manufacturers can stake the next product on a new feature, the performance of that innovation needs to be firmly established and the durability needs to be characterized as well as possible. These risks are

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

140

U.S. Department of Energy

mitigated by RD&D investment, including extensive component and prototype testing before deployment. The following are brief summaries of key wind energy technologies that are expected to increase productivity through better efficiency, enhanced energy capture, and improved reliability.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The Rotor The number one target for advancement is the means by which the energy is initially captured—the rotor. No indicators currently suggest that rotor design novelties are on their way, but there are considerable incentives to use better materials and innovative controls to build enlarged rotors that sweep a greater area for the same or lower loads. Two approaches are being developed and tested to either reduce load levels or create load-resistant designs. The first approach is to use the blades themselves to attenuate both gravity- and turbulencedriven loads (see the Blades subsection that follows). The second approach lies in an active control that senses rotor loads and actively suppresses the loads transferred from the rotor to the rest of the turbine structure. These improvements will allow the rotor to grow larger and capture more energy without changing the balance of the system. They will also improve energy capture for a given capacity, thereby increasing the capacity factor (Ashwill 2004). Another innovation already being evaluated at a smaller scale by Energy Unlimited Inc. (EUI; Boise, Idaho) is a variable-diameter rotor that could significantly increase capacity factor. Such a rotor has a large area to capture more energy in low winds and a system to reduce the size of the rotor to protect the system in high winds. Although this is still considered a very high-risk option because of the difficulty of building such a blade without excessive weight, it does provide a completely different path to a very high capacity factor (EUI 2003). Blades Larger rotors with longer blades sweep a greater area, increasing energy capture. Simply lengthening a blade without changing the fundamental design, however, would make the blade much heavier. In addition, the blade would incur greater structural loads because of its weight and longer moment arm. Blade weight and resultant gravity-induced loads can be controlled by using advanced materials with higher strength-to-weight ratios. Because highperformance materials such as carbon fibers are more expensive, they would be included in the design only when the payoff is maximized. These innovative airfoil shapes hold the promise of maintaining excellent power performance, but have yet to be demonstrated in fullscale operation. One elegant concept is to build passive means of reducing loads directly into the blade structure. By carefully tailoring the structural properties of the blade using the unique attributes of composite materials, the internal structure of the blade can be built in a way that allows the outer portion of the blade to twist as it bends (Griffin 2001). “Flap-pitch” or “bendtwist” coupling, illustrated in Figure 2.10, is accomplished by orienting the fiberglass and carbon plies within the composite layers of the blade. If properly designed, the resulting twisting changes the angle of attack over much of the blade, reducing the lift as wind gusts begin to load the blade and therefore passively reducing the fatigue loads. Yet another approach to achieving flap-pitch coupling is to build the blade in a curved shape (see Figure

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

141

2.11) so that the aerodynamic loads apply a twisting action to the blade, which varies the angle of attack as the aerodynamic loads fluctuate. To reduce transportation costs, concepts such as on-site manufacturing and segmented blades are also being explored. It might also be possible to segment molds and move them into temporary buildings close to the site of a major wind installation so that the blades can be made close to or actually at the wind site. 3.000

Position (m)

2.000 1.000 0.000 -1.000

-2.000 -3.000 0

1

2

3

4

5

6

7

8

9

10 11

12 13

14 15

16

17

18

Station (m)

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 2.10. Curvature-based twist coupling.

Figure 2.11. Twist-flap coupled blade design (material-based twist coupling).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

19 20 21

22 23 24 25

142

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Active Controls Active controls using independent blade pitch and generator torque can be used to reduce tower-top motion, power fluctuations, asymmetric rotor loads, and even individual blade loads. Actuators and controllers already exist that can achieve most of the promised load reductions to enable larger rotors and taller towers. In addition, some have published control algorithms that could achieve the load reductions in the research literature (Bossanyi 2003). Sensors capable of acting as the eyes and ears of the control system will need to have sufficient longevity to monitor a high- reliability, low-maintenance system. There is also concern that the increased control activity will accelerate wear on the pitch mechanism. Thus, the technical innovation that is essential to enabling some of the most dramatic improvements in performance is not a matter of exploring the unknown, but rather of doing the hard work of mitigating the innovation risk by demonstrating reliable application through prototype testing and demonstration. Towers To date there has been little innovation in the tower, which is one of the more mundane components of a wind installation. But because placing the rotor at a higher elevation is beneficial and because the cost of steel continues to rise rapidly, it is highly likely that this component will be examined more closely in the future, especially for regions of higher than average wind shear. Because power is related to the cube of wind speed, mining upward into these rich veins of higher wind speed potentially has a high payoff—for example, a 10% increase in wind speed produces about a 33% increase in available power. Turbines could sit on even taller towers than those in current use if engineers can figure out how to make them with less steel. Options for using materials other than steel (e.g., carbon fiber) in the tower are being investigated. Such investigations could bear fruit if there are significant adjustments in material costs. Active controls that damp out tower motion might be another enabling technology. Some tower motion controls are already in the research pipeline. New tower erection technologies might play a role in O&M that could also help drive down the system COE (NREL 2002). Tower diameters greater than approximately 4 m would incur severe overland transportation cost penalties. Unfortunately, tower diameter and material requirements conflict directly with tower design goals—a larger diameter is beneficial because it spreads out the load and actually requires less material because its walls are thinner. On-site assembly allows for larger diameters but also increases the number of joints and fasteners, raising labor costs as well as concerns about fastener reliability and corrosion. Additionally, tower wall thickness cannot be decreased without limit; engineers must adhere to certain minima to avoid buckling. New tower wall topologies, such as corrugation, can be employed to alleviate the buckling constraint, but taller towers will inevitably cost more. The main design impact of taller towers is not on the tower itself, but on the dynamics of a system with the bulk of its mass atop a longer, more slender structure. Reducing tower-top weight improves the dynamics of such a flexible system. The tall tower dilemma can be further mitigated with smarter controls that attenuate tower motion by using blade pitch and generator torque control. Although both approaches have been demonstrated, they are still rarely seen in commercial applications.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

20% Wind Energy by 2030

143

The Drivetrain (Gearbox, Generator, and Power Conversion) Parasitic losses in generator windings, power electronics, gears and bearings, and other electrical devices are individually quite small. When summed over the entire system, however, these losses add up to significant numbers. Improvements that remove or reduce the fixed losses during low power generation are likely to have an important impact on raising the capacity factor and reducing cost. These improvements could include innovative powerelectronic architectures and large- scale use of permanent-magnet generators. Direct-drive systems also meet this goal by eliminating gear losses. Modular (transportable) versions of these large generation systems that are easier to maintain will go a long way toward increasing the productivity of the low-wind portion of the power curve. Currently, gearbox reliability is a major issue and gearbox replacement is quite expensive. One solution is a direct-drive power train that entirely eliminates the gearbox. This approach, which was successfully adopted in the 1990s by EnerconGmbH (Aurich, Germany), is being examined by other turbine manufacturers. A less radical alternative reduces the number of stages in the gearbox from three to two or even one, which enhances reliability by reducing the parts count. The fundamental gearbox topology can also be improved, as Clipper Windpower (Carpinteria, California) did with its highly innovative multiple-drive-path gearbox, which divides mechanical power among four generators (see Figure 2.12). The multiple-drive-path design radically decreases individual gearbox component loads, which reduces gearbox weight and size, eases erection and maintenance demands, and improves reliability by employing inherent redundancies. The use of rare-earth permanent magnets in generator rotors instead of wound rotors also has several advantages. High energy density eliminates much of the weight associated with copper windings, eliminates problems associated with insulation degradation and shorting, and reduces electrical losses. Rare-earth magnets cannot be subjected to elevated temperatures, however, without permanently degrading magnetic field strength, which imposes corresponding demands on generator cooling reliability. Availability of rare-earth permanent magnets is a potential concern because key raw materials are not available in significant quantities within the United States (see Section 3). Power electronics have already achieved elevated performance and reliability levels, but opportunities for significant improvement remain. New silicon carbide (SiC) devices entering the market could allow operation at higher temperature and higher frequency, while improving reliability, lowering cost, or both. New circuit topologies could furnish better control of power quality, enable higher voltages to be used, and increase overall converter efficiency. Distributed Energy Systems (Wallingford, Connecticut; formerly Northern Power Systems) has built an advanced prototype power electronics system that will deliver lower losses and conversion costs for permanent-magnet generators (Northern Power Systems 2006). Peregrine Power (Wilsonville, Oregon) has concluded that using SiC devices would reduce power losses, improve reliability, and shrink components by orders of magnitude (Peregrine Power 2006). A study completed by BEW Engineering (San Ramon, California; Behnke, Erdman, and Whitaker Engineering 2006) shows that using medium-voltage power systems for multimegawatt turbines could reduce the cost, weight, and volume of turbine electrical components as well as reduce electrical losses. The most dramatic change in the long-term application of wind generation may come from the grid support provided by the wind plant. Future plants will not only support the grid

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

144

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

by delivering fault-ride-through capability as well as frequency, voltage, and VAR control, but will also carry a share of power control capability for the grid. Plants can be designed so that they furnish a measure of dispatch capability, carrying out some of the traditional duties of conventional power plants. These plants would be operated below their maximum power rating most of the time and would trade some energy capture for grid ancillary services. Paying for this trade-off will require either a lower capital cost for the hardware, contractual arrangements that will pay for grid services at a high enough rate to offset the energy loss, or optimally, a combination of the two. Wind plants might transition, then, from a simple energy source to a power plant that delivers significant grid support.

2.3.2. Learning-curve Effect Progressing along the design and manufacturing learning curve allows engineers to develop technology improvements (such as those listed in Section 2.3.1) and reduce capital costs. The more engineers and manufacturers learn by conducting effective RD&D and producing greater volumes of wind energy equipment, the more proficient and efficient the industry becomes. The learning curve is often measured by calculating the progress ratio, defined as the ratio of the cost after doubling cumulative production to the cost before doubling. The progress ratio for wind energy from 1984 to 2000 was calculated for the high volume of machines installed in several European countries that experienced a healthy combination of steadily growing manufacturing output, external factors, and research investment during that time. Results show that progress ratio estimates were approximately the same for Denmark (91%), Germany (94%), and Spain (91%) (ISET 2003). At the time this report was written, there was not enough reliable data on U.S.-based manufacturing of wind turbines to determine a U.S. progress ratio. Figure 2.13 shows the data for Spain. Moving from the current level of installed wind capacity of roughly 12 gigawatts (GW) to the 20% Wind Scenario total of 305 GW will require between four and five doublings of capacity. If the progress ratio of 91% shown in Figure 2.13 continues, prices could drop to about 65% of current costs, a 35% reduction. The low-hanging fruit of cost reduction, however, has already been harvested. The industry has progressed from machines based on designs created without any design tools and built almost entirely by hand to the current state of advanced engineering capability. The assumption in the 20% Wind Scenario is that a 10% reduction in capital cost could accelerate large-scale deployment. In order to achieve this reduction, a progress ratio of only 97.8% is required to produce a learning effect of 10% with the 4.6 doublings. With sustained manufacturing growth and technological advancement, there is no technical barrier to achieving 10% capital cost reduction. See Appendix B for further discussion.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

145

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 2.12. Clipper Windpower multiple-drive-path gearbox.

Note: The Y axis represents cost and is presented in logarithmic units. The data points shown fit the downward-sloping straight line with a correlation coefficient, r2, of 0.85. Figure 2.13. Cost of wind turbines delivered from Spain between 1984 and 2000.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

146

U.S. Department of Energy

2.3.3. The System Benefits of Advanced Technology A cost study conducted by the U.S. Department of Energy (DOE) Wind Program identify numerous opportunities for technology advancement to reduce the life-cycle COE (Cohen and Schweizer et al 2008). Based on machine performance and cost, this study used advanced concepts to suggest pathways that integrate the individual contributions from componentlevel improvements into system-level estimates of the capital cost, annual energy production, reliability, O&M, and balance of station. The results, summarized in Table 2.1, indicate significant potential impacts on annual energy production and capital cost. Changes in annual energy production are equivalent to changes in capacity factor because the turbine rating was fixed. A range of values represents the best, most likely, and least beneficial outcomes. Table 2.1. Areas of potential technology improvement Technical Area

Advanced Tower Concepts

Potential Advances

*

Taller towers in difficult locations New materials and/or processes * Advanced structures/foundations * Self-erecting, initial, or for service * Advanced materials * Improved structural-aero design * Active controls * Passive controls * Higher tip speed/lower acoustics * Reduced blade soiling losses * Damage-tolerant sensors * Robust control systems * Prognostic maintenance * Fewer gear stages or direct-drive * Medium/low speed generators * Distributed gearbox topologies * Permanent-magnet generators * Medium-voltage equipment * Advanced gear tooth profiles * New circuit topologies * New semiconductor devices * New materials ( gallium arsenide [GaAs], SiC) * Sustained, incremental design and process improvements * Large-scale manufacturing * Reduced design loads

Performance and Cost Increments (Best/Expected/Least Percentages) Annual Energy Turbine Production Capital Cost +1 1/+1 1/+1 1

+8/+12/+20

+35/+25/+10

-6/-3/+3

+7/+5/0

0/0/0

+8/+4/0

-1 1/-6/+1

0/0/0

-27/-13/-3

+61/+45/+21

-36/-10/+21

*

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Advanced (Enlarged) Rotors

Reduced Energy Losses and Improved Availability

Drivetrai n (Gearboxes and Generators and Power Electronics)

Manufacturing and Learning Curve*

Totals *

The learning curve results from the NREL report (Cohen and Schweizer et al 2008) are adjusted from 3.0 doublings in the reference to the 4.6 doublings in the 20% Wind Scenario.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

20% Wind Energy by 2030

147

The Table 2.1 capacity factor improvement of 11% that results from taller towers reflects the increase in wind resources at a hub height of 120 m, conservatively assuming the standard wind shear distribution meteorologists use for open country. Uncertainty in these capacity factor improvements are reflected in the table below. Depending on the success of new tower technology, the added costs could range from 8% to 20%, but there will definitely be an added cost if the tower is the only component in the system that is modified to take the rotor to higher elevations. An advantage would come from a system design in which the tower head mass is significantly reduced with the integration of a rotor and drivetrain that are significantly lighter. The capital cost reduction shown for the drivetrain components is mainly attributed to the reduced requirements on the structure when lighter components are placed on the tower top. Performance increases as parasitic losses in mechanical and electrical components are reduced. Such components are designed specifically to optimize the performance for wind turbine characteristics. The improvements shown in Table 2.1 are in the single digits but not trivial. Without changing the location of the rotor, energy capture can also be increased by using longer blades to sweep more area. A 10% to 35% increase in capacity factor is produced by 5% to 16% longer blades for the same rated power output. Building these longer blades at an equal or lower cost is a challenge because blade weight must be capped while turbulencedriven loads remain no greater than what the smaller rotor can handle. With the potential of new structurally efficient airfoils, new materials, passive load attenuation, and active controls, it is estimated that this magnitude of blade growth can be achieved in combination with a modest system cost reduction. Technology advances can also reduce energy losses in the field. Improved O&M techniques and monitoring capabilities can reduce downtime for repairs and scheduled maintenance. It is also possible to mitigate losses resulting from degradation of performance caused by wear and dirt over time. These improvements are expected to be in the single digits at best, with an approximate 5% improvement in lifetime energy capture. Doubling the number of manufactured turbines several times over the years will produce a manufacturing learning-curve effect that can also help reduce costs. The learning-curve effects shown in Table 2.1 are limited to manufacturing-related technology improvements and do not reflect issues of component selection and design. As discussed in Section 2.3.2, the learning curve reflects efficiencies driven by volume production and manufacturing experience as well as the infusion of manufacturing technology and practices that encourage more manufacturing-friendly design in the future. Although these changes do not target any added energy capture, they are expected to result in continuous cost reductions. The only adjustment from the NREL (Cohen and Schweizer et al 2008) reference is that the 20% Wind Scenario by 2030 requires 4.6 doublings of cumulative capacity rather than the 3.0 doublings used in the reference targeted at the year 2012. The most likely 13% cost reduction assumes a conservative progress ratio of 97% per doubling of capacity. However, there are a range of possible outcomes. The potential technological advances outlined here support the technical feasibility of the 20% Wind Scenario by outlining several possible pathways to a substantial increase in capacity factor accompanied by a modest but double-digit reduction in capital cost.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

148

U.S. Department of Energy

2.3.4. Targeted RD&D While there is an expected value to potential technology improvements, the risk of implementing them has not yet been reduced to the level that allows those improvements to be used in commercial hardware. The issues are well known and offer an opportunity for focused RD&D efforts. In the past, government and industry collaboration has been successful in moving high-risk, high-potential technologies into the marketplace. One example of such collaboration is the advanced natural gas turbine, which improved the industry efficiency standard—that had been capped at 50%—to almost 60%. DOE invested $100 million in the H-system turbine and General Electric (GE) invested $500 million. Although it was known that higher operating temperatures would lead to higher efficiency, there were no materials for the turbine blades that could withstand the environment. The research program focused on advanced cooling techniques and new alloys to handle combustion that was nearly 300°F hotter. The project produced the world’s largest single crystal turbine blades capable of resisting high-temperature cracking. The resulting “H system” gas turbine is 11.89 m long, 4.89 m in diameter, and weighs more than 811,000 lb. Each turbine is expected to save more than $200 million in operating costs over its lifetime (DOE 2000). A similar example comes from the aviation world. The use of composite materials was known to provide excellent benefits for light-jet airframes, but the certification process to characterize the materials was onerous and expensive. NASA started a program to “reduce the cost of using composites and develop standardized procedures for certifying composite materials” (Brown 2007). The Advanced General Aviation Transport Experiments (AGATE), which began in 1994, solved those problems and opened the door for new composite material technology to be applied to the light-jet application. A technology that would have been too high risk for the individual companies to develop was bridged into the marketplace through a cooperative RD&D effort by NASA, the Federal Aviation Administration (FAA), industry, and universities. The Adam aircraft A500 turboprop and the A700 very light jet are examples of new products based on this composite technology. Some might claim that wind technology is a finished product that no longer needs additional RD&D, or that all possible improvements have already been made. The reality is that the technology is substantially less developed than fossil energy technology, which is still being improved after a century of generating electricity. A GE manager who spent a career in the gas turbine business and then transferred to manage the wind turbine business noted the complexity of wind energy technology: “Our respect for wind turbine technology has grown tremendously. The practical side is so complex and forces are so dramatic. We would never have imagined how complex turbines are” (Knight and Harrison 2005). Already, there is a clear understanding of the materials, controls, and aerodynamics issues that must be resolved to make progress toward greater capacity factors. The combination of reduced capital cost and increased capacity factor will lead to reduced COE. Industry feels the risk of bringing new technology into the marketplace without a full-scale development program is too great and believes sustained RD&D would help reduce risk and help enable the transfer of new technology to the marketplace.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

149

2.4. Addressing Technical and Financial Risks Risks tend to lessen industry’s desire to invest in wind technology. The wind plant performance track record, in terms of generated revenues and operating costs compared with the estimated revenues used in plant financing, will drive the risk level of future installations. The consequences of these risks directly affect the revenues of owners of wind manufacturing and operating capabilities.

2.4.1. Direct Impacts When owners of wind manufacturing and operating capabilities directly bear the costs of failure, the impacts are said to be direct. This direct impact on revenue is often caused by: •

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

•

Increasing O&M costs: As discussed previously and illustrated in Figure 2.9, there is mounting evidence that O&M costs are increasing as wind farms age. Most of these costs are associated with unplanned maintenance or components wearing out before the end of their intended design lives. Some failures can be traced to poor manufacturing or installation quality. Others are caused by design errors, many of which are caused by weaknesses in the technology’s state of the art, generally codified by the design process. Figures 2.14 and 2.15 show steadily rising O&M costs for wind farms installed in the United States in the two decades before the turn of the century and the components that have caused these increasing costs, respectively. The numbers and costs of component failures increase with time, and the risk to the operators grows accordingly. In Figure 2.15 the solid lines represent expected repairs that may not be completely avoidable, and the dashed lines show potential early failures that can significantly increase risk. Poor availability driven by low reliability: Energy is not generated while components are being repaired or replaced. Although a single failure of a critical component stops production from only one turbine, such losses can mount up to significant sums of lost revenue. Poor wind plant array efficiency: If turbines are placed too close together, their wakes interact, which can cause the downwind turbines to perform poorly. But if they are placed too far apart, land and plant maintenance costs increase.

2.4.2. Indirect Impacts Although the wind industry has achieved high levels of wind plant availability and reliability, unpredictable or unreliable performance would threaten the credibility of this emerging technology in the eyes of financial institutions. The consequences of real or perceived reliability problems would extend beyond the direct cost to the plant owners. These consequences on the continued growth of investment in wind could include: •

Increased cost of insurance and financing: Low interest rates and long-term loans are critical to financing power plants that are loaded with upfront capital costs. Each financial institution will assess the risk of investing in wind energy and charge according to those risks. If wind power loses credibility, these insurance and financing costs could increase.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

150

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 2.14. Unplanned repair cost, likely sources, and risk of failure with wind plant age.

Figure 2.15. Average O&M costs of wind farms in the United States.

•

•

Slowing or stopping development: Lost confidence contributed to the halt of development in the United States in the late 1980s through the early 1990s. Development did not start again until the robust European market supported the technology improvements necessary to reestablish confidence in reliable European turbines. As a result, the current industry is dominated by European wind turbine companies. Active technical supporters of RD&D must anticipate and resolve problems before they threaten industry development. Loss of public support: If wind power installations do not operate continuously and reliably, the public might be easily convinced that renewable energy is not a viable source of energy. The public’s confidence in the technology is crucial. Without public support, partnerships working toward a new wind industry future cannot be successful.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

151

Industry Standards The American National Standards Institute (ANSI) has designated the American Wind Energy Association (AWEA) as the lead organization for the development and publication of industry consensus standards for wind energy equipment and services in the United States. AWEA also participates in the development of international wind energy standards through its representation on the International Electrotechnical Commission (IEC) TC-88 Subcommittee. Information on these standards can be accessed on AWEA’s Web site (http://www.awea.org/standards).

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Certification Certification involves high-level, third-party technical audits of a manufacturer’s design development. It includes a detailed review of design analyses, material selections, dynamic modeling, and component test results. The wind industry recognizes that analytical reviews are not sufficient to capture weaknesses in the design process. Therefore, consensus standard developers also require full-scale testing of blades, gearboxes, and the complete system prototype (see Industry Standards sidebar). Actively complying with these standards encourages investment in wind energy by ensuring that turbines reliably achieve the maximum energy extraction needed to expand the industry. Full-Scale Testing Testing standards were drafted to ensure that accredited third-party laboratories are conducting tests consistently. These tests reveal many design and manufacturing deficiencies that are beyond detection by analytical tools. They also provide the final verification that the design process has worked and give the financial community the confidence needed to invest in a turbine model. Full-scale test facilities and trained test engineers capable of conducting full-scale tests are rare. The facilities must have equipment capable of applying tremendous loads that mimic the turbulence loading that wind applies over the entire life of the blade or gearbox. Full-scale prototype tests are conducted in the field at locations with severe wind conditions. Extensive instrumentation is applied to the machine, according to a test plan prescribed by international standards, and comprehensive data are recorded over a specified range of operating conditions. These data give the certification agent a means for verifying the accuracy of the design’s analytical basis. The industry and financial communities depend on these facilities and skilled test engineers to support all new turbine component development. As turbines grow larger and more products come on the market, test facilities must also grow and become more efficient. New blades are reaching 50 m in length, and the United States has no facilities that can test blades longer than 50 m. Furthermore, domestic dynamometer facilities capable of testing gearboxes or new drivetrains are limited in capacity to 1.5 MW. The limited availability of facilities and qualified test engineers increases the deployment risk of new machines that are not subjected to the rigors of current performance validation in accredited facilities.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

152

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 2.16. Blade growth and startup dates for U.S. blade test facilities.

At full-scale facilities, it is also difficult to conduct tests accurately and capture the operating conditions that are important to verify the machine's reliability. These tests are expensive to conduct and accreditation is expensive to maintain for several reasons. First, the scale of the components is one of the largest of any commercial industry. Because blades are approaching sizes of half the length of a football field and can weigh more than a 12.2-m yacht, they are very difficult and expensive to transport on major highways. The magnitude of torque applied to the drivetrains for testing is among the largest of any piece of rotating equipment ever constructed. Figure 2.16 shows the largest blades being built and the approximate dates when U.S. blade test facilities were built to accommodate their testing. Although it is very expensive for each manufacturer to develop and maintain facilities of this scale for its own certification testing needs, without these facilities, rapid technological progress will be accompanied by high innovation risk. Wind energy history has proven that these kinds of tests are crucial for the industry’s success and the financial community’s confidence. These tests, then, are an essential element of any risk mitigation strategy.

Performance Monitoring and O&M One of the main elements of power plant management is strategic monitoring of reliability. Other industries have established anonymous databases that serve to benchmark their reliability and performance, giving operators both the ability to recognize a drop in reliability and the data they need to determine the source of low reliability. The wind industry needs such a strategically designed database, which would give O&M managers the tools to recognize and pinpoint drops in reliability, along with a way to collectively resolve technical problems. Reliability databases are an integral part of more sophisticated O&M management tools. Stiesdal and Madsen (2005) describe how databases can be used for managing O&M and improving future designs.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

153

In mature industries, O&M management tools are available to help maximize maintenance efficiency. Achieving this efficiency is a key factor in minimizing the COE and maximizing the life of wind plants, thereby increasing investor confidence. Unlike central generation facilities, wind plants require maintenance strategies that minimize human attention and maximize remote health monitoring and automated fault data diagnosis. This requires intimate knowledge of healthy plant operating characteristics and an ability to recognize the characteristics of very complex faults that might be unique to a specific wind plant. Such tools do not currently exist for the wind industry, and their development will require RD&D to study wind plant systems interacting with complex atmospheric conditions and to model the interactions. The resultant deeper understanding will allow expert systems to be developed, systems that will aid operators in their quest to maximize plant performance and minimize operating costs through risk mitigation. These systems will also produce valuable data for improving the next generation of turbine designs.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

2.5. Offshore Wind Technology Offshore wind energy installations have a broadly dispersed, abundant resource and the economic potential for cost competitiveness that would allow them to make a large impact in meeting the future energy needs of the United States (Musial, 2007). Of the contiguous 48 states, 28 have a coastal boundary. U.S. electric use data show that these same states use 78% of the nation’s electricity (EIA 2006). Of these 28 states, only 6 have a sufficient land-based wind energy resource to meet more than 20% of their electric requirements through wind power. If shallow water offshore potential (less than 30 m in depth) is included in the wind resource mix, though, 26 of the 28 states would have the wind resources to meet at least 20% of their electric needs, with many states having sufficient offshore wind resources to meet 100% of their electric needs (Musial, 2007). For most coastal states, offshore wind resources are the only indigenous energy source capable of making a significant energy contribution. In many congested energy-constrained regions, offshore wind plants might be necessary to supplement growing demand and dwindling fossil supplies. Twenty-six offshore wind projects with an installed capacity of roughly 1,143 MW now operate in Europe. Most projects were installed in water less than 22 m deep. One demonstration project in Scotland is installed in water at a depth of 45 m. Although some projects have been hampered by construction overruns and higher than-expected maintenance requirements, projections show strong growth in many European Union (EU) markets. For example, it is estimated that offshore wind capacity in the United Kingdom will grow by 8,000 MW by 2015. Similarly, German offshore development is expected to reach 5,600 MW by 2014 (BSH & BWEA). In the United States, eight or nine offshore project proposals in state and federal waters total to a capacity of more than 1,500 MW. Two of these proposed projects are being treated separately by the Minerals Management Service (MMS) because the permits were submitted before MMS authority was established by the Energy Policy Act (EPAct) of 2005 (MMS). Two other projects in Texas state waters have already received state approval.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

154

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

2.5.1. Cost of Energy The current installed capital cost of offshore projects is estimated in the range of $2,400 to $5000 per kW (Black and Veatch, forthcoming 2008, Pace Global 2007). Because offshore wind energy tends to take advantage of extensive land-based experience and mature offshore oil and gas practices, offshore cost reductions are not expected to be as great as land-based reductions spanning the past two decades. However, offshore wind technology is considerably less mature than land-based wind energy, so it does have significant potential for future cost reduction. These cost reductions are achievable through technology development and innovation, implementation and customization of offshore oil and gas practices, and learning- curve reductions that take advantage of more efficient manufacturing and deployment processes and procedures. 2.5.2. Current Technology Today’s baseline technology for offshore wind turbines is essentially a version of the standard land-based turbine adapted to the marine environment. Although turbines of up to 5 MW have been installed, most recent orders from Vestas (Randers, Denmark) and Siemens (Munich, Germany), the two leading suppliers of offshore wind turbines, range from 2.0 MW to 3.6 MW. The architecture of the baseline offshore turbine and drivetrain comprises a three- bladed upwind rotor, typically 90 m to 107 m in diameter. Tip speeds of offshore turbines are slightly higher than those of land-based turbines, which have speeds of 80 m/s or more. The drivetrain consists of a gearbox generally run with variable- speed torque control that can achieve generator speeds between 1,000 and 1,800 rpm. The offshore tower height is generally 80 m, which is lower than that of land- based towers because wind shear profiles are less steep, tempering the advantage of tower height. The offshore foundation system baseline technology uses monopiles at nominal water depths of 20 m. Monopiles are large steel tubes with a wall thickness of up to 60 mm and diameters of 6 m. The embedment depth varies with soil type, but a typical North Sea installation must be embedded 25 m to 30 m below the mud line. The monopile extends above the surface where a transition piece with a flange to fasten the tower is leveled and grouted. Its foundation requires a specific class of installation equipment for driving the pile into the seabed and lifting the turbine and tower into place. Mobilization of the infrastructure and logistical support for a large offshore wind plant accounts for a significant portion of the system cost. Turbines in offshore applications are arranged in arrays that take advantage of the prevailing wind conditions measured at the site. Turbines are spaced to minimize aggregate power plant energy losses, interior plant turbulence, and the cost of cabling between turbines. The power grid connects the output from each turbine, where turbine transformers step up the generator and the power electronics voltage to a distribution voltage of about 34 kilovolts (kV). The distribution system collects the power from each turbine at a central substation where the voltage is stepped up and transmitted to shore through a number of buried, highvoltage subsea cables. A shore-based interconnection point might be used to step up the voltage again before connecting to the power grid. Shallow water wind turbine projects have been proposed and could be followed by transitional and finally deepwater turbines. These paths should not be considered as mutually exclusive choices. Because there is a high degree of interdependence among them, they

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

155

should be considered a sequence of development that builds from a shallow water foundation of experience and knowledge to the complexities of deeper water.

2.5.3. Technology Needs and Potential Improvements Offshore, wind turbine cost represents only one-third of the total installed cost of the wind project, whereas on land, the turbine cost represents more than half of the total installed cost. To lower costs for offshore wind, then, the focus must be on lowering the balance-ofstation costs. These costs, which include those for foundations, electrical grids, O&M, and installation and staging costs, dominate the system COE. Turbine improvements that make turbines more reliable, more maintainable, more rugged, and larger, will still be needed to achieve cost goals. Although none of these improvements is likely to lower turbine costs, the net result will lower overall system costs. The commercialization of offshore wind energy faces many technical, regulatory, socioeconomic, and political barriers, some of which may be mitigated through targeted short- and long-range RD&D efforts. Short-term research addresses impediments that are preventing initial industry projects from proceeding and helps to sharpen the focus for longterm research. Long-term research involves a more complex development process resulting in improvements that can help lower offshore life-cycle system costs. Short-Term RD&D Options Conducting research that will lead to more rapid deployment of offshore turbines should be an upfront priority for industry. This research should address obstacles to today’s projects, and could include the following tasks:

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

•

•

Define offshore resource exclusion zones: A geographically based exclusion study using geographic information system (GIS) land use overlays would more accurately account for all existing and future marine uses and sensitive areas. This type of exclusion study could be part of a regional programmatic environmental impact statement and is necessary for a full assessment of the offshore resource (Dhanju, Whitaker, and Kempton 2006). Currently, the developer bears the burden of siting during a pre-permitting phase with very little official guidance. This activity should be a jointly funded industry project conducted on a regional basis. Develop certification methods and standards: MMS has been authorized to define the structural safety standards for offshore wind turbines on the OCS. Technical research, analysis, and testing are needed to build confidence that safety will be adequate and to prevent overcautiousness that will increase costs unnecessarily. Development of these standards will require a complete evaluation and harmonization of the existing offshore wind standards and the American Petroleum Institute (API) offshore oil and gas standards. MMS is currently determining the most relevant standards. Develop design codes, tools, and methods: The design tools that the wind industry uses today have been developed and validated for land-based utility-scale turbines, and the maturity and reliability of the tools have led to significantly higher confidence in today’s wind turbines. Offshore design tools are relatively immature by comparison. The development of accurate offshore computer codes to predict the

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

156

U.S. Department of Energy

•

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

dynamic forces and motions acting on turbines deployed at sea is essential for moving into deeper water. One major challenge is predicting loads and the resulting dynamic responses of the wind turbine support structure when it is subjected to combined wave and wind loading. These offshore design tools must be validated to ensure that they can deal with the combined dominance of simultaneous wind and wave load spectra, which is a unique problem for offshore wind installations. Floating system analysis must be able to account for additional turbine motions as well as the dynamic characterization of mooring lines. Site turbines and configure arrays: The configuration and spacing of wind turbines within an array have a marked effect on power production from the aggregate wind plant, as well as for each individual turbine. Uncertainties in power production represent a large economic risk factor for offshore development. Offshore wind plants can lose more than 10% of their energy to array losses, but improvements in array layout and array optimization models could deliver substantial recovery (Seawind 2003). Atmospheric boundary layer interaction with the turbine wakes can affect both energy capture and plant-generated turbulence. Accurate characterization of the atmospheric boundary layer behavior and more accurate wake models will be essential for designing turbines that can withstand offshore wind plant turbulence. Wind plant design tools that are able to characterize turbulence generated by wind plants under a wide range of conditions are likely necessary. Develop hybrid wind-speed databases: Wind, sea-surface temperatures, and other weather data are housed in numerous satellite databases available from the National Oceanic and Atmospheric Administration (NOAA), NASA, the National Weather Service (NWS), and other government agencies. These data can be combined to supplement the characterization of coastal and offshore wind regimes (Hasager et al. 2005). The limitations and availability of existing offshore data must be understood. Application of these data to improve the accuracy of offshore wind maps will also be important.

Long-Term R&D Options Long-term research generally requires hardware development and capital investment, and it must take a complex development path that begins early so that mature technology will be ready when it is needed. Most long-term research areas relate to lowering offshore life-cycle system costs. These areas are subdivided into infrastructure and turbine-specific needs. Infrastructure to support offshore wind development represents a major cost element. Because this is a relatively new technology path, there are major opportunities for reducing the cost impacts in this area. Although land-based wind turbine designs can generally be used for offshore deployment, the offshore environment will impose special requirements on turbines. These requirements must be taken into account to optimize offshore deployment. Areas where industry should focus efforts include: •

Minimize work at sea: There are many opportunities to lower project costs by reallocating the balance between work done on land and at sea. In addition, the portion of labor devoted to project O&M, land-based installation and assembly, and remote inspections and diagnostics can be rebalanced with respect to upfront capital

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

•

•

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

•

157

enhancements, such as higher quality assurance, more qualification testing, and reliable designs. This rebalancing might enable a significant life-cycle cost reduction by shifting the way wind projects are designed, planned, and managed. Enhance manufacturing, installation and deployment strategies: New manufacturing processes and improvements in existing processes that reduce labor and material usage and improve part quality have high potential for reducing costs in offshore installations. Offshore wind turbines and components could be constructed and assembled in or near seaport facilities that allow easy access from the production area to the installation site, eliminating the necessity of shipping large components over inland roadways. Fabrication facilities must be strategically located for massproduction, land-based assembly, and for rapid deployment with minimal dependence on large vessels. Offshore system designs that can be floated out and installed without large cranes can reduce costs significantly. New strategies should be integrated into the turbine design process at an early stage (Lindvig 2005; Poulsen and Skjærbæk 2005). Incorporate offshore service and accessibility features: To manage O&M, predict weather windows, minimize downtime, and reduce the equipment needed for uptower repairs, operators should be equipped with remote, intelligent, turbine condition monitoring and self-diagnostic systems. These systems can alert operators to the need for operational changes or to schedule maintenance at the most opportune times. A warning about an incipient failure can alert the operators to replace or repair a component before it does significant damage to the system or leaves the machine inoperable for an extended period of time. More accurate weather forecasting will also become a major contributor in optimizing service for lower cost. Develop low-cost foundations, anchors, and moorings: Current shallow-water foundations have already reached a practical depth limit of 30 m, and anchor systems beyond that are derived from conservative and expensive oil and gas design practices. Cost- saving opportunities arise for wind power plants in deeper water with both fixed-bottom and floating turbine foundations, as well as for existing shallowwater designs in which value-engineering cost reductions can be achieved. Fixedbottom systems comprising rigid lightweight substructures, automated massproduction fabrication facilities, and integrated mooring and piling deployment systems that minimize dependence on large sea vessels are possible low-cost options. Floating platforms will require a new generation of mooring designs that can be mass produced and easily installed. Use resource modeling and remote profiling systems: Offshore winds are much more difficult to characterize than winds over land. Analytical models are essential to managing risk during the initial siting of offshore projects, but are not very useful by themselves for micrositing (Jimenez et al. 2005). Alternative methods are needed to measure wind speed and wind shear profiles up to elevations where wind turbines operate. This will require new equipment such as sonic detection and ranging (SODAR), light detection and ranging (LIDAR), and coastal RADAR-based systems that must be adapted to measure offshore wind from more stable buoy systems or from fixed bases. Some systems are currently under development but have not yet been proven (Antoniou et al. 2006). The results of an RD&D measurement program

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

158

U.S. Department of Energy

•

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

on commercial offshore projects could generate enough confidence in these systems to eliminate the requirement for a meteorological tower. Increase offshore turbine reliability: The current offshore service record is mixed, and as such, is a large contributor to high risk. A new balance between initial capital investment and long-term operating costs must be established for offshore systems, which will have a significant impact on COE. Offshore turbine designs must place a higher premium on reliability and anticipation of on-site repairs than their land-based counterparts. Emphasis should be placed on avoiding large maintenance events that require expensive and specialized equipment. This can be done by identifying the root causes of component failures, understanding the frequency and cost of each event, and appropriately implementing design improvements (Stiesdal and Madsen 2005). Design tools, quality control, testing, and inspection will need heightened emphasis. Blade designers must consider strategies to offset the impacts of marine moisture, corrosion, and extreme weather. In higher latitudes, designers must also account for ice flows and ice accretion on the blades. Research that improves landbased wind turbine reliability now will have a direct impact on the reliability of future offshore machines. Assess the potential of ultra-large offshore turbines: Land-based turbines may have reached a size plateau because of transportation and erection limits. Further size growth in wind turbines will largely be pushed by requirements unique to offshore turbine development. According to a report on the EU-funded UpWind project, “Within a few years, wind turbines will have a rotor diameter of more than 150 m and a typical size of 8 MW–1 0 MW” (Risø National Laboratory 2005). The UpWind project plans to develop design tools to optimize large wind turbine components, including rotor blades, gearboxes, and other systems that must perform in large offshore wind plants. New size-enabling technologies will be required to push wind turbines beyond the scaling limits that constrain the current fleet. These technologies include lightweight composite materials and composite manufacturing, lightweight drivetrains, modular pole direct-drive generators, hybrid space frame towers, and large gearbox and bearing designs that are tolerant of slower speeds and larger scales. All of the weight- reducing features of the taller land-based tower systems will have an even greater value for very large offshore machines (Risø National Laboratory 2005).

RD&D Summary The advancement of offshore technology will require the development of infrastructure and technologies that are substantially different from those employed in land-based installations. In addition, these advances would need to be tailored to U.S. offshore requirements, which differ from those in the European North Sea environment. Government leadership could accelerate baseline research and technology development to demonstrate feasibility, mitigate risk, and reduce regulatory and environmental barriers. Private U.S. energy companies need to take the technical and financial steps to initiate near-term development of offshore wind power technologies and bring them to sufficient maturity for large-scale deployment. Musial (2007) and Bywaters and colleagues (2005) present more detailed analyses of actions for offshore development.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

159

2.6. Distributed Wind Technology

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Distributed wind technology (DWT) applications refer to turbine installations on the customer side of the utility meter. These machines range in size from less than 1 kW to multimegawatt, utility-scale machines used to offset electricity consumption at the retail rate. Because the WinDS deployment analysis does not currently segregate DWT from utility deployment, DWT applications are part of the land-based deployment estimates in the 20% wind energy scenario. Historically, DWT has been synonymous with small machines. The DWT market in the 1990s focused on battery charging for off-grid homes, remote telecommunications sites, and international village power applications. In 2000, the industry found a growing domestic market for behind-the-meter wind power, including small machines for residential and small farm applications and multimegawatt-scale machines for larger agricultural, commercial, industrial, and public facility applications. Although utility-scale DWT requirements are not distinguishable from those for other large-scale turbines, small machines have unique operating requirements that warrant further discussion.

2.6.1. Small Turbine Technology Until recently, three-bladed upwind designs using tail vanes for passive yaw control dominated small wind turbine technology rated at less than 10 kW. Furling, or turning the machine sideways to the wind with a mechanical linkage, was almost universally used for rotor overspeed control. The drivetrains were direct-drive, permanent-magnet alternators with variable-speed operation. Many of these installations were isolated from the grid. Today, there is an emerging technology trend toward grid-connected applications and nonfurling designs. U.S. manufacturers are world leaders in small wind systems rated at 100 kW or less, in terms of both market and technology. Turbine technology begins the transition from small to large systems between 20 kW and 100 kW. Bergey Windpower (Norman, Oklahoma) offers a 50-kW turbine that uses technology commonly found in smaller machines, including furling; pultruded blades; a direct-drive, permanent-magnet alternator; and a tail vane for yaw control. Distributed Energy Systems has a 1 00-kW turbine that uses a direct- drive, variable-speed synchronous generator. Although most wind turbines in the 100-kW range have features common to utility-scale turbines, including gearboxes, mechanical brakes, induction generators, and upwind rotors with active yaw control, Endurance Windpower (Spanish Fork, Utah) has a 4kW machine with such characteristics. Reliability and acoustic emissions are the prominent issues for small DWT applications. These installations usually consist of single machines that are widely scattered, requiring simplicity in design, ease of repair, and long maintenance and inspection intervals. Because DWT applications are usually close to workplaces or residences, limiting sound emissions is critical for market acceptance and zoning approvals. DWT applications are also usually located in areas with low wind speeds that are unsuitable for utility-scale applications, so DWT places a premium on lowwind-speed technologies. The cost of DWT turbines per kilowatt scales inversely with turbine size. Small- scale DWT installation costs are always higher than those for utility-scale installations because the construction effort cannot be amortized over a large number of machines. For a 1-kW system, hardware costs alone can be as high as $5,000 to $7,000/kW. Installation costs vary widely

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

160

U.S. Department of Energy

because of site-specific factors such as zoning and/or permitting costs, interconnection fees, balance-of-station costs, shipping, and the extent of do-it-yourself participation. Five-year warranties are now the industry standard for small wind turbines, although it is not yet known how this contributes to turbine cost. The higher costs of this technology are partially offset by the ability of these applications to compete with retail electricity rates. In addition, the use of small turbines makes connection to the electric distribution system possible, eliminating the need for an expensive interconnection between the substation and the transmission. Tower and foundation costs make up a larger portion of DWT installed cost, especially for wind turbines of less than 20 kW. Unlike utility-scale turbines that commonly use tapered tubular steel towers, multiple types, sources, and heights of towers are available for small wind turbines.

2.6.2. Technology Trends Recent significant developments in DWT systems less than 20 kW include the following: •

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

•

•

•

•

Alternative power and load control strategies: Furling inherently increases sound levels because the cross-wind operation creates a helicopter-type chopping noise. Aerodynamic models available today cannot accurately predict the rotor loads in the highly skewed and unsteady flows that occur during the furling process, complicating design and analysis. Alternative development approaches include soft-stall rotorspeed control, constant-speed operation, variable-pitch blades, hinged blades, mechanical brakes, and centrifugally actuated blade tips. These concepts offer safer, quieter turbines that respond more predictably to high winds, gusts, and sudden wind direction changes. Advanced blade manufacturing methods: Blades for small turbines have been made primarily via hand lay-up manufacturing of fiberglass or pultrusion. The industry is now pursuing alternative manufacturing techniques, including injection, compression, and reaction injection molding. Advantages such as shorter fabrication time, lower parts costs, and increased repeatability and uniformity are often achieved using these methods, although the tooling costs are typically higher. Rare-earth permanent magnets: Ferrite magnets have long been the staple in permanent-magnet generators for small wind turbines. Rare-earth permanent magnets are now taking over the market with Asian suppliers offering superior magnetic properties and a steady decline in price. The result is more compact and lighter weight generator designs. Reduced generator cogging: Concepts for generators with reduced cogging torque (the force needed to initiate generator rotation) are showing promise to reduce cut-in wind speeds, an important characteristic for enhancing low-wind-speed turbine performance. Induction generators: Small turbine designs that use induction generators are under development. This approach, common in the early 1980s, avoids the use of power electronics that increase cost and complexity and reduce reliability. Grid-connected inverters: Inverters used in the photovoltaics market are being adapted for use with wind turbines. Turbine- specific inverters are also appearing in both single- and three-phase configurations. Another new trend is obtaining

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

• •

161

certification of most inverters by Underwriters Laboratories and others for compliance with national interconnection standards. Reduced rotor speeds: To reduce sound emissions, turbine designs with lower tipspeed ratios and lower peak-rotor speeds are being pursued. Design standards and certification: The industry is increasing the use of consensus standards in its turbine design efforts for machines with rotor swept areas under 200 square meters (m2; about 65 kW rated power). In particular, IEC Standard 61400-2 Wind Turbines – Part 2: Design Requirements of Small Wind Turbines. Currently, however, a limited number of wind turbines have been certified in compliance with this standard because of the high cost of the certification process. To address this barrier, a Small Wind Certification Council has been formed in North America to certify that small wind turbines meet the requirements of the draft AWEA standard that is based on the IEC standard (AWEA 1997–2006).

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

2.7. Summary of Wind Technology Development Needs Wind technology must continue to evolve if wind power is to contribute more than a few percentage points of total U.S. electrical demand. Fortunately, no major technology breakthroughs in land-based wind technology are needed to enable a broad geographic penetration of wind power into the electric grid. However, there are other substantial challenges (such as transmission and siting) as well as significant costs associated with increased penetration that are discussed in other sections of this report. No single component improvement in cost or efficiency can achieve the cost reductions or improved capacity factor that system-level advances can achieve. The wind capacity factor can be increased by enlarging rotors and installing them on taller towers. This would require advanced materials, controls, and power systems that can significantly reduce the weight of major components. Capital costs would also be brought down by the manufacturing learning curve that is associated with continued technology advancement and by a nearly fivefold doubling of installed capacity. The technology development required to make offshore wind a viable option poses a substantial potential risk. Offshore wind deployment represents a significant fraction of the total wind deployment necessary for 20% wind energy by 2030. Today’s European shallowwater technology is still too expensive and difficult to site in U.S. waters. Deepwater deployment would eliminate visual esthetics concerns, but the necessary technologies have yet to be developed, and the potential environmental impacts have yet to be evaluated. Work is needed on analysis methods, evaluating technology pathways, and fielding offshore prototypes to establish the offshore option.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

162

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 2.17. Types of repairs on wind turbines from 2.5 kW to 1.5 MW.

Today’s market success is the product of a combination of technology achievement and supportive public policy. A 20% Wind Scenario would require additional land-based technology improvements and a substantial development of offshore technology. The needed cost and performance improvements could be achieved with innovative changes in existing architectures that incorporate novel advances in materials, design approaches, control strategies, and manufacturing processes. Risks are mitigated with standards that produce reliable equipment and full-scale testing that ensures the machinery meets the design requirements.

Fostering the Introduction of Technology Improvements The 20% Wind Scenario assumes a robust technology that will produce cost- competitive generation without preferential tax subsidies. Areas where industry can focus RD&D efforts include those which require the most frequent repairs (see Figure 2.17). Increasing the capacity factors by placing larger rotors on taller towers (this can be achieved economically only by using lighter components and load-mitigating rotors that reduce the integrated tower-top mass and structural loads; reducing parasitic losses throughout the system can also make gains possible), and developing advanced controls and improved power systems. Reducing the capital cost with steady learning-curve improvements driven by innovative manufacturing improvements and a nearly fivefold doubling of installed capacity

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

163

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

2.8. References and other Suggested Reading Antoniou, I., H.E. Jørgensen, T. Mikkelsen, S. Frandsen, R. Barthelmie, C. Perstrup, and M. Hurtig. 2006. “Offshore Wind Profile Measurements from Remote Sensing Instruments.” Presented at the European Wind Energy Conference, February 27–March 2, Athens, Greece. Ashwill, T. 2004. Innovative Design Approaches for Large Wind Turbine Blades: Final Report. Report No. SAND2004-0074. Albuquerque, NM: Sandia National Laboratories. AWEA (American Wind Energy Association). 1996–2007. IEC Wind Turbine Standards. http://www.awea.org/standards/iec_stds.html#WG4. Behnke, Erdman, and Whitaker Engineering (BEW Engineering). 2006. Low Wind Speed Technology Phase II: Investigation of the Application of Medium- Voltage VariableSpeed Drive Technology to Improve the Cost of Energy from Low Wind Speed Turbines. Report No. FS-500-37950, DOE/GO 102006-2208. Golden, CO: National Renewable Energy Laboratory (NREL). http://www.nrel.gov/docs/fy06osti/37950.pdf. Bossanyi, E.A. 2003. “Individual Blade Pitch Control for Load Reduction,” Wind Energy, 6(2): 119–128. Brown, A. 2007. “Very Light and Fast.” Mechanical Engineering, January. http://www. memagazine.org/jan07/features/verylight/verylight.html. BSH (Bundesamt für Seeschifffahrt und Hydrographie.). Wind Farms. http://www. bsh.de/en/Marine%20uses/Industry/Wind%20farms/index.jsp. BTM Consult. 2005. World Market Update 2005. Ringkøbing, Denmark: BTM Consult ApS. http://www.btm.dk/Pages/wmu.htm. BWEA (British Wind Energy Association). “Offshore Wind.” http://www.bwea.com/ offshore/info.html. Bywaters, G., V. John, J. Lynch, P. Mattila, G. Norton, J. Stowell, M. Salata, O. Labath, A. Chertok, and D. Hablanian. 2005. Northern Power Systems WindPA CT Drive Train Alternative Design Study Report; Period of Performance: April 12, 2001 to January 31, 2005. Report No. SR-500 35524. Golden, CO: NREL. http://www.nrel.gov/publications/ Cohen, J., T. Schweizer, A. Laxson, S. Butterfield, S. Schreck, L. Fingersh, P. Veers, and T. Ashwill. 2008. Technology Improvement Opportunities for Low Wind Speed Turbines and Implications for Cost of Energy Reduction. Report No. NREL/SR-500-4 1036. Golden, CO: NREL. Cotrell, J., W.D. Musial, and S. Hughes. 2006. The Necessity and Requirements of a Collaborative Effort to Develop a Large Wind Turbine Blade Test Facility in North America. Report No. TP-500-38044. Golden, CO: NREL Dhanju A., P. Whitaker, and W. Kempton. 2006. “Assessing Offshore Wind Resources: A Methodology Applied to Delaware.” Presented at the AWEA Conference & Exhibition, June 4–7, Pittsburgh, PA. DOE (U.S. Department of Energy). 2000. World’s Most Advanced Gas Turbine Ready to Cross Commercial Threshold. Washington, DC: DOE. http://www.fossil.energy. gov/news/techlines/2000/tl ats ge1.html. EIA (Energy Information Administration). 2006. “State Electricity Sales Spreadsheet.” http://www.eia.doe.gov/cneaf/electricity/epa/sales state.xls.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

164

U.S. Department of Energy

EUI (Energy Unlimited Inc.). 2003. Variable Length Wind Turbine Blade. Report No. DEFG36-03GO13 171. Boise, ID: EUI. http://www.osti.gov/bridge/servlets/purl/841190OF8Frc/ Griffin, D.A. 2001. WindPACT Turbine Design Scaling Studies Technical Area 1 – Composite Blades for 80- to 120-Meter Rotor. Report No. SR-500 29492.Golden, CO: NREL. Hasager, C.B., M.B. Christiansen, M. Nielsen, and R. Barthelmie. 2005. “Using Satellite Data for Mapping Offshore Wind Resources and Wakes.” Presented at the Copenhagen Offshore Wind Proceedings, October 26–28, Copenhagen, Denmark. IEC (International Electrotechnical Commission). 2007. “Technical Committee 88: Wind turbines, Standards 61400-x.” http://nettedautomation.com/standardization/IEC_TC88/ index.html ISET (Institut fuer Solare Energieversorgungstechnik). 2003. Experience Curves: A tool for Energy Policy Programmes Assessment (EXTOOL). Lund, Sweden: ISET. http://www. iset.uni-kassel.de/extool/Extoolframe.htm. Jimenez, B., F. Durante, B. Lange, T. Kreutzer, and L. Claveri. 2005. “Offshore Wind Resource Assessment: Comparative Study between MM5 and WAsP.” Presented at the Copenhagen Offshore Wind Proceedings, October 26–28, Copenhagen, Denmark. Knight, S., and L. Harrison. 2005. “A More Conservative Approach.” Windpower Monthly, November. Kühn, P. 2006. “Big Experience with Small Wind Turbines (SWT).” Presented at the 49th IEA Topical Expert Meeting, September, Stockholm, Sweden. Lindvig, K. 2005. “Future Challenges for a Marine Installation Company.” Presented at the Copenhagen Offshore Wind Proceedings, October 26–28, Copenhagen, Denmark. MMS (Minerals Management Service). Alternative Energy and Alternate Use Program. http:// www.mms.gov/offshore/RenewableEnergy/RenewableEnergyMain.ht m. Musial, W. 2007. “Offshore Wind Electricity: A Viable Energy Option for the Coastal United States.” Marine Technology Society Journal, 42 (3), 32-43. Northern Power Systems. 2006. Low Wind Speed Technology Phase I: Advanced Power Electronics for Low Wind Speed Turbine Applications. Report No. FS-500-37945, DOE/GO-102006-2205. Golden, CO: NREL. http://www.nrel.gov/docs/fy06osti/ 37945.pdf. NREL. 2002. Addendum to WindPACT Turbine Design Scaling Studies Technical Area 3 – Self-Erecting Tower and Nacelle Feasibility: Report No. SR-5 00 29493-A. Golden, CO: NREL. O'Connell, R., and R. Pletka, et al. 2007. 20 % Wind Energy Penetration in the United States: A Technical Analysis of the Energy Resource. Overland Park, KS: Black & Veatch. Pace Global Energy Services, Aug. 2007, Assessment of Offshore Wind Power Resources, http://www.lipower.org/newscenter/pr/2007/pace_wind.pdf Peregrine Power. 2006. Low Wind Speed Technology Phase II: Breakthrough in Power Electronics from Silicon Carbide. Report No. FS-500-37943, DOE/GO-102006-2203. Golden, CO: NREL. http://www.nrel.gov/docs/fy06osti/37943.pdf Poulsen, S.F., and P.S. Skjærbæk. 2005. “Efficient Installation of Offshore Wind Turbines: Lessons Learned from Nysted Offshore Wind Farm.” Presented at the Copenhagen Offshore Wind Proceedings, October 26–28, Copenhagen, Denmark.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

165

Risø National Laboratory. 2005. Association Euratom - Risø National Laboratory Annual Progress Report 2005. Report No. Risø-R- 1 579(EN). Roskilde, Denmark: Risø National Laboratory. http://www.risoe.dk/rispubl/ofd/ofdpdf/ris-r-1579.pdf. SEAWIND, Altener Project, 2003. (Per Nielsen) “Offshore Wind Energy Projects Feasibility Study Guidelines,” Denmark. Stiesdal, H., and P.H. Madsen. 2005. “Design for Reliability.” Presented at the Copenhagen Offshore Wind Proceedings, October 26–28, Copenhagen, Denmark. Walford, C.A. 2006. Wind Turbine Reliability: Understanding and Minimizing Wind Turbine Operation and Maintenance Costs. Report No. SAND2006-1 100. Albuquerque, NM: Sandia National Laboratories. Wiser, R., and M. Bolinger. 2007. Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2006. DOE/GO–102007-2433. Golden, CO: NREL. http://www. osti.gov/bridge/product.biblio.jsp?query_id=0&page=0&osti_id =908214

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

SECTION 3. MANUFACTURING, MATERIAL AND RESOURCES Stakeholders and decision makers need to know whether a generation mix of 20% wind energy by 2030 might be constrained by raw materials availability, manufacturing capability, or labor availability. This section examines the adequacy of these critical resources. Over the past five years, the wind industry in the United States has grown by an average of 22% annually. In 2006 alone, America’s wind power generating capacity increased by 27%. The U.S. wind energy industry invested approximately $4 billion in 2,454 megawatts (MW) of new generating capacity in 2006, making wind the second largest source of new power generation in the nation—surpassed only by natural gas—for the second year in a row. Recently installed wind farms increased cumulative installed U.S. wind energy capacity to 13,884 MW—well above the 10,000 MW milestone reached in August 2006 (AWEA 2007). On average, 1 MW of wind power produces enough electricity to power 250 to 300 U.S. homes. Based on estimates released by the U.S. Department of Energy (DOE) Energy Information Administration (EIA 2006), annual electricity consumption in the United States is expected to grow at a rate of 1.3% annually—from 3.899 billion megawatt-hours (MWh) in 2006 to about 5.368 billion MWh in 2030. Although wind energy supplied approximately 0.8% of total electricity in 2006, more and larger wind turbines can help to meet a growing demand for electricity. (See the Glossary in Appendix E for explanations of wind energy capacity and measurement units.) The most common large turbines currently in use have a rated capacity of between 1 MW and 3 MW, with rotor diameters between 60 meters (m) and 90 m, tower heights between 60 m and 100 m, and capacity factors between 30% and 40% (capacity factor is an indicator of annual energy production). Although currently installed machines are expected to operate through 2030, larger turbines (with capacity factors that increase over time, as discussed in Section 2) are expected to become more common as offshore technology advances are transferred to land- based turbines. These larger turbines could reach rated power between 4 MW and 6 MW and capacity factors between 40% and 50%.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

166

U.S. Department of Energy

For the purpose of estimating the raw materials and investment effort needed to support the required level of wind penetration in the 20% Wind Scenario, industry leaders have assumed that most of the wind turbines used in the next two to three decades will be in the 1MW to 3-MW class, with a modest contribution of the larger-sized machines (see Section 2). Today, approximately 2,000 turbines are installed each year, but that figure is expected to rise and to level out at about 7,000 turbines per year by 2017.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

3.1. Raw Materials Requirements Wind turbines are built in many sizes and configurations, with a wide range of materials used in manufacturing large turbines. Reducing the weight and cost of the turbines is the key to making wind energy competitive with other power sources, and several research programs have significantly improved the efficiency of current machines. Throughout the next few decades, business opportunities are expected to expand in wind turbine components and materials manufacturing. To reach the high levels of wind energy associated with the 20% Wind Scenario, materials usage will also need to increase considerably, even as new technologies that improve component performance are introduced. To estimate the raw materials required for the 20% Wind Scenario, this analysis focuses on the most important materials used in building a wind turbine today (such as steel and aluminum) and on main turbine components. Table 3.1 shows the percentage of different materials used in each component and each component’s percentage of total turbine weight. The table applies to turbines in the 1.5-MW class, as well as to larger turbines of 4 MW or more. Using the materials consumption model in Table 3.1 as a basis, Table 3.2 further describes the raw materials required to reach manufacturing levels of about 7,000 turbines per year. This analysis assumes that turbines will become lighter and annual installation rates will level off to roughly 7,000 turbines per year by 2017 and continue at that rate through 2030. Approximately 100,000 turbines will be required to produce 20% of the nation’s electricity in 2030. No single component dominates a wind turbine’s total cost, which is generally split evenly among the rotor, electrical system, drivetrain, and tower. The technological progress described in Section 2, however, could significantly reduce costs (e.g., through the use of lighter weight components for blades and towers). The availability of critical resources is crucial for large-scale manufacturing of wind turbines. The most important resources are steel, fiberglass, resins (for composites and adhesives), blade core materials, permanent magnets, and copper. The production status of these materials is reviewed in the following list: •

Steel: The steel needed for additional wind turbines is not expected to have a significant impact on total steel production. (In 2005, the United States produced 93.9 million metric tons of steel, or 8% of the worldwide total.) Although steel will be required for any electricity generation technology installed over the next several decades, it can be recycled. As a result, replacing a turbine after 20+ years of service would not significantly affect the national steel demand because recycled steel can be

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

167

used in other applications for which high-quality steel is not a requirement (Laxson, Hand, and Blair 2006). Fiberglass: Additional fiberglass furnaces would be needed to build more wind turbines. Primary raw materials for fiberglass (sand) are in ample supply, but availability and costs are expected to fluctuate for resins, adhesives, and cores made from the petroleum-based chemicals that are used to impregnate the fiberglass (Laxson, Hand, and Blair 2006).

•

Table 3.1. Main components and materials used in a wind turbine (%) 1.5 MW

Weight %

Permanent ConMagnet crete

Steel

Aluminum

Copper

GRP

CRP

Adhesive

Core

15

5

Total

Rotor Hub

6.0

100

Blades

7.2

2

10.1

96

100.0 78

100.0

Nacelle Gearbox Generator

3.4

65

Frame

6.6

85

Tower

66.7 100.0

4 MW

2 0.0

1.3

Permanent ConMagnet crete

2

2

9

3

100.0

35

100.0 3

100.0

98 89.1

0.8

1.6

5.8

0.0

1.1

0.4

Steel

Aluminum

Copper

GRP

CRP

Adhesive

Core

100.0

Rotor Hub

6.00

100

Blades

7.6

2

10.10

96

100.0 68

10

15

5

100.0

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Nacelle Gearbox Generator

2.7

Frame

6.60

Tower

3

0.08

2

9

3

3

0.80

0.51

5.37

93

100.0

4

85

67.00 100.0

2

2

98

1.34

89.63

100.0 100.0 0.76

1.14

0.38

100.0

Notes: Tower includes foundation. GRP = glass-fiber-reinforced plastic. CRP = carbon fiber reinforced plastic Source: Sterzinger and Svrcek (2004).

Table 3.2. Yearly raw materials estimate (thousands of metric tons) Year

kWh/kg

2006 2010 2015 2020 2025 2030

65 70 75 80 85 90

Permanent Magnet 0.03 0.07 0.96 2.20 2.10 2.00

Concrete 1,614 6,798 16,150 37,468 35,180 33,800

Steel 110 464 1,188 2,644 2,544 2,308

Aluminum 1.2 4.6 15.4 29.6 27.8 26.4

Copper

GRP

CRP

1.6 7.4 10.2 20.2 19.4 18.4

7.1 29.8 73.8 162.2 156.2 152.4

0.2 2.2 9.0 20.4 19.2 18.4

Adhesive 1.4 5.6 15.0 33.6 31.4 30.2

Core 0.4 1.8 5.0 11.2 10.4 9.6

Notes: kg = kilograms; GRP = glass-fiber-reinforced plastic. CRP = carbon fiber reinforced plastic Source: Sterzinger and Svrcek (2004). Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

168

U.S. Department of Energy •

•

•

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

Core: End-grain balsa wood is an alternative core material that can replace the lowdensity polymer foam used in blade construction. Availability of this wood might be an issue based on the growth rate of balsa trees relative to the projected high demand. Carbon fiber: Current global production of commercial-grade carbon fiber is approximately 50 million pounds (lb) per year. The use of carbon fiber in turbine blades in 2030 alone would nearly double this demand. To achieve such drastic industry scale-up, changes to carbon fiber production technologies, production facilities, packaging, and emissions-control procedures will be required. Permanent magnets: By eliminating copper from the generator rotor and using permanent magnets, which are becoming more economically feasible, it is possible to build smaller and lighter generators. World magnet production in 2005 was about 40,000 metric tons, with about 35,000 metric tons produced in China. Although supply is not expected to be restricted, significant additions to the manufacturing capability would be required to meet the demand for wind turbines and other products (Trout 2002; Laxson, Hand, and Blair 2006). Copper: Although wind turbines use significant amounts of copper, the associated level of demand still equates to less than 4% of the available copper. This demand level, then, would not have a significant impact on national demand (U.S. refined copper consumption was 2.27 million metric tons in 2005). Although copper ranks third after steel and aluminum in world metals consumption, global copper production is adequate to satisfy growing demands from the wind industry. Copper price escalation has exceeded inflation in recent years and could affect turbine costs.

Despite the demand and supply status of these materials, new component developments are expected to significantly change material usage patterns. Generally, trends are toward using lighter-weight materials, as long as the life-cycle costs are low. In addition to the findings of Ancona and McVeigh (2001; described in the Materials Usage Analysis sidebar), other trends in turbine components are outlined in the subsections that follow. Material Usage Analysis (Ancona and McVeigh 2001) • • • • • • • • •

Turbine material usage is, and will continue to be, dominated by steel. Opportunities exist for introducing aluminum or other lightweight composites, provided that cost, strength, and fatigue requirements can be met. GRP is expected to continue to be used for blades. The use of carbon fiber might help reduce weight and cost. Low costs and high reliability remain the primary drivers. Variable-speed generators will become more common. Permanent-magnet generators on larger turbines will increase the need for magnetic materials. Simplification of the nacelle machinery might reduce raw material costs and also increase reliability.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

169

Evolution of Rotors Most rotor blades in use today are built from glassfiber-reinforced plastic (GRP). Steel and various composites and carbon filament-reinforced plastic (CFRP) are also used. As the rotor size increases for larger machines, the trend will be toward high strength, fatigueresistant materials. Composites involving steel, GRP, CFRP, and possibly other new materials will likely come into use as turbine designs evolve. Changes to Machine Heads The machine head contains an array of complex machinery including yaw drives, bladepitch change mechanisms, drive brakes, shafts, bearings, oil pumps and coolers, controllers, a bedplate, the drivetrain, the gearbox, and an enclosure. Design simplifications and innovations are anticipated in each element of the machine head.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

3.2. Manufacturing Capability In principle, a sustainable level of annual wind turbine installation would be best supported by a substantial domestic manufacturing base. If installation rates fluctuate greatly from one year to the next, however, manufacturing capability may or may not be able to grow or shrink as necessary. The National Renewable Energy Laboratory (NREL) created a simple model to explore sustainable installation rates that would maintain wind energy production at specific levels spanning several decades (Laxson, Hand, and Blair 2006). The NREL study explored a number of alternative scenarios for annual wind power capacity expansion to understand their potential impact on wind energy installation and manufacturing rates. The results indicate that achieving the 20% Wind Scenario by 2030 is possible without overwhelming the ability of U.S. industry to meet those demands (Laxson, Hand, and Blair 2006). NREL’s study assessed potential barriers that would prohibit near-term high wind penetration levels, such as manufacturing rates or resource limitations. To reach 20% electric generation from wind by 2030 in the United States, the authors noted, an annual installed capacity increase of about 20% would need to be sustained for a decade (Laxson, Hand, and Blair 2006). Figure 3.1 shows a comparison of three models for the installation rates required to meet three energy supply goals of 10%, 20%, and 30% of total national electrical energy production from wind by 2030. Figure 3.1(a) shows the annual rates and Figure 3.1(b). shows the cumulative capacity attained in each case. A manufacturing production level of 20 gigawatts (GW) per year by 201 7—and maintained at this value thereafter—would reach levels close to 400 GW of wind energy capacity by 2030. The NREL study assumed that the wind plant capacity factor would not change from year to year or from location to location, providing an upper bound on the annual installation rate and cumulative capacity required to produce 20% of electricity demand. Alternatively, the 20% Wind Scenario evaluation assumes that plant capacity factors will increase modestly with experience and technology improvements (see Section 2). The 20% scenario also accounts for regional variations in wind resources, as explained in Appendix A’s detailed description of the analytic modeling approach employed. Note that when these refinements

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

170

U.S. Department of Energy

are included, the 20% curve in Figure 3.1(a) shifts downward, somewhat similar to that shown in Figure 3.2. This section discusses the materials and manufacturing needed to pursue 20% wind energy from 2007 through 2030 to meet the annual and cumulative installed capacity shown in Figure 3.2. This figure shows the forecasts for annual and cumulative installed wind energy capacity, which also forms the basis for estimates of new wind turbines and the raw materials required to produce them. In this scenario, annual installations climb to more than 16 GW per year, and the total installed wind capacity increases to 305 GW by 2030. Between 2007 and 2030, 293 GW are installed. (For more details on the modeling approach used, see Appendix A.)

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

a

b Figure 3.1. a. Annual installed wind energy capacity to meet 20% of energy demand. b. Cumulative installed wind energy capacity to meet 20% of energy demand.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

171

Figure 3.2. Annual and cumulative installed wind energy capacity represented in the 20% Wind Scenario.

3.2.1. Current Manufacturing Facilities A growing number of states and companies in the United States are ramping up capacity to manufacture wind turbines, or have the ability to do so. Jobs are expected to remain in the U.S. if investments are made in certain components and in advanced manufacturing technologies.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table 3.3. Locations of U.S. wind turbine component manufacturers Region

Division

Midwest East North Central West North Central Northeast Middle Atlantic New England South East South Central South Atlantic West South Central West Mountain Pacific Component Total:

Rotor

Generator & Power Electronics 1

Tower

Division Total

6

Nacelle Gearbox & and Drivetrain Controls 5 8

2

22

1

0

1

1

8

11

3 0 0

4 6 0

4 0 0

5 2 0

1 0 2

17 8 2

3 4

2 5

1 0

1 1

2 6

9 16

1 5 23

0 4 26

0 2 16

1 4 16

0 4 25

2 19 106

(Sterzinger and Svrcek 2004)

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

172

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

A useful perspective on growing manufacturing requirements is provided by a non government organization study released in 2004 called Wind Turbine Development: Location of Manufacturing Activity (Sterzinger and Svrcek 2004). This study investigated the current and future U.S. wind manufacturing industry, both to determine the location of companies involved in wind turbine production and to examine limitations to a rapidly expanding wind business. The report covered four census regions (the Midwest, Northeast, South, and West) and divided turbine manufacturing into 20 separate components. These components were grouped into five categories, as shown in Table 3.1. The table also shows the locations of U.S. wind turbine component manufacturers in 2004, broken down by region. Among the 106 companies surveyed, about 90 companies directly manufacture components for utility-scale wind turbines, with utility scale being roughly defined as 1 MW or greater.

Figure 3.3. Examples of manufacturers supplying wind equipment across the United States.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

173

Table 3.4. U.S. Manufacturing firms with technical potential to enter wind turbine component market NAICS Code

Code Description

Total Employees

326199 331511 332312 332991 333412

All Other Plastics Products Iron Foundries Fabricated Structural Metal Ball and Roller Bearings Industrial and Commercial Fans and Blowers Turbines, and Turbine Generators, and Turbine Generator Sets Speed Changer, Industrial Power Transmission Equip. Printed Circuits and Electronics Assemblies Measuring and Controlling Devices Motors and Generators Electronic Equipment and Components, NEC

333611 333612 333613 334418 334519 335312 335999

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Total

501,009 75,053 106,161 33,416 11,854

Annual Payroll ($1000s) 15,219,355 3,099,509 3,975,751 1,353,832 411,979

8,174 747 3,033 198 177

17,721

1,080,891

110

13,991 21,103 105,810 34,499 62,164 42,546

539,514 779,730 4,005,786 1,638,072 2,005,414 1,780,246

248 292 716 830 659 979

1,025,327

35,890,079

16,163

Number of Companie

Figure 3.3 shows the locations of a number of the current manufacturers of wind turbines and components. These firms are widely distributed around the country and some are located in regions with, as yet, little wind power development. A large national investment in wind would likely spread beyond these active companies. To identify this potential, the North American Industrial Classification System (NAICS; http://www.census.gov/epcd/www/naics.html) was searched to identify companies operating under relevant industry codes. The manufacturing activity related to wind power development is substantial and widely dispersed (Sterzinger and Svrcek 2004). As shown in Table 3.4, more than 16,000 firms are currently producing products under one or more of the NAICS codes that include manufacture of wind components. These firms are spread across all 50 states. They are concentrated, however, in the most populous states and the states that have suffered the most from loss of manufacturing jobs. The 20 states that would likely receive the most investment and the most new manufacturing jobs from wind power expansion account for 75% of the total U.S. population, and 76% of the manufacturing jobs lost in the last 3.5 years. A 2006 NGO report entitled “Renewable Energy Potential: A Case Study of Pennsylvania (Sterzinger and Stevens 2006) identified the bottlenecks in the component supply chain. Bottlenecks were identified for various components, but obtaining gearbox components was particularly problematic. Currently, only a few manufacturers in the world deliver gearboxes for large wind turbines. To sustain a growing number of wind installations, additional investment must be in place to support the development of a gearbox industry focused on wind applications. The manufacture of large bearings—as well as the number of large castings suppliers— will also need to expand.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

174

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The wind equipment manufacturing sector also faces trade-offs between using domestic or foreign manufacturing facilities. An advantage to U.S.-based operations is a reduction in the often significant transportation cost of moving large components such as blades and towers. Manufacturing many significant wind turbine components is also a labor-intensive process. With U.S. labor wage rates at higher levels than those paid in many other countries, manufacturers have naturally been drawn to setting up their factories outside the United States (e.g., in Mexico and China). One wind blade manufacturer with significant international manufacturing experience estimates that, to make a U.S. factory competitive, the labor hours per blade would need to be reduced by a factor of 30%–35%. To ensure that the bulk of these manufacturing jobs stay in the United States, automation and productivity gains through the development of advanced manufacturing technology are needed. These gains will allow the higher U.S. wage rates to be competitive. To attract these jobs, a number of U.S. states have set aside funds for RD&D, with plans to collaborate with industry and the federal government on a cost-shared basis. Collaboration among state, industry, and federal programs in advanced manufacturing can create competitive U.S. factories with U.S. employees whose jobs will remain secure for a long time.

3.2.2. Ramping up Energy Industries In the United States, several industries have experienced large rates of growth over a short period of time. The power plants most commonly used to produce electricity around the world are large in scale, such as thermal power stations fired with coal, gas or oil, or nuclear reactors. Nuclear power stations have been developed mainly since the middle of the twentieth century and have now reached a penetration of 17.1% in the world’s power supply. Worldwide, nuclear power plant installations saw a 17% annual growth rate between 1960 and 1997 (BTM 1999). In the United States, despite a halt in new nuclear plant licensing in the early 1980s, nuclear plants generate about 20% of the nation’s electrical energy, and have done so for the last decade or more. The history of nuclear power shows that it is possible to achieve substantial levels of penetration with a new technology over two to three decades. Even though the time horizon of the 20% Wind Scenario is consistent with the historical development of nuclear power, it is nonetheless difficult to directly compare penetration patterns for nuclear power and wind technology. Wind power is a smaller scale technology, with a current typical commercial unit size of 2 MW–3 MW compared to a typical 1,000-MW nuclear plant. Despite the smaller scales of wind power, its modularity makes it ideal for all sizes of installations—from a single unit (2 MW–3 MW) to a huge wind farm (1,000 MW). On the supply side, serial production of large numbers of similar units can reduce manufacturing costs. These factors suggest that manufacturing ramp-up for wind turbines should be less daunting than ramp-up for nuclear power plant equipment. Experiences with natural-gas-fired power plants over the past decade also provide important perspectives on the ability to rapidly expand manufacturing capability for wind power. From the early 1 990s through the first half of the current decade, the U.S. electric sector experienced a rush toward new gas combined-cycle and combustion-turbine generation. This growth was driven by the expectation—now discounted—of continuing low natural gas prices. From 1999 through 2005, tens of gigawatts of natural gas power plants were manufactured and installed in the United States each year, with installations peaking in 2002 at more than 60 GW (Black and Veatch, forthcoming 2008). The experience with

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

175

natural gas demonstrates that huge amounts of power generation equipment can be manufactured in the United States if sufficient market demand exists. As shown in Table 3.3, Toyota North America exemplifies the manufacturing scale up of a modular technology and capability that is possible in the United States. Toyota has continued to establish its U.S. manufacturing capability since the mid 1980s, and automobiles, like wind turbines, require large quantities of steel, plastics, and electronic components. There is no indication that Toyota’s domestic expansion has caused any strain on the nation’s manufacturing or materials-supply sectors. Today, the majority of vehicles Toyota sells in the United States are actually produced in this country. Table 3.3 shows that Toyota’s annual U.S. production, when expressed in terms of engine power output, increased to 236 GW by 2005. This annual production begins to approach in power capability the total amount of wind generation installed between 2007 and 2030 through realization of the 20% Wind Scenario.

3.3. Labor Requirements

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Beyond the raw material and manufacturing facilities required to create wind turbines and components, a skilled labor force would be required. These staff would need a range of skills and experience to fill many new employment opportunities. The likely outcome from developing new capabilities and capacity would be expansion of manufacturing in areas currently capable of competing or locations where logistic advantages exist.

3.3.1. Maintaining and Expanding Relevant Technical Strength Major expansion of wind power in the United States would require substantial numbers of skilled personnel available to design, build, operate, maintain, and advance wind power equipment and technology. Toward this end, a number of educational programs are already offered around the nation, including those shown in Table 3.6. Table 3.5. Toyota North America vehicle production and sales Direct U.S. Employment (2005)

32,003 employees

2005 Payroll

$2,244,946,444

Cumulative U.S. Production

12,374,062 vehicles

Cumulative Sales

$272,390,226,806

U.S. Vehicle Sales (2005)

2,269,296 vehicles

U.S. Vehicle Production (2005)

1,393,100 vehicles

Average Engine Power 2004-2005 2005 U.S. Production in Power Output Terms

227 horsepower or 0.17 MW 275 million horsepower 236 million kW or 236 GW 448 million horsepower 384 million kW or 384 GW

2005 U.S. Sales in Power Output Terms

Source: Adapted from website data. http://www.toyota.com/about/operations/manufacturing/

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

176

U.S. Department of Energy

Although this is an excellent beginning, many more programs of a similar nature will be needed nationwide to satisfy the needs stemming from the 20% Wind Scenario. One concern is that the number of students in power engineering programs has been dropping in recent years. Currently, U.S. graduate power engineering programs produce about 500 engineers per year; in the 1980s, this number approached 2,000. In addition, the number of wind engineering programs in U.S. graduate schools is significantly lower than in Europe. This concern is echoed in Figure 3.4, which shows that the number of college graduates receiving degrees in science and engineering has been declining, and that this trend is projected to continue for the foreseeable future (NSTC 2000).

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table 3.6. Wind technology-related educational programs around the United States today School Wind Energy Applications Training Symposium Colorado State University

Location Boulder, Colorado

Degree or Program Workshops for Industry

Fort Collins, Colorado

Advanced Technology Environmental Education Center: Sustainable Energy Education and Training Iowa Lakes Community College

Bettencourt, Iowa

65-MW turbine on campus for research (engineering, environmental, etc.) Workshops for upper level high school and community college technology instructors

University of Massachusetts at Amherst: College of Engineering, and Renewable Energy Research Laboratory (becoming University of Massachusetts Wind Energy Center in late 2008) Minnesota West Community and Technical College

Amherst, Massachusetts

Southwestern Indian Polytechnic Institute

Albuquerque, New Mexico

Estherville, Iowa

Canby, Maine

One-year diploma for wind technician; two-year associate in applied science degree for wind technician MS and Ph.D. level engineering programs specializing in wind energy

Associate of applied science degree program in wind energy technology; diploma for wind energy mechanic; online certificate program for ”windsmith” Under development: Integration of renewable energy technology experiential learning into the electronics technology, environmental science, agricultural science, and natural resources certificate and degree programs

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030 Mesalands Community College: North American Wind Research and Training Center

Tucumcari, New Mexico

Wayne Technical and Career Center Columbia Gorge Community College

Williamson, New York Hood River, Oregon

Lane Community College

Eugene, Oregon

Texas Tech and other American universities: Wind Science & Engineering Research Center Lakeshore Technical College

Lubbock, Texas

Fond du Lac Tribal and Community College

Fond du Lac, Wisconsin

Under development: Curriculum for operations and maintenance technician; two-year associate degree in wind farm management New Vision Renewable Energy Program for high school seniors One-year certificate and two-year degree for renewable energy technician Two-year associate of applied science degree for energy management technician; two-year associate of applied science option for renewable energy technician Integrative graduate education and research traineeship Associate degree in applied science; electromechanical technology with a wind system Technician track Clean Energy Technician Certificate Program

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Cleveland, Wisconsin

177

Figure 3.4. Percentage of 22-year-olds with a bachelor degree in science and engineering through 2050.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

178

U.S. Department of Energy

Even the level of U.S. graduate programs is well below similar graduate programs in Europe (Denmark, Germany, etc). At this rate, the United States will be unable to provide the necessary trained talent and manufacturing expertise. Unless this trend is reversed, despite major new wind installations in the United States, most of the technology will be imported, and a significant portion of the economic gains will be foreign, rather then domestic.

3.4. CHALLENGES TO 20% WIND ENERGY BY 2030 3.4.1. Challenges

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Materials Several key materials are crucial to the production of a wind turbine. Among the raw materials that might potentially constrain the ability to reach high levels of wind power are fiberglass (about 9 metric tons required per megawatt of wind turbine capacity), resins, and permanent magnets. For example, the glass fiber requirements would be about half the level used domestically for roofing shingles (which is currently the largest consumer of fiberglass) and about double the amount now used in boat building. Manufacturing The 20% Wind Scenario would demand installations at a sustained growth rate of 20% annually for nearly a decade and then maintain annual installations through 2030. For turbine companies, it is no longer simply a matter of where to establish new manufacturing capacity. Investment decisions must now address strategies for building out and securing supply lines on a global basis; a proactive stance is essential to operate successfully in an environment of rapidly growing and shifting demand for wind turbines (Hays, Robledo, and Ambrose 2006). Fortunately, the 20% Wind Scenario could be feasible even with the potential challenges related to the availability of raw material or increased manufacturing demands. For rapid growth of manufacturing capacity to be achieved, stable and consistent policies that encourage investment in these new sectors of activity are needed. Labor One potential gap in achieving high rates of wind energy development is the availability of a qualified work force. In a report published by the National Science and Technology Counsel (NTSC) in 2000, the percentage of 22-year-olds earning degrees in science and engineering will continue to drop in the next 40 years (NSTC 2000). More support from industry, trade organizations, and various levels of government could foster university programs in wind and renewable energy technology, preparing the work force to support the industry’s efforts.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

179

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

3.5. References and other Suggested Reading Ancona and McVeigh. 2001. Princeton Energy Resources International, LLC. Rockville, MD http://www.generalplastics.com/uploads/technology/WindTurbine MaterialsandManufacturing_FactSheet.pdf AWEA (American Wind Energy Association). 2007. Wind Power Capacity In U.S. Increased 27% in 2006 and Is Expected To Grow an Additional 26% in 2007. Washington, DC: AWEA. http://www.awea.org/newsroom/releases/Wind_Power_Capacity_012307.ht ml BTM Consult. 1999. Wind Force 10: A Blueprint to Achieve 10% of the World’s Electricity from Wind Power by 2010. Ringkøbing, Denmark: BTM Consult ApS. http://www. inforse.dk/doc/Windforce10.pdf EIA (Energy Information Administration). February 2006. Annual Energy Outlook 2006. Report No. DOE/EIA-0383.Washington, DC: EIA. Hays, K., C. Robledo, and W. Ambrose. 2006. Wind Power at a Crossroads, Supply Shortages Spark Industry Restructuring, Strategy White Paper. Cambridge, MA: Emerging Energy Research. Laxson, A., M.M. Hand, and N. Blair. 2006. High Wind Penetration Impact on W.S. Wind Manufacturing Capacity and Critical Resources. Report No. NREL/TP-500-40482. Golden, CO: National Renewable Energy Laboratory (NREL). NSTC (National Science and Technology Council). 2000. Ensuring a Strong U.S. Scientific, Technical and Engineering Workforce in the 21st Century. Washington, DC:NSTC. O’Connell, R., and R. Pletka, et al. 2007. 20% Wind Energy Penetration in the United States: A Technical Analysis of the Energy Resource. Overland Park, KS: Black & Veatch. Sterzinger, G., and M. Svrcek. September 2004. Wind Turbine Development: Location of Manufacturing Activity. Washington, DC: Renewable Energy Policy Project (REPP). Sterzinger, G., and M. Svrcek. 2005. Component Manufacturing: Ohio’s Future in the Renewable Energy Industry. Washington, DC: REPP. Sterzinger, G., and J. Stevens. October 2006. Renewable Energy Potential: A Case Study of Pennsylvania. Washington, DC: REPP. Trout, S.R. 2002. “Rare Earth Magnet Industry in the USA: Current Status and Future Trends.” Presented at the XVII Rare Earth Magnet Workshop, August 18–22, Newark, New Jersey.

SECTION 4. TRANSMISSION AND INTEGRATION INTO THE U.S. ELECTRIC SYSTEM The ever-increasing sophistication of the operation of the U.S. electric power system—if it continues on its current path—would allow the 20% wind energy scenario to be realized by 2030. The 20% Wind Scenario would require the continuing evolution of transmission planning and system operations, in addition to expanded electricity markets. There are two separate and distinct power system challenges to obtaining 20% of U.S. electric energy from wind. One challenge lies in reliably balancing electrical generation and load over time with a large portion of energy coming from a variable power source such as

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

180

U.S. Department of Energy

wind, which, unlike many traditional power sources, cannot be accessed on demand or is “nondispatchable.” The other challenge is to plan, build, and pay for the new transmission facilities that will be required to access remote wind resources. Substantial work already done in this field have outlined scenarios in which barriers to achieving the 20% Wind Scenario could be removed while maintaining reliable service and reasonable electricity rates. This section begins with an examination of several detailed studies that have looked at the technical and economic impacts of integrating high levels of wind energy into electric systems. Next, this section examines how wind can be reliably accommodated into power system operations and planning. Transmission system operators must ensure that enough generation capacity is operating on the grid at all times, and that supply meets demand, even through the daily and seasonal load cycles within the system. To accommodate a nondispatchable variable source such as wind, operators must ensure that sufficient reserves from other power sources are available to keep the system in balance. Overall, it is the net system load that must be balanced, however, not an individual load or generation source in isolation. When seen in this more systemic way, wind energy can play a vital role in diversifying the power system’s energy portfolio. As the research discussed in this section demonstrates, wind’s variability need not be a technical barrier to incorporating it into the broader portfolio of available options. Although some market structures, generation portfolios, and transmission rules accommodate much more wind energy than others, reforms already under consideration in this sector can better accommodate wind energy. Experience and studies suggest that with these reforms, wind generation could reliably supply 20% of U.S. electricity demand.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wind Penetration Levels

At least three different measures are used to describe wind penetration levels: energy penetration, capacity penetration, and instantaneous penetration. They are defined and related as follows: Energy penetration is the ratio of the amount of energy delivered from the wind generation to the total energy delivered. For example, if 200 megawatt- hours (MWh) of wind energy is supplied and 1,000 MWh is consumed during the same period, wind’s energy penetration is 20%. Capacity penetration is the ratio of the nameplate rating of the wind plant capacity to the peak load. For example, if a 300-MW wind plant is operating in a zone with a 1,000-MW peak load, the capacity penetration is 30%. The capacity penetration is related to the energy penetration by the ratio of the system load factor to the wind plant capacity factor. Say that the system load factor is 60% and the wind plant capacity factor is 40%. In this case, and with an energy penetration of 20%, the capacity penetration would be 20% × 0.6/0.4, or 30%. Instantaneous penetration is the ratio of the wind plant output to load at a specific point in time, or over a short period of time.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

181

Finally, this section assesses the feasibility and cost of building new transmission lines and facilities to tap the remote wind resources that would be needed for the 20% Wind Scenario. Many challenges are inherent in building transmission systems to accommodate wind energy. If electric loads keep growing as expected, however, extensive new transmission will be required to connect new generation to loads. This is true regardless of the power sources that dominate over the coming decades, whether they are fossil fuels, wind, hydropower, or others. The U.S. power industry has renewed its commitment to a robust transmission system, and support continues to grow for cleaner generation options. In this environment, designers and engineers must find ways to build transmission at a reasonable cost and take a closer look at the alternatives to conventional power generation in a carbonconstrained future.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

4.1. Lessons Learned 4.1.1. Wind Penetration Experiences and Studies The needs of system operators—reflected in grid codes—ensure that wind power will continue to be integrated in ways that guarantee the continued reliable operation of the power system. Grid codes are regulations that govern the performance characteristics of different aspects of the power system, including the behavior of wind plants during steady-state and dynamic conditions. Grid codes around the world are also changing to incorporate wind plants, including Federal Energy Regulatory Commission (FERC) Order 661-A in the United States. Several U.S. utilities are approaching 10% wind capacity as a percentage of their peak load, including the Public Service Company of New Mexico (PNM) and Xcel Energy (which serves parts of Colorado, Michigan, Minnesota, New Mexico, North Dakota, South Dakota, Texas, and Wisconsin). Xcel Energy could actually exceed 13% by the end of 2007. MidAmerican Energy in Iowa has already exceeded 10%, and Puget Sound Energy (PSE) in Washington expects to reach 10% capacity penetration shortly after 2010. 4.1.2. Power System Studies Conclude that 20% Wind Energy Penetration Can be Reliably Accommodated Rapid growth in wind power has led a number of utilities in the United States to undertake studies of the technical and economic impacts of incorporating wind plants, or high levels of wind energy, into their electric systems. These studies are yielding a wealth of information on the expected impacts of wind plants on power system operations. General Electric International (GE), for example, has conducted a comprehensive study for New York State that examines the impact of 10% capacity penetration of wind by 2008 (Piwko et al. 2005). The state of California has set the ambitious goal of achieving 20% of its electrical energy from renewable sources by 2010 and 30% by 2020 (CEC 2007). The state of Minnesota has studied wind energy penetration of up to 25% to be implemented statewide by 2020 (EnerNex Corporation 2006). The Midwest ISO (Independent System Operator) has examined the impact of achieving a wind energy penetration of 10% in the region by 2020, with 20% in Minnesota (Midwest ISO 2006).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

182

U.S. Department of Energy

U.S. experience with studies on wind were reviewed in a special issue of IEEE Power & Energy Magazine (IEEE 2005). The Utility Wind Integration Group (UWIG; 2006) also summarized these studies in cooperation with the three large utility trade associations—the Edison Electric Institute (EEI), the American Public Power Association (APPA), and the National Rural Electric Cooperative Association (NRECA). The UWIG (2006) summary came to the following conclusions: •

•

•

• •

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

•

•

“Wind resources have impacts that can be managed through proper plant interconnection, integration, transmission planning, and system and market operations.” “On the cost side, at wind penetrations of up to 20% of system peak demand, system operating cost increases arising from wind variability and uncertainty amounted to about 10% or less of the wholesale value of the wind energy. These conclusions will need to be reexamined as results of higher-wind-penetration studies—in the range of 25%–30% of peak balancing-area load—become available. However, achieving such penetrations is likely to require one or two decades.” “During that time, other significant changes are likely to occur in both the makeup and the operating strategies of the nation’s power system. Depending on the evolution of public policies, technological capabilities, and utility strategic plans, these changes can be either more or less accommodating to the natural characteristics of wind power plants.” “A variety of means—such as commercially available wind forecasting and others discussed below—can be employed to reduce these costs.” “There is evidence that with new equipment designs and proper plant engineering, system stability in response to a major plant or line outage can actually be improved by the addition of wind generation.” “Since wind is primarily an energy—not a capacity—source, no additional generation needs to be added to provide back-up capability provided that wind capacity is properly discounted in the determination of generation capacity adequacy. However, wind generation penetration may affect the mix and dispatch of other generation on the system over time, since non-wind generation is needed to maintain system reliability when winds are low.” “Wind generation will also provide some additional load carrying capability to meet forecasted increases in system demand. This contribution is likely to be up to 40% of a typical project’s nameplate rating, depending on local wind characteristics and coincidence with the system load profile. Wind generation may require system operators to carry additional operating reserves. Given the existing uncertainties in load forecasts, the studies indicate that the requirement for additional reserves will likely be modest for broadly distributed wind plants. The actual impact of adding wind generation in different balancing areas can vary depending on local factors. For instance, dealing with large wind output variations and steep ramps over a short period of time could be challenging for smaller balancing areas, depending on the specific situation.”

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

20% Wind Energy by 2030

183

Load, Wind Generation, and Reserves The first phase in determining how to integrate wind energy into the power grid is to conduct a wind integration study, which begins with an analysis of the impact of the wind plant profiles relative to the utility load curve. By way of illustration, Figure 4.1 shows a two-week period of system loads in the spring of 2010 for the Xcel system in Minnesota. This system has 1,500 MW of wind capacity on a 10,000-MW peakload system (Zavadil et. al. 2004). Because both load and wind generation vary, it is the resulting variability—load net of wind generation—that system operators must manage, and to which the non-wind generation must respond. Although wind plants exhibit significant variability and uncertainty in their output, electric system operators already deal with these factors on similar time scales with current power system loads. It is critical to understand that output variability and uncertainty are not dealt with in isolation, but rather as one component of a large, complex system. The system must be operated with balance and reliability, taking into account the aggregate behavior of all of its loads and generation operating together. To maintain system balance and security, the electric system operator analyzes the regulation and load-following requirements of wind relative to other resources. Wind energy contributes some net increase in variability above that already imposed by cumulative customer loads. This increase, however, is less than the isolated variability of the wind alone on all time scales of interest. Although specific details vary, distribution of changes in the net load flattens and broadens when large-scale wind is added to the system. The resulting reserve requirements can be predicted with statistical analysis. It is not necessary, or economically feasible, to counter each movement of wind with a corresponding movement in a traditional energy source. As a result, the net load of wind requires fewer reserves than would be required to balance the output of individual wind plants, or all the wind plants aggregated together, in isolation from the load. In the very short time frame, the additional regulation burden has been found to be quite small, typically adding less than $0.50/MWh to the cost of the wind energy (Zavidil, et. al. 2004).

Figure 4.1. Hourly load shapes with and without wind generation. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

184

U.S. Department of Energy

Source: Milligan et al. (2006) Figure 4.2. Time scales for grid operations.

Reserve Requirements Calculation A hypothetical example is offered to calculate reserve requirements. Say that system peak load for tomorrow is projected at 1,000 MW with a 2% forecast error, which makes the forecast error (i.e., expected variability of peak load) equal to 20 MW. Wind generation for a 200-MW wind plant in that balancing area is predicted at a peak hour output of 100 MW with an error band of 20%. The expected variability of peak wind generation, then, is 20 MW. Assuming that these are independent variables, the total error is calculated as the square root of the sum of the squares of the individual variables (which is the square root of 2 × 20 squared, or 1.41 × 20, which equals 28 MW). Adding the two variables to estimate reserve requirements would result in an incorrect value of 40 MW.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

185

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Operational impacts of nondispatchable variable resources can occur in each of the time scales managed by power system operators. Figure 4.2 illustrates these time scales, which range from seconds to days. “Regulation” is a service that rapid- response maneuverable generators deliver on short time scales, allowing operators to maintain system balance. This typically occurs over a few minutes, and is provided by generators using automatic generation control (AGC). “Load following” includes both capacity and energy services, and generally varies from 10 minutes up to several hours. This time scale incorporates the morning load pick-up and evening load drop-off. The “scheduling” and “unit-commitment” processes ensure that sufficient generation will be available when needed over several hours or days ahead of the real time schedule.

Figure 4.3. Impact of wind on load-following requirements. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

186

U.S. Department of Energy

A statistical analysis of the load net of wind indicates the amount of reserves needed to cope with the combination of wind and load variability. The reserve determination starts with the assumption that wind generation and load levels are independent variables. The resultant variability is the square root of the sum of the squares of the individual variables (rather than the arithmetic sum). This means that the system operator, who must balance the total system, needs a much smaller amount of reserves to balance the load net of wind. Higher reserves would be needed if that operator were to try to balance the output of individual wind plants, or all the wind plants aggregated together in isolation from the load. Some suggest that hydropower capacity, or energy storage in the form of pumped hydro or compressed air, should be dedicated to supply backup or firming and shaping services to wind plants. Given an ideally integrated grid, this capacity would not be necessary because the pooling of resources across an electric system eliminates the need to provide costly backup capacity for individual resources. Again, it is the net system load that needs to be balanced, not an individual load or generation source in isolation. Attempting to balance an individual load or generation source is a suboptimal solution to the power system operations problem because it introduces unnecessary extra capacity and an associated increase in cost. Hydro capacity and energy storage are valuable resources that should be used to balance the system, not just the wind capacity. Figure 4.3 illustrates the incremental load-following impact of wind on an electrical system, as determined in the work of Zavadil and colleagues (2004). The histograms show more high-ramp requirements with wind than without wind, and a general reduction in smallramp requirements compared to the no wind case. For these illustrative summer and winter hours, following load alone entails relatively fewer large-megawatt changes in generation (ramps). Following load net of wind generation, however, creates a wider variability in the magnitude of load change between two adjacent hours. A system with wind generation needs more active load- following generation capability than one without wind, or more loadmanagement capability to offset the combined variability of load net of wind.

Wind Integration Cost One impact of the variability that wind imposes on the system is an increase in the uncertainty introduced into the day-ahead unit-commitment process. Specifically, despite improvements in wind generation forecasting, greater uncertainty remains about what the next day’s load net of wind and resulting generation requirements will be. The impact of these effects has been shown to increase system operating cost by up to $5.00/MWh of wind generation at wind capacity penetrations up to 20%, assuming that the wind turbine capacities have been appropriately derated. These figures are shown in the Unit-Commitment Cost column of Table 4.1. These day-ahead cost impacts are significantly higher than the others, reflecting the high cost of starting up generating units on a daily basis—even when they might or might not be needed. The impact of wind’s variability depends on the nature of the dispatchable generation sources, their fuel cost, the market and regulatory environment, and the characteristics of the wind generation resources. The most recent study conducted for Minnesota, for example, examined up to 25% energy penetration in the Midwest ISO market context (EnerNex 2006). The study found that the cost of wind integration is similar to that found in a study done two years earlier for a 15% wind capacity penetration in a vertically integrated market (Zavadil et al. 2004). A comparison of these results illustrates the beneficial effect of regional energy

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

187

markets, namely that large operational structures reduce variability, contain more loadfollowing resources, and offer more useful financial mechanisms for managing the costs of wind integration. Handling large output variations and steep ramps over short time periods (e.g., within the hour), though, can be challenging for smaller balancing areas. Table 4.1 shows the integration cost results from recent U.S. studies. The wind integration issue is primarily a matter of cost, but the costs in the 20% Wind Scenario are expected to be less than 10% of the wholesale cost of energy (COE). Table 4.1. Wind integration costs in the U.S. Date

Study

Wind Capacity Penetration (%)

Regulati on Cost ($/MWh)

Load Following Cost ($/MWh)

Unit Commitment Cost ($/MWh)

Gas Supply Cost ($/MWh)

Total Operating Cost Impact ($/MWh)

May 03 Sep 04 Nov 06

XcelUWIG XcelMNDOC MN/MIS O

3.5

0

0.41

1.44

na

1.85

15

0.23

na

4.37

na

4.60

35 (25% energy) 4

0.15

na

4.26

na

4.41

0.45

na

na

na

na

1.12

0.09

0.69

na

1.90

1.02

0.15

1.75

na

2.92

0

1.6

3.0

na

4.6

0.20

na

2.26

1.26

3.72

0.20

na

3.32

1.45

4.97

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

July 04

CA RPS Multiyear Analysis June We 4 03 Energies June We 29 Energies 03 2005 PacifiCor 20 p April Xcel10 06 PSCo April Xcel15 06 PSCo Source: Adapted from IEEE (2005).

Wind Penetration Impacts U.S. studies for capacity penetrations in the range between 20% and 35% have found that the additional reserves required to meet the intrahour variability are within the capabilities of the existing stack of units expected to be committed. In the high-penetration Minnesota study (EnerNex 2006), changes in total reserve requirements amounted to 7% of the wind generation needed to reach 25% wind energy penetration (5,700 MW). These reserves included 20 MW of additional regulating reserve, 24 MW of additional load-following reserve, and 386 MW maximum of additional operating reserve to cover next-hour errors in the wind forecast. Existing capacity is expected to cover these reserve needs, although over time, load growth could reduce this spare capacity without the construction of new

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

188

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

dispatchable power plants. Because wind and load are generally uncorrelated over short time scales, the regulation impact of wind is modest. The system operator will schedule sufficient spinning and nonspinning reserves so that unforeseen events do not endanger system balance, and so that control performance standards prescribed by the North American Electric Reliability Corporation (NERC) are met.

4.1.3. Wind Turbine Technology Advancements Improve System Integration As described in more detail in the Wind Turbine Technology section, wind turbine technology has advanced dramatically in the last 20 years. From a performance point of view, modern wind power plants have much in common with conventional utility power plants, with the exception of variability in plant output. In the early days of wind power applications, wind plants were often thought of as a curiosity or a nuisance. Operators were often asked to disconnect from the system during a disturbance and reconnect once the system was restored to stable operation. With the increasing penetration of wind power, most system operators recognize that wind plants can and should contribute to stable system operation during a disturbance, as do conventional power plants. As grid codes are increasingly incorporating wind energy, new plants are now capable of riding through a serious fault at the point of interconnection and are able to contribute to the supply of reactive power and voltage control, just like a conventional power plant. The supply of reactive power is a critical aspect of the design and operation of an interconnected power system. Modern wind plants can perform this function and supply voltage support for secure grid operations. In addition, modern wind plants can be integrated into a utility’s supervisory control and data acquisition (SCADA) system. They can provide frequency response similar to that of other conventional machines and participate in plant output control functions and ancillary service markets. Figure 4.4 illustrates the ability of a wind power plant to increase its output (blue line) in response to a drop in system frequency (red line). Figure 4.5 illustrates various control modes possible via SCADA participation, including the ability to limit plant output power at any given time, control ramp rate in moving up or down, and carry spinning reserves as ordered (Saylors 2006). These plants also have the ability to tap frequency- responsive reserves. These control features come at a cost, however, which is that of “spilling” wind, a free energy resource. In any given geographic area, the cost of operating wind units in this manner so as to provide ancillary services would have to be compared with the cost of furnishing such services by other means. Wind plant control systems offer another mechanism for dealing with the variability of the wind resource. Controllers can hold system voltage constant at a remote bus, even under widely varying wind speed conditions. Figure 4.6 shows an example of the voltage control features on a GE wind plant built recently in Colorado. In this system, voltage can be controlled across a broad range of wind conditions and power plant output. Voltage disturbances at the point of interconnection (POI) on the remote bus trigger offsetting changes in the wind plant voltage, controlling variations in the bus voltage. Modern wind plants can be added to a power grid without degrading system performance. In fact, they can contribute to improvements in system performance. A severe test of the reliability of a system is its ability to recover from a three-phase fault at a critical point in the system. (For definitions of faults, see the Glossary in Appendix E.) System stability studies have shown that modern wind plants—equipped with power electronic controls and dynamic

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

189

voltage support capabilities—can improve system performance by supporting postfault voltage recovery and damping power swings.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure 4.4. GE turbine frequency response.

Figure 4.5. Vestas wind turbine control capability.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

190

U.S. Department of Energy

Figure 4.6. GE wind plant controls.

This performance is illustrated in Figure 4.7, which simulates a normally cleared threephase fault on a critical 345-kV bus in New York State (the Marcy substation in central New York; Piwko et al. 2005). The simulation assumed a 10% wind penetration (3,300 MW on a 33,000-MW system) of wind turbines with doubly fed induction generators. It incorporated power electronics that allowed for independent control of real and reactive power. The top half of the figure shows the quicker recovery and increased damping in the system voltage transient at the Marcy 345-kV bus. The bottom half of the figure similarly shows that the flow on the east interface has less overshoot and is more highly damped with wind. And because the power electronics capabilities of these wind turbines remain connected to the grid and respond to grid conditions with or without real power generation, they manage voltage on the grid even when the turbine is not generating power. Utility planners use models to understand and represent the capabilities and performance of generators and transmission system assets. Detailed wind plant models that incorporate today’s sophisticated wind turbine and plant control features are being used to study future system configurations, as well as to improve the power system performance of conventional technology. Wind turbine manufacturers and developers are giving a high priority to the development of improved models in response to the leadership of utility organizations such as

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

191

the Western Electricity Coordinating Council (WECC). The models are critical tools that enable planners to understand wind plant capabilities and accurately determine the impact of wind plants on power system behavior. Improved performance features are likely to be incorporated into wind models as the utility interface and control characteristics of wind turbines and wind plants continue to evolve. Variable-speed designs with power electronic controls are improving real and reactive power control within wind turbines under both transient and steady- state conditions. (Solid: Wind, Dot: No Wind) 1.1

1.0

0.9

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

5000

4000

3000 0

1

2

Time (seconds) Figure 4.7. Impact of wind generation on system dynamic performance.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

3

4

192

U.S. Department of Energy Effective Load Carrying Capability

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The ELCC is the amount of additional load that can be served at the target reliability level with the addition of a given amount of generation (wind in this case). For example, if the addition of 100 MW of wind could meet an increase of 20 MW of system load at the target reliability level, it would have an ELCC of 20 MW, or a capacity value of 20% of its nameplate value. Consider the following example: There are 1,000 MW of wind capacity in a concentrated geographic area, with an ELCC of 200 MW or a capacity value of 20%. The peak load of the system is 5,000 MW. On the peak load day of the year, there is a dead calm over the area, and the output of the wind plant is 0. The lost capacity is 200 MW (20% of 1,000 MW). If this system were planned with a nominal 15% reserve margin, it would have a planning reserve of 750 MW that would well exceed the reserves needed to replace the loss of the wind capacity at system peak load.

4.1.4. Wind Forecasting Enhances System Operation System operators can significantly reduce the uncertainty of wind output by using wind forecasts that incorporate meteorological data to predict wind production. Such systems yield both hour-ahead and day-ahead forecasts to support real-time operations. They also inform the scheduling and market decisions necessary for day- ahead planning. Forecasting allows operators to anticipate wind generation levels and adjust the remainder of generation units accordingly. Piwko and colleagues (2005) found that a perfect wind forecast reduced annual variable production costs by $125 million. And a state-of-theart forecast delivered 80% of the benefit of a perfect forecast. Improved short-term wind production forecasts let operators make better day-ahead market operation and unitcommitment decisions, help real-time operations in the hour ahead, and warn operators about severe weather events. Advanced forecasting systems can also help warn the system operator if extreme wind events are likely so that the operator can implement a defensive system posture if needed. The operating impact with the largest cost is found in the unit-commitment time frame. The seamless integration of wind plant output forecasting—into both power market operations and utility control room operations—is a critical next step in accommodating large penetrations of wind energy in power systems. 4.1.5. Flexible, Dispatchable Generators Facilitate Wind Integration Studies and actual operating experience indicate that it is easier to integrate wind energy into a power system where other generators are available to provide balancing energy and precise load-following capabilities. In 2005, Energinet.dk published the preliminary results of a study of the impact of meeting 100% of western Denmark’s annual electrical energy requirement from wind energy (Pedersen 2005). The study showed that the system could absorb about 30% energy from wind without any excess (wasted) wind production, assuming no transmission ties to outside power systems. Surplus wind energy starts to grow substantially after the wind share reaches 50%. And if wind generates 100% of the total energy demand of 26 terawatt-hours (TWh), 8 TWh of the wind generation would be surplus because it would be produced during times that do not match customer energy use patterns. Other energy sources, such as thermal plants, would supply the deficit, including the

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

193

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

balancing energy. In the Pedersen study, the cost of electricity doubled when wind production reached 100% of the load. The study made very conservative assumptions, however, of no external ties or market opportunities for the excess wind energy.

4.1.6. Integrating an Energy Resource in a Capacity World Wind energy has characteristics that differ from those of conventional energy sources. Wind is an energy resource, not a capacity resource. Capacity resources are those that can be available on demand, particularly to meet system peak loads. Because only a fraction of total wind capacity has a high probability of running consistently, wind generators have limited capacity value. Traditional planning methods, however, focus on reliability and capacity planning. Incorporating wind energy into power system planning and operation, then, will require new ways of thinking about energy resources. Traditional system planning techniques use tools that are oriented toward ensuring adequate capacity. Most transmission systems, however, can make room for additional energy resources if they allow some flexibility for interconnection and operation. This flexibility includes choice of interconnection voltage, operation as a price-taker in a spot market, and limited curtailment. Economic planning tools and probabilistic analytical methods must also be used to ensure that a bulk power system has adequate generation and transmission capacity while optimizing its use of energy resources such as wind and hydropower. Many hydropower generators produce low-cost variable energy. Unlike wind energy, most hydropower energy can be scheduled and delivered at peak times, so it contributes greater capacity value to the system. But because the reality of droughts causes hydropower capacity to vary from year to year, the capacity value of this energy resource (effective loadcarrying capacity [ELCC]) must be calculated using industry-standard reliability models. The capacity value is used for system planning purposes on an annual basis, not on a daily operating basis. Some combination of existing market mechanisms and utility unitcommitment processes must be used to plan capacity for day-to-day reliability. Planning techniques for a conventional power system focus on the reliable capacity offered by the units that make up the generation system. This is essential for meeting the system planning reliability criterion, such as the loss of load probability (LOLP) of 1 day in 10 years. The ELCC of a generation unit is the metric used to determine its contribution to system reliability. It is important to recognize that wind does offer some additional planning reserves to the system, which can be calculated with a standard reliability model. The ELCC of wind generation, which can vary significantly, depends primarily on the timing of the wind energy delivery relative to times of high system risk. The capacity value of wind has been shown to range from approximately 5% to 40% of the wind plant rated capacity, as shown in Table 4.2. In some cases, simplified methods are used to approximate the rigorous reliability analysis. Reliability planning entails determining how much generation capacity of what type is needed to meet specified goals. Because wind is not a capacity resource, it does not require 100% backup to ensure replacement capacity when the wind is not blowing. Although 12,000 MW of wind capacity have been installed in the United States, little or no backup capacity for wind energy has been added to date. Capacity in the form of combustion turbines or combined cycle units has been added to meet system reliability requirements for serving load. Thinking in terms of “backing up” the wind is not appropriate because the wind capacity was installed to generate, low- emissions energy but not to meet load growth requirements. Wind

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

194

U.S. Department of Energy

power cannot replace the need for many “capacity resources,” which are generators and dispatchable load that are available to be used when needed to meet peak load. If wind has some capacity value for reliability planning purposes, that should be viewed as a bonus, but not a necessity. Wind is used when it is available, and system reliability planning is then conducted with knowledge of the ELCC of the wind plant. Nevertheless, in some areas of the nation where access to generation and markets that spans wide regions has not developed, the wind integration process could be more challenging. (For more information on capacity terminology, see the Glossary in Appendix E.) Plant capacity factors illustrate the roles that different power technologies play in a bulk power system. The capacity factor (CF) of a unit measures its actual energy production relative to its potential production at full utilization over a given time period. Table 4.3 shows the capacity factors of different power plant types within the Midwest ISO for a year. The units with the highest capacity factors—nuclear (75% CF) and coal (62% and 71% CF)—are the workhorses of the system because they produce relatively low-cost baseload energy and are fully dispatchable. Wind (30% CF) and hydro (27% CF) generate essentially free energy, so the wind is taken whenever it is available (subject to transmission availability) and the hydro is scheduled to deliver maximum value to the system (to the extent possible). The plants with the lowest capacity factors (combined cycle, combustion turbines, and oil- and gas-fired steam boilers) are operated as peaking and load-following plants and essential capacity resources. As illustrated in Table 4.3, many resources in the system operate at far less than their rated capacity for much of the year, but all are necessary components of an economic and reliable system.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table 4.2. Methods to estimate wind capacity value in the U.S. Region/Utility CA/CEC PJM

Method ELCC Peak Period

ERCOT MN/DOC/Xcel GE/NYSERDA CO PUC/Xcel

10% ELCC ELCC ELCC

RMATS PacifiCorp MAPP PGE Idaho Power PSE and Avista SPP

Rule of ELCC Peak Period Peak Period Peak Period Peak Period

Note Rank bid evaluations for RPS (20%-25%) Jun-Aug HE 3 -7 p.m., capacity factor using 3-year rolling average (20%, fold in actual data when available) May change to capacity factor for the hours between 4 -6 p.m. Sequential Monte Carlo (26%-34%) Offshore/land-based (40%/1 0%) PUC decision (10%), Full ELCC study using 10-year data gave average value of 12.5% 20% for all sites in RMATS Sequential Monte Carlo (20%). New Z-method 2006 Monthly 4-hour window, median 33% (method not stated) 4 p.m. -8 p.m. capacity factor during July (5%) The lesser of 20% or 2/3 of January Capacity Factor Top 10% loads/month; 85th percentile

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

195

4.1.7. Aggregation Reduces Variability The greater the number of wind turbines operating in a given area, the less their aggregate production variability. This is shown in Table 4.4, which gives an analysis of wind production variability as a function of an increasing number of aggregated wind turbines in a large wind plant in the Midwest (Wan 2005). Table 4.4 shows the average and standard deviation of step changes in wind plant output for different numbers of turbines over different time periods. These results indicate that wind production changes very little over short time periods. As the time period increases from seconds to minutes to hours, the output variability increases because it is driven by changes in weather patterns. In addition, as a general trend, the more wind turbines that are operating in a given period, the lower the production variability during that period. Simply put, system operators in the United States have found that as more wind generating capacity is installed, the combined output becomes less variable. A careful evaluation of integrating wind into current operations should include a determination of the magnitude and frequency of occurrence of changes in the net load on the system during the time frames of interest (seconds, minutes, and hours). This analysis, which should be conducted both before and after the wind generation is added, will help determine the additional requirements on the balance of the generation mix.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table 4.3. Midwest ISO plant capacity factor by fuel type (June 2005–May 2006) Fuel Type

Number of Units 50 275

Max Capacity (MW) 12,130 21,224

Possible Energy (MWh) 106,257,048 185,924,868

Actual Energy (MWh) 11,436,775 14,749,450

Capacity Factor (%) 11 8

Combined Cycle Gas Combustion Turbine (CT) Oil CT Hydro Nuclear Coal Steam Turbine (ST; 800

Speed m/s 6.4–7.0 7.0–7.5 7.5–8.0 8.0–8.8 >8.8

Notes: W/m2 = watts per square meter; m/s = meters per second. Wind speed measured at 50 m above ground level. Source: Elliott and Schwartz (1993).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

282

U.S. Department of Energy

Table B.8. Data sources for land-based wind resource and environmental exclusions Onshore Wind Resource Data Used in WinDS (10/23/2006) Resource Data (50 m height): State Data State Data * Source Source* Arizona 2003, Maine 2002, N/AWST N/AWST Alabama 1987, PNL Maryland 2003, N/AWST Arkansas 2006, Massachusetts 2002, N/AWST** N/AWST California 2003, Michigana 2005, N/AWST N/AWST Colorado 2003, Minnesota 2006, N/AWST OTH Connecticut 2002, Mississippi 1987, N/AWST PNL Delaware 2003, Missouria 2004, N/AWST N/AWST Florida 1987, PNL Montana 2002, N/AWST Georgia 2006, Nebraskaa 2005, AWST N/AWST

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Idaho

Iowa

2002, N/AWST 2001, NREL 2004, N/AWST 1997, OTH

New Mexico

Kansas

2004, OTH

New Yorka

Kentucky

1987, PNL

Louisiana

1987, PNL

North Carolina North Dakota

Illinois Indianaa

Nevada New Hampshire New Jersey

2003, N/AWST 2002, N/AWST 2003, N/AWST 2003, N/AWST 2004, AWST 2003, N/AWST 2000 NREL

State

Data Source*

Ohioa

2004, N/AWST

Oklahomaa

2002, OTH

Oregon

2002, N/AWST

Pennsylvaniaa

2003, N/AWST

Rhode Island

2002, N/AWST

South Carolina South Dakota

2005, AWST 2000 NREL

Tennessee

1987, PNL

Texas

Utah

2004, OTH/2000, NREL 2003, N/AWST

Vermont

2002, N/AWST

Virginia

2003, N/AWST

Washington

2002, N/AWST

West Virginia

2003, N/AWST

Wisconsin

2003, OTH

Wyoming

2002, N/AWST

*

Yr Source. Yr = Year produced (1987 to present); Source = PNL, NREL, N/AWST (NREL with AWS TrueWind), AWST (AWS TrueWind alone not validated by NREL) or OTH (data from other sources). PNL data resolution is 1/4 degree of latitude by 1/3 degree of longitude, each cell has a terrain exposure percent (5% for ridgecrest to 90% for plains) to define base resource area in each cell. Ridgecrest areas have 10% of the area assigned to the next higher power class. NREL data was generated with the WRAMS model, and does not account for surface roughness. Resolution is 1 km. Texas includes the Texas mesas study area updated by NREL using WRAMS.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

283

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

N/AWST data was generated by AWS TrueWind and validated by NREL. Resolution is 400 m for the northwest states (WA, OR, ID, MT, and WY) and 200 m everywhere else. These data consider surface roughness in their estimates. N/AWST** data was generated by AWS TrueWind, and will be validated by NREL. Data used is preliminary. OTH data from other sources. The methods, resolution, and assumptions vary. These results have not been validated by NREL. For most states, the data was taken at face value. However, some datasets were not available as 50 m power density. In those cases, assumptions were made to adjust the data to 50 m power density. a In these states, the class 2, 3 and 4 wind power class estimates were adjusted upwards by 1/2 power class to better represent the likely wind resource at wind turbine height. For Nebraska, only the portion of the state east of 102 degrees longitude was adjusted.

Wind Resource Onshore Exclusions (last revised Jan 2004) Criteria for Defining Available Windy Land (numbered in the order they are applied): Data/Comments: Environmental Criteria 2) 100% exclusion of National Park Service USGS Federal and Indian Lands shapefile, Jan 2005 and Fish and Wildlife Service managed lands USGS Federal and Indian Lands shapefile, Jan 3) 100% exclusion of federal lands 2005 designated as park, wilderness, wilderness study area, national monument, national battlefield, recreation area, national conservation area, wildlife refuge, wildlife area, wild and scenic river or inventoried roadless area. State/GAP land stewardship data management 4) 100% exclusion of state and private status 1, from Conservation Biology Institute lands equivalent to criteria 2 and 3, where Protected Lands database, 2004 GIS data is available. USGS Federal and Indian Lands shapefile, Jan 50% exclusion of remaining USDA Forest 2005 Service (FS) lands (incl. National Grasslands)*** 50% exclusion of remaining Dept. of USGS Federal and Indian Lands shapefile, Jan Defense lands*** 2005 50% exclusion of state forest land, where State/GAP land stewardship data management GIS data is available*** status 2, from Conservation Biology Institute Protected Lands database, 2004 Land Use Criteria 5) 100% exclusion of airfields, urban, USGS North America Land Use Land Cover wetland and water areas. (LULC), version 2.0, 1993; ESRI airports and airfields (2003) 11) 50% exclusion of non-ridgecrest Ridge-crest areas defined using a terrain forest*** definition script, overlaid with USGS LULC data screened for the forest categories.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

284

U.S. Department of Energy Table B.8. Continued

Other Criteria 1) Exclude areas of slope > 20% 6) 100% exclude 3 km surrounding criteria 2-5 (except water) 7) Exclude resource areas that do not meet a density of 5 km2 of class 3 or better resource within the surrounding 100 km2 area. ***

Derived from elevation data used in the wind resource model. Merged datasets and buffer 3 km Focalsum function of class 3+ areas (not applied to 1987 PNL resource data)

50% exclusions are not cumulative. If an area is non-ridgecrest forest on FS land, it is just excluded at the 50% level one time.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wind power density and speed are not explicitly calculated in WinDS. Different classes of wind power are identified by resource level, capacity factor, turbine cost, and so forth, which are discussed in the subsections that follow.

B.3.2. Wind Resource Data The basic wind resource input for the WinDS model is the amount of available windy land area (in square kilometers [km2]) by wind power class (Class 3 and higher). The amount of available windy land is derived from state wind resource maps and modified for environmental and land use exclusions (as outlined in Tables B.8 and B.9). These are the most recent state wind maps available from the Wind Powering America (WPA; see http://www.eere.energy.gov/windandhydro/windpoweringamerica/) initiative and individual state programs. The maps depict estimates of the wind resource at 50 m above the ground. The WinDS base case (Denholm and Short 2006) used only two data sources, the WPA maps validated by NREL and the Wind Energy Resource Atlas of the United States (PNL 1987). For this report, however, the WinDS model uses recent wind maps from individual state programs where available (instead of maps from the 1987 PNL atlas) and new WPA state maps. Using the recent maps offers an advantage in that modern mapping techniques and recent measurement data are incorporated into the mapping process, resulting in a finer horizontal resolution (1 km or smaller size grid cells) of the wind resource. The disadvantage is that not all updated maps were created using the same technique. The difference in techniques leads to a “patchwork quilt” pattern in some regions where notable resource discontinuities at state borders result from the different mapping techniques. For this project, several 50-m state maps were adjusted to produce more interstate compatibility. Table B.8 summarizes the state sources and land use exclusions for the land-based wind resource data used in WinDS, and Table B.9 presents the same information for offshore wind. Most state maps were completed with direct support from WPA and cost-sharing from individual states and regional partners. Under the WPA initiative, state wind resource maps were produced as described here. The preliminary resource map was produced by AWS Truewind (AWST; Albany, New York). NREL validated this map in cooperation with private consultants who had access to proprietary data, special data and knowledge of wind resources in each state, or both. The validation results were used to modify the preliminary map and to create a final wind map. NREL mapped three states—Illinois, North Dakota, and South

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

285

Dakota—before AWST became involved. An important difference between the NREL and AWST maps is that the NREL mapping technique assumed low surface roughness (equivalent to short grasslands); AWST used digital land cover data sets for surface roughness values. Increases in surface roughness generally cause decreases in the 50-m wind resource, so the NREL maps might overestimate the wind resource in areas that do not have low surface roughness. The 50-m wind power classes for individual grid cells on the WPA maps were used to determine available windy land for the WinDS model.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table B.9. Data sources for the offshore wind resource and environmental exclusions Offshore Wind Resource Data Used in WinDS (1 0/23/2006) Resource Data (50 m height): State Data State Data Source* Source* Alabama 2006, Maine 2002, NREL3 NREL1 California 2003, Maryland 2003, NREL1 NREL1 Connecticut 2002, Massachusetts 2003, NREL1 NREL1 Delaware 2003, Michigan 2006, NREL1 NREL2 Florida 2006, Minnesota 2006, NREL3 NREL2 Georgia 2006, Mississippi 2006, NREL3 NREL3 Illinois 2006, New 2002, NREL1 NREL2 Hampshire Indiana 2006, New Jersey 2003, NREL2 NREL1 Louisiana 2006, New York 2003, NREL3 NREL1

State

Data Source*

North Carolina Ohio

2003, NREL1 2006, NREL2

Oregon

2002, NREL1

Pennsylvania

2006, NREL2

Rhode Island

2002, NREL1

South Carolina Texas

2006, NREL3

Virginia

2003, NREL1

Washington

2002, NREL1

Wisconsin

2006, NREL2

2006, NREL3

*

YrSource Yr = Year produced (2002 to present); Source = NREL with different methods enumerated below. NREL1: Validated near-shore data was supplemented with offshore resource data from earlier, preliminary runs which extended further from shore. In most cases, this still did not fill the modeling area of interest of 50 nm from shore. The resource estimates were extended linearly to obtain full coverage at 50 nm with little or no change in spatial pattern. NREL2: Similar to NREL1, but available resource data estimates and areas not covered by validated and preliminary data were evaluated by NREL meteorologist to establish a best estimate of resource distribution based on expert knowledge and available measured/modeled data sources. NREL3: No validated resource estimates existed to provide a baseline. NREL meteorologists generated an initial best estimate of resource distribution to be used in the model, based on expert knowledge and available measured/modeled data sources.

Wind Resource Offshore Exclusions No exclusions were applied to the offshore resource data. It is characterized by power class and depth (0-30 m and >30m)

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

286

U.S. Department of Energy

Individual state programs have updated other (non-WPA) maps, which were created using a variety of mapping techniques. NREL has not, however, validated these maps, which do not necessarily show the 50-m wind power classes on the maps or the 50-m classes in geographic information system (GIS) format. For two states (Minnesota and Wisconsin) where the 50-m power classes for individual grid cells were unavailable, a methodology that applies basic assumptions to calculate wind power classes for each grid cell was used. This methodology calculates a combination of wind speed at the grid cells (direct or interpolated), extrapolates to adjust the wind speeds from map height(s) to 50 m, plots common wind speed frequency distribution, and takes air density into consideration. Next, environmental and land use exclusions were applied to arrive at the final windy land area totals. Updated wind resource maps were unavailable for six southeastern states— Alabama, Florida, Kentucky, Louisiana, Mississippi, and Tennessee. The underlying 50-m wind power class data from the maps contained in the 1987 atlas (PNL 1987) were used to calculate windy land area for these states. The horizontal resolution of the atlas maps is quite a bit larger (approximately 25-km grid cells) than that of the updated state maps, which feature 1km or smaller grid cells. Consequently, landform classifications and environmental and land use exclusions were used to calculate the available windy land for these states. As mentioned previously, several state maps were adjusted to produce more interstate compatibility. The Texas map was adjusted to include wind resources currently being developed on the mesas in western Texas. Because the mesas are relatively small terrain features, adequately depicting the available resources on these features is difficult. As a result, the Texas map underestimates the power class on the mesas where considerable wind energy development has taken place. In adjusting the maps, the power class values for the mesas were increased based on anemometer measurements, leading to a realistic representation of the mesas in the Texas map used for the WinDS model. The maps for eight states— Oklahoma, Missouri, Nebraska (the eastern two-thirds of the state), Indiana, Michigan, Ohio, Pennsylvania, and New York—were adjusted because their 50-m wind power class maps underestimate the potential resource at modern turbine hub heights. The available resource increase results from the high wind speed shear that is present in the affected states. The available windy land in these states was increased based on the wind power density values of individual grid cells. Grid cells in classes 2, 3, and 4 that had 50-m power density values greater than the midpoint of the associated wind power class were adjusted to the next highest class. The net result of these adjustments was to increase the windy land for classes 3, 4, and 5 in the eight states. For each of the 358 WinDS regions, the total available land area corresponding to a particular wind resource power class was multiplied by an assumed turbine density of 5 megawatts per square kilometer (MW/km2). This calculation yields the total wind-generation capacity available within each WinDS region for each wind power class. The patchwork quilt effect that results from the varied resource input data affects the selection of wind energy capacity in the WinDS model. If a state’s resource is underestimated, the WinDS model may select less wind energy capacity than is currently being developed in a given state. Similarly, if a state’s resource is overestimated, the actual wind energy capacity could be significantly less than that calculated by the model. All these resource maps were based on wind power estimates at 50 m above ground level. Today’s wind turbines, however, have hub heights as high as 80 m to 100 m. As turbine technology improves and hub heights increase, wind resources could be significantly

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

20% Wind Energy by 2030

287

different. Many states that show poor wind capability for electricity generation at the 50-m level may have significantly improved wind speeds at heights of 80 m to 100 m. As an example, even though Missouri is currently developing several hundred megawatts of wind energy, WinDS does not specify significant wind energy capacity for the state.

B.3.3. WinDS Seasonal and Diurnal Capacity Factor Calculations For each region and wind power class (classes 3 to 7), 16 time slices represent four seasons and four time periods (see Table B.3). The diurnal and seasonal variations of the wind are portrayed as the ratio of the average wind turbine output during the time slice with the annual average wind turbine output. Average capacity factors are calculated for each of the 358 WinDS regions for each power class. Monthly and hourly wind variations were obtained from two databases:

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

• •

AWST text supplemental database files National Commission on Energy Policy/National Center for Atmospheric Research (NCEP/NCAR) global reanalysis mean values (Kalnay et al. 1996).

For states with AWST data, annual and monthly average wind speeds and power were selected from the fine map grid (400-m resolution in Washington, Oregon, Idaho, Montana, and Wyoming; 200-m resolution in all other states), and hourly wind speed profiles by season from the coarse model grid (10 km in Washington, Oregon, Idaho, Montana, and Wyoming; 2 km in all other states). States with AWST data are identified in Table B.8. For monthly input data, only one 3 × 3-km cell for each region and power class was used. This cell was chosen because it has the lowest cost based on the existing grid usage optimization that is normally done as an input to WinDS (Sabeff et al. 2004). The resulting monthly pattern is the average of the monthly values within the 3 × 3 km cell for all map points in the desired power class (plus or minus one class). For hourly input data, the closest grid point from the coarse grid for each 3 × 3 cell was used. The hourly pattern is the average of hourly values for up to twenty 3 × 3 cells for each region/power class combination. There are four patterns, one for each season. Seasons are three-month periods (March–May, June– August, September– November, and December–February). For states without AWST data and for certain offshore regions, NCEP/NCAR reanalysis data were used. Reanalysis uses a dynamic data assimilation model to create worldwide data sets of wind, temperature, and other variables on a 208-km resolution grid, four times daily, throughout the depth of the atmosphere. Average values of wind speed, wind power, and air density were used, by month and by day (four times daily), over a 46-year period of record. Reanalysis wind characteristics from 120 m above ground level have been found to have the best correlation with measured wind data and wind maps. Reanalysis data, though, are suitable for use only over fairly level terrain at lower elevations. Fortunately, AWST data are available for most states that are not suitable for reanalysis. For regions that use reanalysis, the reanalysis grid point closest to the geographic center of the region was chosen. For some offshore locations, the center of the offshore region was computed and the closest reanalysis grid point was used. Using the AWST and NCEP/NCAR databases, input data sources were used to populate matrices of average wind speed, wind power, and air density by month and hour of day (24

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

288

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

hours × 12 months). The 24 × 12 array of wind speed, wind power, and air density was then divided into desired seasonal and diurnal time slices (see Table B.3). For each time slice, the power output of the General Electric International (GE) 1.5-MW wind turbine as a function of air density was estimated, and a histogram of wind speed probability as a function of wind speed and Weibull k factor was calculated. These data were then combined to calculate wind turbine capacity factor for each time slice. In the AWST data, wind power is available only by month, so the Weibull k factor was calculated only once for each season. All times of day use the same Weibull k for calculating capacity factor. Finally, a weighted average of capacity factors from the four time slices was used to revise nighttime values into a “nights and weekends” capacity factor. Time-slice capacity factors were then normalized by the total annual capacity factor, resulting in values representing the ratio of power produced in the current time slice to annual average power produced. This is the desired input into the WinDS model. This process creates a desired array of capacity factor ratios only for regions and wind power classes with data. With reanalysis, each region has data from only one power class. A final data processing step is to populate the entire array of 358 regions × 5 power classes with results. If a power class is missing, data from the next lower power class are chosen. If there are no available data from a lower power class, the next higher power class is chosen. For reanalysis regions, all five power classes are given the same array of capacity factor ratios.

B.3.4. Wind Technology Cost and Performance Black & Veatch analysts developed wind technology cost and performance projections for this report in consultation with AWEA industry experts (Black and Veatch, forthcoming 2008). Costs for turbines, towers, foundations, installation, profit, and interconnection fees are included. Capital costs are based on an average installed capital cost of $1,775 per kilowatt (kW) in 2007, which reduces to $1,650/kW in 2006 after adjusting for inflation and removing the construction financing charge. Additional costs reflecting terrain slope and regional population density are described later in this subsection. Capital costs are projected to decrease by 10% in the future as a result of technology development. Black & Veatch used historical capacity factor data to create a logarithmic bestfit line, which is then applied to each wind power class to project future performance improvements.17 Variable and fixed operations and maintenance (O&M) costs represent an average of recent project costs according to Black & Veatch’s experience. Approximately 50% of variable O&M cost is the turbine warranty. These costs are expected to decline as turbine reliability improves and the scale of wind turbines increases. Other variable O&M expenses are tied to labor rates, royalties, and other costs that are expected to be stable. Fixed O&M costs, including insurance, property taxes, site maintenance, and legal fees, are projected to stay the same because they are not affected by technology improvements. Table B. 10 lists cost and performance projections for land-based wind systems (Black and Veatch, forthcoming 2008). Table B.11 lists cost and performance projections prepared by Black & Veatch for shallow offshore wind technology (in water shallower than 30 m). Capital costs for 2005 were based on publicly available cost data for European offshore wind farms. Capital costs are assumed to decline 12.5% as a result of technology development and a maturing market. The capacity factor projection, which is based on the logarithmic best-fit lines generated for landbased turbines, we increased 15% to account for larger rotor diameters and reduced wind

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

289

turbulence over the ocean. By 2030 this adjustment factor is reduced to 5% as land-based development allows larger turbines to be used in turbulent environments. O&M costs are assumed to be three times those of land-based turbines (Musial and Butterfield 2004) with a learning rate commensurate to that projected by the U.S. Department of Energy (DOE; NREL 2006). Table B.10. Land-based wind technology cost and performance projections (US$2006)

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

B

20% Wind Energy by 2030

Wind Resource Power Class at 50 m 3 3 3 3 3 3 4 4 4 4 4 4 5 5 5 5 5 5 6 6 6 6 6 6 7 7 7 7 7 7

Year Installed 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030

Capacity Factor (%) 32 35 36 38 38 38 36 39 41 42 43 43 40 43 44 45 46 46 44 46 47 48 49 49 47 50 51 52 52 53

Cost ($/kW) 1,650 1,650 1,610 1,570 1,530 1,480 1,650 1,650 1,610 1,570 1,530 1,480 1,650 1,650 1,610 1,570 1,530 1,480 1,650 1,650 1,610 1,570 1,530 1,480 1,650 1,650 1,610 1,570 1,530 1,480

Fixed O&M ($/kW-yr) 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5

Note: MWh = megawatt-hour. Source: Black and Veatch, forthcoming 2008 et al. (2007).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Variable O&M ($/MWh) 7.0 5.5 5.0 4.6 4.5 4.4 7.0 5.5 5.0 4.6 4.5 4.4 7.0 5.5 5.0 4.6 4.5 4.4 7.0 5.5 5.0 4.6 4.5 4.4 7.0 5.5 5.0 4.6 4.5 4.4

290

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table B.11. Shallow offshore wind technology cost and performance projections (US$2006) Wind Resource Power Class at 50 m 3 3 3 3 3 3 4 4 4 4 4 4 5 5 5 5 5 5 6 6 6 6 6 6 7 7 7 7 7 7

Year Installed

Capacity Factor (%)

Capital Cost ($/kW)

Fixed O&M ($/kW-yr)

Variable O&M ($/MWh)

2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030

34 37 38 39 40 40 38 41 43 44 45 45 42 45 46 47 48 48 46 48 50 51 51 51 50 52 54 55 55 55

2,400 2,300 2,200 2,150 2,130 2,100 2,400 2,300 2,200 2,150 2,130 2,100 2,400 2,300 2,200 2,150 2,130 2,100 2,400 2,300 2,200 2,150 2,130 2,100 2,400 2,300 2,200 2,150 2,130 2,100

15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15

21 18 16 14 13 11 21 18 16 14 13 11 21 18 16 14 13 11 21 18 16 14 13 11 21 18 16 14 13 11

Source: Black and Veatch, forthcoming 2008.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table B.12. General assumptions for conventional generation technologies Technology Modeled

Conventional Hydropower Hydraulic Turbine Natural Gas Combustion Turbine Combined Cycle Natural Gas Turbine Conventional Pulverized Coal Steam Plant (No SO2 Scrubber)

Conventional Pulverized Coal Steam Plant (With SO2 scrubber) Advanced

Capability for new builds in WinDS

Construction Time (years) (1)

Construction Schedule (2) Fraction of Cost in Each Year

Forced Outage Rate (%) (3)

2 -

3 -

4 -

5 -

6 -

2.0%

Planned Outage Rate (%) (3)

Emissions Rates (4) (lbs/MMBTU fuel input)

Lifetime (years)

No

NA

1 -

5.0%

SO2 0

NOx 0

Hg 0

CO2 0

100

Yes

3

0.8

0.1

0.1

-

-

-

10.7%

6.4%

0.0006

0.08

0

33.2877

30

Yes

3

0.5

0.4

0.1

-

-

-

5.0%

7.0%

0.0006

0.02

0

33.2877

30

No-Scrubbers may be added to meet SO2 constraints. Existing plants may also switch to lowsulfur coal. No-see above

6

0.1

0.2

0.2

0.2

0.2

0.1

7.9%

9.8%

0.2355

0.448

4.6E06

55.771 31

60

6

0.1

0.2

0.2

0.2

0.2

0.1

7.9%

9.8%

1.57

0.448

4.6E06

55.77131

60

Yes

4

0.4

0.3

0.2

0.1

-

-

7.9%

9.8%

0.157

0.02

4.6E-

55.77131

60

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Supercritical Coal Steam Plant (with SO2 and Nox Controls) Integrated Coal Gasification Combined Cycle Turbine Oil/Gas Steam Turbine

Nuclear Geothermal Biomass (as Thermal Steam Generator) Concentrating Solar Power with Storage Municipal Solid Waste / Landfill Gas

06

Yes

4

0.4

0.3

0.2

0.1

-

-

7.9%

9.8%

0.0184

0.02

4.6E06

55.77131

60

No -Assumes Gas-CT or Gas- CC will be built instead. Yes No No

NA

-

-

-

-

-

-

7.9%

9.8%

0.026

0.1

0

33.2877

50

6 NA NA

0.1 -

0.2 -

0.2 -

0.2 -

0.2 -

0.1 -

5.0% 5.0% 5.0%

5.0% 5.0% 5.0%

0 0 0

0 0 0

0 0 0

0 0 0

30 20 45

Yes

3

0.5

0.4

0.1

-

-

-

35.0%

5.0%

0.00015

0.02

0

8.321926

30

No

NA

-

-

-

-

-

-

5.0%

5.0%

0

0

0

0

30

WinDS considers outage rates when determining the net capacity available for energy (as described in Section 2) and also when determining the capacity value of each technology. Planned outages are assumed to occur in all seasons except summer. Table B.12 shows outage rates for each conventional technology. Emission rates are estimated in Table B.12 for SO2, NOx, mercury, and CO2. Table B. 13 provides input-specific emission rates (in pounds per million British. thermal units) for plants that use combustible fuel. Output emission rates (in pounds per megawatt-hour) are calculated by multiplying input emission rate by heat rate.

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 293 A number of adjustments, including financing, interest during construction, terrain slope, population density, and rapid growth were applied to the capital cost. Although financing has not been treated explicitly, it is assumed to be captured by the weighted cost of capital (real discount rate) of 8.5%. A slope penalty that increases one-fourth of the capital cost by 2.5% per degree of terrain slope was used to represent expected costs associated with installations on mesas or ridge crests. Costs associated with installation represent 25% of the capital cost. Wiser and Bolinger (2007) present regional variations in installed capital cost for projects constructed in 2006. Applying a multiplier related to population density within each of the 358 WinDS regions results in regional variations similar to that observed in data. An additional 20% must be applied to the base capital cost in New England to reflect observed capital cost variations. Slope and population density penalties have been applied to the capital cost listed in Tables B.10 and B.11 within the model to represent topographical and regional variations across the United States. WinDS does assume that the price paid per unit of wind capacity can rise above the capital costs of Tables B.10 and B.11 as well as the multiplier factors, if the demand for new wind capacity significantly exceeds that supplied in earlier years. In particular, if new wind installations are more than 20% greater than those of the preceding year, there is a 1 % increase in capital cost for each 1 % growth above 20% per year (EIA 2004).

B.4. Conventional Generation

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

U.S. conventional energy generation included in the WinDS model, and most likely to be built in the United States, has been included in EIA’s data reports (2007). Table B.12 illustrates expected construction time and schedules for conventional energy technologies.

B.4.1. Conventional Generation Cost and Performance Table B.13 also gives capital cost values, heat rates (efficiency), and fixed and variable O&M costs for conventional technologies that might be added to the electric system. Cost and performance values for natural gas, nuclear, and coal technologies are based on recent project costs according to Black & Veatch experience. Pulverized coal plants continue to operate in WinDS, and SO2 scrubbers can be added to unscrubbed coal plants for $200/kW. Oil, gas, steam, and unscrubbed coal plants cannot be added to the electric system, but those currently in operation are maintained until retired. WinDS sites conventional generation technology where it is least expensive (generally adjacent to load centers) and does not require new transmission. California is the exception because its legislative requirements prohibit siting new coal plants. Capital costs for 2005, 2010, and 2015 are based on proposed engineering, procurement, and construction (EPC) estimates for plants that will be commissioned in 2010, 2015, and 2020. A wet scrubber is included in the EPC costs for new pulverized coal plants. Owners’ costs of 20% for coal, nuclear, and combined-cycle gas plants and 10% for simple-cycle gas plants provide an “all-in” cost. These owners’ costs are based on national averages and include transmission and interconnection, land, permitting, and other costs. As with wind systems, an additional 20% of the capital costs listed in Table B.3 is applied to coal and nuclear generation technology in New England, representing siting difficulties.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

294

U.S. Department of Energy Table B.13. Cost and performance characteristics for conventional generation (US$2006) Install Date

Gas CT

Gas-CC

New Coal (SC)

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Coal - IGCC

Nuclear

2005 2010 2015 2020 2030 2005 2010 2015 2020 2030 2005 2010 2015 2020 2030 2005 2010 2015 2020 2030 2005 2010 2015 2020 2030

Capital Cost ($/kW) 625 750 750 750 750 780 780 780 780 780 2,120 2,180 2,240 2,240 2,240 2,750 2,840 2,840 2,840 2,840 3,260 3,170 3,020 2,940 2,350

Fixed O&M ($/MW/yr) 7,700 6,600 6,600 6,600 6,600 14,400 14,400 14,400 14,400 14,400 35,300 35,300 35,300 35,300 35,300 38,100 38,100 38,100 38,100 38,100 90,000 90,000 90,000 90,000 90,000

Variable O&M ($/MWh) 12.0 2.8 2.8 2.8 2.8 3.0 3.0 3.0 3.0 3.0 1.7 1.7 1.7 1.7 1.7 3.9 3.9 3.9 3.9 3.9 0.5 0.5 0.5 0.5 0.5

Heat Rate (Btu/kWh) 11,560 8,900 8,900 8,900 8,900 6,870 6,870 6,870 6,870 6,870 9,470 9,200 9,100 9,000 9,000 9,000 9,000 8,900 8,800 8,580 10,400 10,400 10,400 10,400 10,400

Notes: New nuclear plants may not be constructed before 2010. O&M costs do not include fuel. Heat rate is net heat rate (including internal plant loads). Source: Black and Veatch, forthcoming 2008.

B.4.2. Fuel Prices Fuel prices for natural gas and coal are derived from reference projections from the AEO (EIA 2007b). These tables provide the prices in each census region, which are then assigned to a NERC subregion used in WinDS. Prices in the AEO 2007 are projected to 2030. Beyond 2030, WinDS increases fuel prices at the same national annual average rate as the AEO 2007 projects between 2020 and 2030. Figure B.4 illustrates the projected fossil fuel prices in constant $US2005. The 20% Wind Scenario uses the reference AEO fuel price forecast for coal because government agencies and the private sector regularly use that forecast to make planning and investment decisions. The New York Mercantile Exchange futures prices for natural gas for May 2007 through 2012 exceed the AEO’s high fuel price forecast over that period. Also, under the current set

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 295 of technology cost and performance assumptions, the WinDS model tends to select natural gas-fueled technology over coal-fueled technology. To provide a conservative estimate while representing a more traditional mix of conventional generation technology, the AEO high natural gas price forecast has been implemented. The price of uranium fuel in WinDS is constant at $0.5/MMBtu (Denholm and Short 2006).

B.5. Transmission Three types of transmission systems can be used to transport wind power around the country:

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

•

Existing grid: It is assumed that 10% of the existing grid can be used for new wind capacity, either by improving the grid or by tapping existing unused capacity. A GIS optimization determines the distance at which a particular wind farm will have to be built to connect to the grid (based on the assumption that the closest wind installation will access the grid first at the least cost). In this way, a supply curve of costs to access the grid is created for each class of wind in each region. Additionally, a pancake-type fee for crossing between balancing areas may be charged within the model. The supply curves described earlier are based on this type of transmission and the GIS optimization described here. In the near term, one can expect that most wind will be built and use the existing grid without needing to build excessive amounts of new transmission lines, but as higher penetration levels are reached, the existing grid will be insufficient. Existing transmission capacity is estimated using a database of existing lines (length and voltage) from RDI/Platts (Platts Energy Market Data; see http://www. platts.com/Analytic%20Solutions/ BaseCase/). This database is translated into a megawatt capacity as a function of kilovolt (kV) rating and length (Weiss and Spiewak 1998). New lines: The model has the ability to build straight-line transmission lines between any of the 358 wind regions. The line is built exactly to the size necessary to transmit the desired megawatts and the cost of building that transmission line is accounted for in the model. AWEA experts indicate that new transmission line capacity might be constructed for any generation technology for an average cost of $1,600/MW-mile. Based on input from the AWEA expert panel, regional transmission cost variations include an additional 40% in New England and New York; 30% in PJM East (New Jersey and Delaware); 20% in PJM West (Maryland, West Virginia, Pennsylvania, Ohio, parts of Illinois, Indiana, and Virginia); and 20% in California.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

296

U.S. Department of Energy

Figure B.4. Projected coal and natural gas prices in WinDS to 2030.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

•

The WinDS model assumes that 50% of the cost of new transmission is borne by the generation technology for which the new transmission is being built (wind or conventional); the other half is borne by the ratepayers within a region (because of the reliability benefits to all users associated with new transmission). This 50–50 allocation, which is common in the industry, was recently adopted for the 15-state Midwest Independent Transmission System Operator (Midwest ISO) region. New wind transmission lines that carry power across the main interconnects are not costshared with other technology. In the WinDS model, this sharing of costs is implied by reducing the cost of new transmission associated with a particular capacity by 50%. This means that the relative costs of transmission and capacity capital are in line with the model’s assumption. The remaining 50% of transmission costs are integrated into the final cost value outputs from the model, resulting in accurate total transmission costs. In-region transmission: Within any of the 358 wind regions around the country, the model can build directly from a wind resource location to a load within the same region. A second GISgenerated supply curve is used within the model to assign a cost for this transmission.

A fourth type of transmission, used predominantly by conventional capacity and called general transmission, can be built as well. This is limited because conventional capacity can

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 297 generally be built in the region where it is needed, thereby obviating the need for new transmission. WinDS uses a transmission loss rate of 0.236 kW/MW-mile. This value is based on the loss estimates for a typical transmission circuit (Weiss and Spiewak 1998). The assumed typical line is a 200-mile, 230-kV line rated at 170 megavolt amperes (MVA; line characteristics derived from EPRI [1983]). To emulate large regional planning structures based on that of the Midwest ISO, there is essentially no wheeling fee between balancing areas used in this analysis (although the model has the capability to model such a fee). The wind penetration is limited to 25% energy in each of the three interconnects: Western, Eastern, and ERCOT.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

B.6 Treatment of Resource Variability Variability of the wind resource can affect the electricity grid in several ways. One useful way to examine these impacts is to categorize them in terms of time, ranging from multiyear planning issues to small instantaneous fluctuations in output. At the longest time interval, a utility’s capacity expansion plans might call for the construction of more nameplate generation capacity. To meet this need, planners can plan to build conventional dispatchable capacity or wind. The variability of wind output precludes the planners from considering 1 MW of nameplate wind capacity to be the same as 1 MW of nameplate dispatchable capacity. The wind capacity cannot be counted on to be available when electricity demand is at its peak. Actually, conventional capacity cannot be considered 100% available, either. The difference is in the degree of availability. Conventional generators experience forced outages on the order of 2% to 20% of the time; wind energy is available at varying levels that average about 30% to 45% of the time, depending on the quality of the wind site. For planning purposes, this lack of availability can be handled in the same way—a statistical treatment that calculates how much more load can be added to the system for each megawatt of additional nameplate wind or conventional capacity or effective load carrying capability (ELCC). Wind’s ELCC is less than that of conventional capacity because (1) the wind availability is less than that of conventional generators and (2) at any given instant, energy from a new wind farm can be heavily correlated with the output from the existing wind farms. In other words, if the wind is not blowing at one wind site, there is a reasonable chance that it is not blowing at another nearby site. On the other hand, there is essentially no correlation between the outputs of any two conventional generation plants. Fortunately, there are ways to partly mitigate both the low availability of the wind resource and its correlation between sites. In the past 20 years, the capacity factors of new wind installations have improved considerably. This is attributable to better site exploration and characterization and to improvements in the wind turbines (largely higher towers). The correlation in wind output between sites can also be reduced. Increasing the distance between sites and the terrain features that separate them reduces the chance that two sites will experience the same wind at the same time. Figure B.5 shows this correlation as a function of distance between sites in an east–west direction and in a north–south direction (Simonsen and Stevens 2004). With its multiple regions, WinDS is able to approximate the distance between

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

298

U.S. Department of Energy

sites and, therefore, the correlation between their outputs. WinDS uses the correlation between sites to estimate the variation in wind output from the total set of wind farms supplying power to a particular region. Between each two-year optimization period and for each demand region, WinDS updates its estimate of the marginal ELCC associated with adding wind of each resource class in each wind supply region to meet demand within a NERC region. This marginal ELCC is a strong function of the wind capacity factor and the distance from the existing wind systems to the new wind site for which the ELCC is being calculated. It is also a weak function of the demand region’s LDC and the size and forced outage rates of conventional capacity. This marginal ELCC is assumed to be the capacity value of each megawatt of that wind class added in the next period in that wind supply region to serve the NERC region’s demand. All other factors being equal, when expanding wind capacity, WinDS will select the next site in a region that is as far from the existing sites as possible to ensure the lowest correlation and the highest ELCC for the next wind site. (From a practical standpoint, all factors are never “equal,” and WinDS considers the trade-offs between ELCC and wind site quality, transmission availability and cost, and local siting costs.) Generally, for the first wind site supplying a demand region, these capacity values (ELCCs) are almost equal to the peak season capacity factor. As the wind penetrates to higher levels, though, the ELCC can decline to almost zero in an individual wind supply region. The next time frame of major interest is the day ahead. Utilities generally make decisions on which generating units to commit to generation the day before they are actually committed. To comply with these unit-commitment procedures, independent power plant owners can be expected to bid for firm capacity a day ahead. This can be problematic for wind generator owners. For example, if the wind owner bids to provide firm capacity and the wind does not blow as forecast, the owner may have to make up the difference by purchasing power on the real-time market. If that power costs more per kilowatt-hour than the owner is being paid for the day-ahead bid, the owner will lose money on those kilowatt-hours that must be purchased. Not all of today’s electric grid systems operate day-ahead and real-time markets. California, for example, allows a monthly balancing of bid and actual wind generation that is much more tolerant of the inaccuracies in forecasting wind a day ahead of time. In all cases, however, the imbalances can be offset with adequate operating reserves. To capture the essence of the unit-commitment issue, WinDS estimates the impact of wind variability on the need for operating reserves (which include quick-start and spinning reserves) that can rapidly respond to changes in wind output. The operating reserves are assumed to be a linear function of the variance in the sum of generation (both wind and conventional) minus load. Because the variability of wind is statistically independent of load variability and forced outages, the total variance can be calculated as the sum of the variance associated with the normal (i.e., no wind) operating reserve and the total variance (over all the wind supply regions) in the wind output over the reconciliation period.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 299

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure B.5. Distance between wind sites and correlation with power output.

Before each two-year optimization, WinDS calculates the marginal operating reserve additions required by the next unit of wind added in a particular wind supply region from a particular wind class. The resulting value is the difference between the operating reserve required by the total system with the new wind and the operating reserve required by the total system if there were no new wind installations in that wind supply region. This value is then used throughout the next two-year linear program optimization as the marginal operating reserve requirement induced by the next megawatt of wind addition in that region of that wind resource class. In the shortest time interval, regulation reserves must compensate for instantaneous changes in wind output. Regulation reserves are normally provided by automatic generation control of conventional generators whose output can be automatically adjusted to compensate for small voltage changes on the grid. Fortunately, these instantaneous changes in wind output do not all occur at the same time, even from wind turbines within the same wind farm. This lack of correlation over time and the ease with which conventional generators can respond allows this second-order cost to be reasonably ignored. WinDS assumes that energy generated by wind that is delivered to a specific demand region in a specific time slice and exceeds the total electricity load in that region/time slice will be lost. In addition, WinDS also statistically accounts for surplus wind lost within a time slice because of variations in load and wind within the time slice. WinDS has three endogenous options for mitigating the impact of resource variability. The first is to add conventional generators that can provide spinning reserve (e.g., gas-CC) and quick-start capabilities (combustion turbines). The second—and usually least costly— option is to allow the dispersion of new wind installations to reduce the correlation of the outputs from different wind sites. Finally, the model can allow for storage of electricity at the wind site, which is usually the most costly option. The storage option was not available within this analysis and is currently being developed for the model.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

300

U.S. Department of Energy

B.7. Federal and State Energy Policy All currently enacted federal and state emission standards, renewable portfolio standards (RPS), and tax credits are implemented in WinDS. Table B.14. National SO2 emission limit schedule in WinDS Year National SO2 Emissions (Million Tons)

2003 10.6

2010 6.1

2015 5.0

2020 4.3

2030 3.5

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

(EPA 2005)

B.7.1. Federal Emission Standards WinDS has the ability to add a national cap on CO2 emissions from electricity production. It can also charge a tax for CO2 emissions. Neither a carbon cap nor a tax is implemented in the 20% Wind Scenario. Emissions of SO2 are capped at the national level. WinDS uses a cap that corresponds roughly to the 2005 Clean Air Interstate Rule (CAIR), replacing the previous limits established by the 1990 Clean Air Act Amendments (CAAA). The CAIR rule divides the United States into two regions. WinDS uses the U.S. Environmental Protection Agency’s (EPA) estimate of the effective national cap on SO2 resulting from the CAIR rule (EPA 2005). Table B.14 shows the SO2 cap used in WinDS. NOx emissions are currently unconstrained in WinDS. The NOx cap from CAIR can be added, but the net effect on the overall competitiveness of coal is expected to be relatively small (EIA 2003). Mercury emissions are currently unconstrained in WinDS. The Clean Air Mercury Rule (see http://www.epa.gov/camr/index.htm) is a cap and trade regulation, expected to be met largely via the requirements of CAIR. Control technologies for SO2 and NOx that are required for CAIR are expected to capture enough mercury to largely meet the cap goals. As a result, the incremental cost of mercury regulations is very low and is not modeled in WinDS (EIA 2003). B.7.2. Federal Energy Incentives Several classes of incentives have been applied to wind systems at the federal level. These incentives generally have the effect of reducing the cost of producing energy from these and other renewable sources. A production tax credit (PTC) provides an offset to the tax liability of companies, based on the production of energy from the resource receiving the incentive. Within this analysis, a PTC has been available for wind up to 2008 (see Table B.15).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 301 Table B.15. Federal renewable energy incentives Name Renewable Energy PTC

Value $19/MWh

Notes and Source Applies to wind. No limit to the aggregated amount of incentive. Value is adjusted for inflation to US$2006. Expires end of 2008.

(U.S. Congress 2005)

Table B.16. State renewable energy incentives State Iowa Idaho Minnesota New Jersey New Mexico Oklahoma Utah Washington Wyoming

PTC $/ MWh

ITC

Assumed State Corporate Tax

5.00% 5.00% 6.50% 6.00%

10.0% 7.60% 9.8% 9.0% 7.0% 6.0% 5.0% 0.0% 0.0%

10 2.5 4.75% 6.50% 4.00%

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Investment and production tax credit data from IREC 2006 Tax rates from: www.taxadmin.org/ fta/rate/corpinc.html

B.7.3. State Energy Incentives Several states also offer production and investment incentives for renewable energy resource development. Table B.16 lists the values used in WinDS. These incentives, however, are overwhelmed in the 20% Wind Scenario by the specification of wind energy generation in each year through 2030. B.7.4. State Renewable Portfolio Standards A number of states have addressed RPS, and states can put capacity mandates in place as an alternative or supplement to an RPS (see Table B.17). A capacity mandate requires a utility to install a certain fixed capacity of renewable energy generation. Unless prohibited by law, a state might also meet requirements by importing electricity.

B.8. Electricity Sector Direct Cost Calculation The objective of the electricity sector direct cost calculation is to determine the difference in system-wide costs where 20% wind penetration is required compared to the case where no new wind penetrates after 2006. The goal was to estimate the cost per kilowatt-hour of wind produced and the cost per kilowatt-hour of total load met. The resulting numbers for both scenarios are reported in Appendix A. To gather necessary costs from the WinDS model, it was programmed to calculate costs incurred in each year of the simulation from 2008 through 2030 for both cases (with and

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

302

U.S. Department of Energy

without wind). These costs are then broken into subgroups, including wind capital costs; conventional energy capital costs; wind and conventional transmission build costs (including the full transmission cost, not just the portion shared by each generator); and conventional fuel costs.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table B.17. State RPS requirements as of August 2005 State

RPS Start Year2

RPS Full Implementation3

Penalty in $/MWh

Arizona California Colorado Connecticut Delaware Illinois Massachusetts Maryland Minnesota Montana New Jersey New Mexico Nevada New York Oklahoma Oregon Pennsylvania Rhode Island Texas Vermont Wisconsin

2001 2003 2007 2004 2007 2004 2003 2006 2002 2008 2005 2006 2003 2006 2005 2002 2007 2007 2003 2005 2001

2025 2017 2015 2010 2019 2013 2009 2019 2015 2015 2008 2011 2015 2013 2016 2020 2020 2019 2015 2012 2011

50 5 50 55 25 10 50 20 10 10 50 10 10 5 50 5 45 55 50 10 10

WinDS Assumed RPS Fraction4 0.0079 0.034 0.044 0.013 0.056 0.062 0.026 0.045 0.072 0.075 0.029 0.026 0.133 0.035 0.05 0.078 0.014 0.069 0.01 0.05 0.006

1.

Legislated RPS Fraction (%) 1.1 20 10 10 10 15 4 7.5 1,125 MW 15 6.5 10 20 25 See Note 6 See Note 6 8 15 5,880 MW See Note 6 2.2

Load Fraction5

1 0.63 0.69 0.94 0.75 0.92 0.85 0.8 1 0.9 1 0.53 0.89 0.84 1 1 0.98 0.99 1 1 0.75

RPS data as of 8/16/05. Source: IREC 2006. RPS Start Year is the “beginning” of the RPS program. The RPS is ramped linearly to the full implementation year. 3. RPS Full Implementation is the year that the full RPS fraction must be met. WinDS assumes the fraction met is ramped up linearly between the start year and the full implementation year. 4. WinDS Assumed RPS Fraction is the fraction of state demand that must be met by wind by the full implementation year. This value is based on the total state RPS requirement and adjusted to estimate the fraction actually provided by wind since WinDS does not currently include other renewables such as biomass cofiring and certain hydro projects. 5. Load fraction is the fraction of the total state load that must meet the RPS. In certain locations, municipal or cooperative power systems may be exempt from the RPS. 6. Several states have special funds set aside to promote renewables. The net increase in wind due to these funds was estimated and applied as an effective RPS. 2.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 303 Because the benefits (especially fuel savings) of wind turbines installed in the years immediately preceding 2030 are not evident until after 2030, the cost impacts beyond 2030 are estimated. To arrive at the estimate, the model assumes that wind generation would linearly decay from 2030 to 2050 and that the conventional fuel and O&M savings would also linearly decay to 0 from 2030 to 2050. This is a conservative approach because it assumes that the wind farms are retired linearly. Finally, all costs (including the approximated costs after 2030) are discounted back to 2006. The WinDS model run is made with an 8.5% real weighted cost of capital to represent a typical utility perspective. In evaluating a policy such as an RPS, a social discount rate of 7% should be used in accordance with Office of Management and Budget guidelines (OMB 1992). This lower rate effectively places higher (higher than a utility’s 8.5% discount rate) value on benefits and costs encountered further in the future. The total cost difference then simply becomes the difference in the present value of the two cost streams. To find the cost per kilowatt-hour (levelized cost) of wind produced, the total cost difference is levelized to satisfy the following formula: Σ wind generationt * LC /(1+d)t = PV of costs in 20% case – PV of costs in no wind case As a second result, to find the cost per kilowatt-hour of total generation, replace wind generation with total generation in the preceding formula. The complete equation that calculates the present value of the costs used in the preceding equation is as follows:

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

PVCosts = a + b + c

where FractionNotRetiredWind = Fraction of wind generation remaining from wind capacity installed prior to 2031 in the 20% wind case.

B.9. References and Suggested further Reading Denholm, P., and W. Short. 2006. Documentation of WinDS Base Case. Version AEO 2006 (1). Golden, CO: National Renewable Energy Laboratory (NREL). http://www .nrel.gov/analysis/winds/pdfs/winds data.pdf.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

304

U.S. Department of Energy

EIA (Energy Information Administration). 2000. Cross Reference of States to Federal Regions, NERC Regions, and Census Divisions. Washington, DC: EIA. http://www. eia.doe.gov/cneaf/electricity/ipp/html1/tb5p01.html. EIA. 2002. Upgrading Transmission Capacity for Wholesale Electric Power Trade. Washington, DC: EIA. http://www.eia.doe.gov/cneaf/pubs_html/feat_trans_capacity/ w_sale.html. EIA. 2003. Analysis of S. 485, the Clear Skies Act of 2003, and S. 843, the Clean Air Planning Act of 2003. SR/OIAF2003-03(2003). Washington, DC: EIA. EIA. 2004a. The Electricity Market Module of the National Energy Modeling System; Model Documentation Report. DOE/EIA-M068(2004). Washington, DC: EIA. EIA. 2004b. Analysis of Senate Amendment 2028, the Climate Stewardship Act of 2003. SR/OIAF/2004-06. Washington, DC: EIA. EIA. 2006a. Assumptions to the Annual Energy Outlook 2006 with Projections to 2030.. Washington, DC: EIA. http://www.eia.doe.gov/oiaf/archive/aeo06/assumption/index.html EIA. 2006b. Supplemental Tables to the Annual Energy Outlook 2006. Washington, DC: EIA. http://www.eia.doe.gov/oiaf/archive/aeo06/supplement/index.html. EIA. 2006c. Energy and Economic Impacts of H.R.5049, the Keep America Competitive Global Warming Policy Act. SR/OIAF/2006-03. Washington, DC: EIA. EIA. 2007a. Annual Energy Outlook 2007 with Projections to 2030. Washington, DC: EIA. Report No. DOE/EIA-0383. http://www.eia.doe.gov/oiaf/archive/aeo07/index.html EIA. 2007b. Supplemental Tables to the Annual Energy Outlook. Tables 60 through 72. Washington, DC: EIA. http://www.eia.doe.gov/oiaf/aeo/supplement/index.html. EIA. 2007c. Assumptions to the Annual Energy Outlook 2007 with Projections to 2030. Washington, DC: EIA. http://www.eia.doe.gov/oiaf/aeo/assumption/index.html EIA. 2007d. Energy Market and Economic Impacts of a Proposal to Reduce Greenhouse Gas Intensity with a Cap and Trade System. SR/OIAF/2007-0 1. Washington, DC: EIA. http://www.epa.gov/cleanenergy/egrid/index.htm. Elliott, D.L., and M.N. Schwartz. 1993. Wind Energy Potential in the United States. PNLSA-23 109. NTIS No. DE9400 1667. Richland, WA: Pacific Northwest Laboratory (PNL). EPA (U.S. Environmental Protection Agency). 1996. “Compilation of Air Pollutant Emission Factors, AP-42.” In Volume I: Stationary Point and Area Sources. Fifth edition. Washington, DC: EPA. http://www.epa.gov/ttn/chief/ap42/. EPA. 2005a. Clean Air Interstate Rule, Charts and Tables. Washington, DC: EPA. http://www.epa.gov/cair/charts files/cair emissions costs.pdf. EPA. 2005b. eGRID Emissions & Generation Resource Integrated Database. Washington, DC: EPA Office of Atmospheric Programs. EPRI (Electric Power Research Institute). 1983. Transmission Line Reference Book, 345-kV and Above. Second edition. Palo Alto, CA: EPRI. IREC (Interstate Renewable Energy Council). 2006. Database of State Incentives for Renewable & Efficiency (DSIRE). http://www.dsireusa.org/. Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, et al. 1996. “The NCEP/NCAR 40-Year Reanalysis Project.” Bulletin of the American Meteorological Society. 77, 437–471. http://ams.allenpress.com/perlserv/?request=res loc&uri=urn%3Aap%3Apdf%3Adoi%3A1 0.11 75%2F 1520 0477%28 1 996%29077%3C0437%3ATNYRP%3E2.0.CO%3B2.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 305 McDonald, A., and L. Schrattenholzer. 2001. “Learning Rates for Energy Technologies.” Energy Policy 29, 255–261. Musial, W., and S. Butterfield. 2004. Future for Offshore Wind Energy in the United States. NREL/CP-500-363 13. Golden, CO: NREL. NREL. 2006. National Wind Technology Center Website, “About the Program,” http://www.nrel.gov/wind/uppermidwestanalysis.html. NREL. 2006. Projected Benefits of Federal Energy Efficiency and Renewable Energy Programs-FY2007 Budget Request. NREL/TP-320-39684. Golden, CO: NREL. http://www1.eere.energy.gov/ba/pdfs/39684 00.pdf. O’Connell, R., R. Pletka, et al. 2007. 20 % Wind Energy Penetration in the United States: A Technical Analysis of the Energy Resource. Overland Park, KS: Black & Veatch. OMB (Office of Management and Budget). 1992. Guidelines and Discount Rates for BenefitCost Analysis of Federal Programs. Circular A-94.Washington, DC: OMB. http://www.whitehouse.gov/OMB/circulars/index.html. PA Consulting Group. 2004. “Reserve Margin Data.” Energy Observer 2, July. PNL. 1987. Wind Energy Resource Atlas of the United States. DOE/CH 10093-4. Richland, WA: PNL. Sabeff, L., R. George, D. Heimiller, and A. Milbrandt. 2004. Regional Data and GIS Representation: Methods, Approaches & Issues. Presentation to Scoping Workshop for GIS Regionalization for EERE Models. http://www.nrel.gov/analysis/workshops/ pdfs/brady_gis_workshop.pdf. Simonsen, T., and B. Stevens. 2004. Regional Wind Energy Analysis for the Central United States. Grand Forks, ND: Energy and Environmental Research Center. http://www. undeerc.org/wind/literature/Regional_Wind.pdf. U.S. Congress. 2005. Domenici-Barton Energy Policy Act of 2005. Washington, DC: 109th Congress. Weiss, L., and S. Spiewak. 1998. The Wheeling and Transmission Manual. Lilburn,GA: The Fairmont Press Inc. Wiser, R., and M. Bolinger. 2007. Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2006. DOE/GO-102007-2433. Golden, CO: NREL. http://www. osti.gov/bridge. Notes: Many of the assumptions about conventional generation and fuel prices are drawn from the EIA’s National Energy Modeling System. This information is published in the AEO, which consists of three documents: the main AEO (which focuses on results); the supplemental tables (which contain additional details on results at the regional level); and the assumptions (which presents input details). Several sources for emissions data are available from the EPA, including the AP-42 series of documents. Detailed emissions estimates for different combustion technologies and emissions controls can be found in the AP-42 series. The eGRID database estimates emissions rates from existing plants, based on measured fuel use and continuous emissions monitoring system data measurement.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

306

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

APPENDIX C. WIND-RELATED JOBS AND ECONOMIC DEVELOPMENT This appendix details the economic model used to project the employment and economic development impacts of the 20% Wind Scenario described in Appendix A. Ramping up wind capacity and electricity output from wind would displace jobs and economic activity elsewhere. However, identifying such transfers accurately would be very difficult so the impacts cited here do not constitute impacts to the U.S. economy overall but are specific to the wind industry and related industries from this 20% scenario.The impacts were calculated using the Jobs and Economic Development Impacts (JEDI) model, based in part on data from the Wind Deployment System (WinDS) model (developed by the National Renewable Energy Laboratory [NREL]). Appendix A summarizes the WinDS modeled scenario, and specific assumptions are described in Appendix B. Cost and performance projections for this analysis were supplied by Black & Veatch (Black and Veatch, forthcoming 2008) and are detailed in Appendix B. The 20% Wind Scenario was constructed by specifying annual wind energy generation for every year from 2007 to 2030 based on a trajectory proposed in an NREL study (Laxson, Hand, and Blair 2006). The 2006 study forced the WinDS model to reach the 20% level for wind-generated electricity by 2030. The investigators evaluated aggressive near-term growth rates followed by sustainable levels of wind capacity installations that would maintain electricity generation levels at 20% and accommodate the repowering of wind installations beyond 2030. The 20% wind by 2030 trajectory was implemented in WinDS by calculating the percentage of annual energy production from wind at an increase of approximately 1% per year. Figure C.1 illustrates the energy generation trajectory proposed by the NREL study, along with the corresponding annual wind capacity installations that the WinDS model projects will meet these energy-generation percentages. The combined cost, technology, and operational assumptions in the WinDS model show that an annual installation rate of about 1 6 gigawatts per year (GW/year) reached by 20 1 8 could result in generation capacity capable of supplying 20% of the nation’s electricity demand by 2030. This annual installation rate is affected by the quality of wind resources selected for development as well as future wind turbine performance. The declining annual installed capacity after 2024 is an artifact of the prescribed energy generation from the NREL study in which technology improvement and wind resource variation were not considered. The NREL study provides an upper level of about 20 GW/year, because turbine performance is unchanged over time and only one wind resource power class was assumed. Based on the wind resource data and the projected wind technology improvements presented in this report, sustaining a level of annual installations at approximately 16 GW/year beyond 2030 would accommodate the repowering of aging wind turbine equipment along with increased electricity demand, so that the nation’s energy demand would continue to be met at the 20% wind level. This installation level could maintain energy production of 20% of the Nation’s demand. Additionally, this scenario shows that this level of wind development could accommodate the repowering of aging wind turbine equipment. Specific policy incentives necessary for this growth, such as a production tax credit (PTC) or carbon regulation policy, are not modeled.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 307

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure C.1. Prescribed annual wind technology generation as a percentage of national electricity demand from Laxson, Hand, and Blair (2006) and corresponding annual wind capacity installation for 20% Wind Scenario from WinDS model.

To obtain 20% of U.S. electricity from wind by 2030, changes in the wind power and electricity industries would need to be made. These changes, which are discussed in the body of this report, include advances in domestic manufacturing of wind turbine components; training, labor, and materials for installation of wind farms and operations and maintenance (O&M) functions; and improvements in wind technology and electric power system infrastructure. This appendix covers the output from the JEDI model, which shows the potential employment impacts from this scenario along with other impacts to the United States associated with new wind installations.

C.1. The JEDI Model C.1.1. Model Description The JEDI model was developed in 2002 for NREL to demonstrate the state and local economic development impacts associated with developing wind power plants in the United States. These impacts include employment numbers created in the wind power sector, and the increase in overall economic activity associated with the construction and operating phases of new wind power. The JEDI spreadsheet-based model for wind is free and available to the public. It can be downloaded from the Wind Powering America website: www. windpoweringamerica.gov. Documentation is listed on the same site. For questions, please contact Marshall Goldberg at [email protected] or Suzanne Tegen at [email protected]. JEDI was initially designed to estimate economic impacts to state economies. Subsequent enhancements made the model capable of performing county, regional, and national analyses as well. This particular analysis focuses primarily on economic impacts for the United States as a whole, although some state and regional results are presented.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

308

U.S. Department of Energy

To calculate economic impacts, the model relies on investment and expenditure data from the 20% Wind Scenario for the period between 2007 and 2030. It also uses industry multipliers that trace supply linkages in the economy. For example, the analysis shows how wind turbine purchases benefit not only turbine manufacturers, but also the fabricated metal industries and other businesses that supply inputs (goods and services) to those manufacturers. The model evaluates three separate impacts for each expenditure: direct, indirect, and induced. •

•

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

Direct impacts are the on-site or immediate effects created by spending money for a new wind project. In the JEDI model, the construction phase includes the on-site jobs of the contractors and crews hired to construct the plant as well as their managers and staffs. It also includes the jobs at the manufacturing plants that build the turbines and the jobs at the factories that produce the towers and blades, among others.18 Indirect impacts refer to the increase in economic activity that occurs, for example, when a contractor, vendor, or manufacturer receives payment for goods or services and in turn is able to pay others who support their business. This includes the banker who finances the contractor and the accountant who keeps the contractor’s books, as well as the steel mills, electrical part manufacturers, and suppliers of other necessary materials and services. Induced impacts are the changes in wealth that result from spending by people directly and indirectly employed by the project. For example, when plant workers and other local workers receive income from expenditures related to the plant, they in turn purchase food, clothing, and other goods and services from local business.

The sum of these three impacts yields a total impact that results from the construction of the turbine. Figure C.2 illustrates this ripple effect—the turbine installation spending that increases dollar flow in the economy. This figure excludes the impacts on other energy sectors as wind power displaces other sources of energy. JEDI relies on U.S.-specific multipliers and personal expenditure patterns. These multipliers—for patterns of employment, wage and salary income, output (economic activity), and personal spending (expenditure)—are adapted from the IMPLAN Professional Software model (Minnesota IMPLAN Group, Inc., Stillwater, Minnesota; see http://www.implan.com/software.html). The IMPLAN model is based on U.S. industry and census data. Spending from new investments (e.g., purchases of equipment and services) to construct and operate wind plants is matched with the appropriate multipliers for each industry sector (e.g., construction, electrical equipment, machinery, professional services, and others) affected by the change in expenditure. Outputs from the JEDI model are reported for two distinct phases: the construction phase and the annual operations phase. The construction period outputs represent the entire construction period (typically one year for a utility-scale wind project, although this can vary depending on the size of the project). The outputs for the operating period represent the jobs and economic impacts created for one year of operation.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 309

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure C.2. Wind's economic ripple effect.

C.1.2. Caveats Before noting the specific economic impacts from the 20% Wind Scenario, it is important to underscore several caveats about the JEDI model. First, the model is considered static. As such, it relies on interindustry relationships and personal consumption patterns at the time of the analysis. The model does not account for feedback through demand increases or reductions that could result from price changes. Similarly, the model does not account for feedback from inflationary pressures or potential constraints on local labor and money supplies. In addition, the model assumes that adequate local resources and production and service capabilities are available to meet the level of local demand identified in the model’s assumptions. For new power plants, the model does not automatically take into account improvements in industry productivity over time, changes during construction, or changes in O&M processes (e.g., production recipe for labor, materials, and service cost ratios). To adjust for advancements in technology or changes in wages and salaries, the model is run with new cost assumptions (e.g., once with a construction cost of $1,650/kW and again with a construction cost – excluding construction financing - of $1,6 10/kW). Second, the intent of using the JEDI model is to construct a reasonable profile of investments (e.g., wind power plant construction and operating costs) to demonstrate the economic impacts that will likely result during the construction and operating periods. Given the potential for future changes in wind power plant costs beyond those identified, and potential changes in industry and personal consumption patterns in the economy noted earlier, the analysis is not intended to provide a precise forecast, but rather an estimate of overall economic impacts in the wind energy sector from specific scenarios. Third, because the analysis and results are specific to developing new land-based and offshore wind power plants only, this is considered a gross analysis. This means that results do not reflect the net impacts of construction or operation of other types of electricitygenerating power plants or replacement of existing power generation resources to meet growing needs.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

310

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table C.1. JEDI wind modeling assumptions Category Period of Analysis

Land-Based 2007-2030

Shallow Offshore 2007-2030

Total

Nameplate Capacity Number of Turbines Turbine Size Technology Cost1 per kW 2007 2010 2015 2020 2025 2030 O&M Costs Fixed2 Variable3 2004 2010 2015 2020 2025

239.5 GW 79,130 1500–5000 kW

53.9 GW 17,976 3000 kW

293.4 GW 97,106

$1650 $1650 $1610 $1570 $1530 $1480

$2400 $2300 $2200 $2150 $2130 $2100

$11.50/kW

$15.00/kW

$7.00/MWh $5.50/MWh $5.00/MWh $4.60/MWh $4.50/MWh

$21.00/MWh $18.00/MWh $16.00/MWh $14.00/MWh $13.00/MWh

2030 $4.40/MWh U.S. Spending Labor 100% Materials and Services 100% Equipment (Manufacturing Transition)4

$11.00/MWh

Major Components Blades Towers Machine Heads Sub-Components

100% 100%

50% in 2007 to 80% in 26% in 2007 to 50% in 20% in 2007 to 42% in 10% in 2007 to 30% in

1

All dollar values are 2006 dollars. Technology costs exclude construction financing costs and regional cost variations that result from increased population density, elevation, or other considerations that are included in the WinDS model. Thus, the cumulative investment costs presented in this study are lower than those presented in Appendix A. 2 Fixed costs include land lease cost. 3 Variable costs include property taxes. 4 Refers to U.S. manufacturing/assembly for turbines, blades and towers. For purposes of this modeling, the transition (percentage of U.S. manufacturing/assembly) is assumed to occur at an average annual rate over the 24-year period.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 311 Fourth, the analysis assumes that the output from the wind power plants and the specific terms of the power purchase agreements generate sufficient revenues to accommodate the equity and debt repayment and annual operating expenditures. And finally, the analysis period is 2007 through 2030; additional impacts beyond these years are not considered.

C.2. Wind Scenario Inputs To assess the economic development from the addition of 293 GW of wind technology in the United States, the authors relied on inputs from the WinDS model. The detailed cost and performance projections can be found in Appendix B of this report. Table C.1 summarizes the wind data assumptions used in the JEDI model. The cost data are allocated into expenditure categories. Each category includes the portion of the expenditure that goes to the local area, which in this case is the entire United States. As explained earlier, the JEDI model uses project expenditures—or spending—for salaries, services, and materials to calculate the total economic impacts. Table C.2 summarizes the expenditure data used in the analysis.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

C.3. Findings As Table C.3 indicates, developing 293 GW of new land-based and offshore wind technologies from 2007 to 2030 could have significant economic impacts for the entire United States. Cumulative economic activity from the construction phase alone will reach more than $944 billion for direct, indirect, and induced activity in the nation. This level of economic activity stimulates an annual average of more than 250,000 workers required for employment in the wind power and related sectors from 2007 forward. Of these average annual positions, the wind industry supports 70,000 full-time workers in construction-related sectors, including more than 47,000 full-time workers directly in construction and 22,000 workers in manufacturing. As noted earlier, this estimate does not take into account the offsetting employment effects in other energy sectors. Under this scenario, the wind industry would produce 300 GW/year. By 2020, the economic activity generated from annual operations of the wind turbines would exceed $27 billion/year. The number of wind plant workers alone would grow to more than 28,000/year, and total wind-related employment would exceed 215,000 workers (see Table C.4). Economic impacts from direct, indirect, and induced impacts are shown per year in Figure C.3. Figure C.4 displays the total economic impacts on a relative basis. The impacts of both the construction and the operation phases are included for the entire period from 2007 through 2030. The 20% Wind Scenario shows the U.S. wind industry growing from its current 3 GW/year in 2007 to a sustained 16 GW/year by around 2018, as represented in Figure C.1. In the following sections, employment impacts in the wind industry are divided into three major industry sectors: manufacturing, construction, and operations. Each sector is described during the year of its maximum employment supported by the wind industry.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

312

U.S. Department of Energy

The JEDI model estimates the number of jobs supported by one project throughout the economy, as well as the total economic output from the project. Results from the JEDI model do not include macroeconomic effects; instead, the model focuses on jobs and impacts supported by specific wind projects. In other words, the employment estimates from the JEDI model look only at gross economic impacts from this 20% Wind Scenario. Table C.2. Wind plant expenditure data summary (in millions) Category Total Cumulative Construction Cost (2007-2030)

Onshore $379,343

Offshore $115,790

All Wind $495,133

Domestic Spending Total Annual Operational Expenses in 2030 (300 GW)

$200,192 $63,618

$94,690 $20,765

$294,882 $84,383

Direct O&M Costs

$4,394

$2,861

$7,255

Other Annual Costs

$59,224

$17,904

$77,128

Property Taxes

$1,533

$345

$1,877

Land Lease

$639

$144

$783

Note: All dollar values are 2006 dollars. All dollars represent millions of dollars. Though some of the money spent during construction leaves the country, all O&M spending is domestic.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Table C.3. U.S. construction-related economic impacts from 20% wind Average Annual Impacts Direct Impacts Construction Sector Only Manufacturing Sector Only Other Industry Sectors Indirect Impacts Induced Impacts Total Impacts (Direct, Indirect, Induced) Total Construction Impacts 2007-2030 Direct Impacts Construction Sector Only Manufacturing Sector Only Other Industry Sectors Indirect Impacts Induced Impacts Total Impacts (Direct, Indirect, Induced)

Jobs 72,946 47,020 22,346 3,580 66,035 119,774 258,755 Jobs

Earnings $5,221 $3,547 $1,446 $228 $3,008 $4,483 $12,712 Earnings

Output $12,217

1,750,706 1,128,479 536,305 85,922 1,584,842 2,874,582 6,210,129

$125,305 $85,129 $34,706 $5,471 $72,197 $107,591 $305,093

$293,197

NPV of Output $111,153

$273,057 $377,984 $944,238

$103,541 $143,367 $358,061

$11,377 $15,749 $39,343 Output

Note: All dollar values are millions of 2006 dollars. Average annual Jobs are full-time equivalent for each year of the construction period. Cumulative jobs are total full-time equivalent for the 24-year construction period from 2007 through 2030. The NPV column shows the net present value of the output column with a discount rate of 7%, per guidance from the Office of Management and Budget.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 313 Table C.4. U.S. operations-related economic impacts from 20% wind

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Operation of 300 GW in 2030 Direct Impacts Plant Workers Only Nonplant Workers Indirect Impacts Induced Impacts Total Impacts (Direct, Indirect, Induced) Total Operation Impacts 20072030 Direct Impacts Property Tax Land Lease Other Direct Impacts Plant Workers Only Nonplant Workers Indirect Impacts Induced Impacts Total Impacts (Direct, Indirect, Induced)

Jobs

Earnings

Output

76,667 28,557 48,110 37,785 102,126 216,578

$3,643 $1,617 $2,026 $1,624 $3,822 $9,090

$8,356

Jobs

Earnings

Output

1,163,297

$55,907

$122,463 $1,877 $783 $119,804

NPV of Output $26,072 $760 $317 $24,996

482,578 680,719 561,107 1,591,623 3,316,027

$27,458 $28,449 $24,118 $59,572 $139,596

$84,008 $209,286 $415,757

$17,674 $42,569 $86,315

$5,642 $13,429 $27,427

Note: All dollar values are millions of 2006 dollars. Operation jobs in 2030 are full-time equivalent for operation of the 300 GW fleet existing in 2030. Cumulative jobs are total full-time equivalent for the 24-year construction period from 2007 through 2030. The NPV column shows the net present value of the output column with a discount rate of 7%, per guidance from the Office of Management and Budget.

Figure C.3. Annual direct, indirect and induced economic impacts from 20% scenario. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

314

U.S. Department of Energy

Figure C.4. Total economic impacts of 20% Wind Energy by 2030 on a relative basis.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

C.4. Manufacturing Sector The 20% Wind Scenario includes the prospect of significantly expanding wind power manufacturing capabilities in the United States. In 2026, this level of wind development supports more than 32,000 U.S. manufacturing full-time workers in land-based and offshore wind projects. These employment impacts are directly related to producing the major components and subcomponents for the turbines, towers, and blades installed in the United States. Although the level of domestic wind installations declines after 202 1 in the scenario modeled, the manufacturing and construction industries have the potential to maintain a high level of employment and expand further to meet increasing global demand. To estimate the potential location for manufacturing jobs, data from a non governmental organization, Renewable Energy Policy Project (REPP), report were used (Sterzinger and Svrcek 2004). The REPP report identified existing U.S. companies with the technical potential to enter the wind turbine market. The map in Figure C.5 was created using the percentages of manufacturing capability in each state and JEDI’s manufacturing jobs output. Again, these potential manufacturing jobs from the REPP report are based on technical potential existing in 2004, without assuming increased productivity or expansion over time. The data also assume that existing facilities that manufacture components similar to wind turbine components are modified. Most of the manufacturing jobs in this scenario are located in the Great Lakes region, where manufacturing jobs are being lost. Even states without a significant wind resource can be impacted economically from new manufacturing jobs (e.g., southeastern US).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 315

Figure C.5. Potential manufacturing jobs created by 2030.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

C.5. Construction Sector The year 2021 represents the height of the wind plant construction period, with 16.7 GW of wind having been brought online. In that year, more than 65,000 construction industry workers are assumed to be employed and $54.5 billion is generated in the U.S. economy from direct, indirect, and induced construction spending. To reach the 20% Wind Scenario, today’s wind power industry would have to grow from 9,000 annual construction jobs in 2007 to install 3 GW, to 65,000 new annual construction jobs in 2021 to install more than 16 GW. Construction jobs could be dispersed throughout the United States. Assuming the 16 GW/year capacity can be maintained into the future, including the replacement of outdated wind plants, the industry could maintain 20% electricity from wind as demand grows. In this scenario, the construction sector would experience the largest increase in jobs, followed by the operations sector, and then by the manufacturing sector. Figure C.6 shows the direct employment impact on the construction sector, the manufacturing sector and the operations sector (plant workers only). Figure C.7 shows employment impacts during the same years, but adds the indirect and induced jobs. The bottom three bars (manufacturing, construction, and operations—including plant workers and other direct jobs) are direct jobs only. This chart depicts the large impact from the indirect and induced job categories, compared to the initial direct expenditures in the direct categories.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

316

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Figure C.6. Direct manufacturing, construction, and operations jobs supported by the 20% Wind Scenario.

Figure C.7. Jobs per year from direct, indirect, and induced categories.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 317

C.6. Operations Sector

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

JEDI results indicate that in 2030, employment of more than 215,000 total operations workers (direct, indirect, and induced) will exist to maintain 293 GW of wind capacity installed between 2007 and 2030. This includes more than 28,000 direct O&M jobs and 48,000 other direct jobs related to operating a wind plant (e.g., utility services and subcontractors). In 2030, JEDI predicts that land-based and offshore wind project operations will have a total economic impact of $27 billion. Operations employment would be dispersed across the country and is likely to be near wind installations. Rural Americans, in particular, could realize significant positive impacts from this scenario in the form of landowner payments and property taxes. Counties use property taxes to improve roads and schools, along with other vital infrastructure. More than $8.8 billion is estimated in property taxes and land lease payments between 2007 and 2030, which could be an important boost for rural communities. Figure C.8 shows the results of JEDI analysis performed on a state-by-state basis in the form of impacts to each North American Electric Reliability Corporation (NERC) region. The individual state impacts were summed to calculate the NERC region impacts. These total impacts are lower than those from the JEDI analysis for the entire country because any job or dollar flowing out of state is considered monetary leakage (in the U.S. analysis, the model considers the whole country to be “local”).

Figure C.8. Jobs and economic impacts by NERC region.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

318

U.S. Department of Energy

Figure C.8 shows jobs in job-years, which are FTE jobs counted in each year in which they exist. For example, if a maintenance worker holds one job for 20 years, this is shown as 20 job-years. For this figure, jobs during construction are assumed to last for one year. Jobs during the operations period are assumed to last for 20 years. Economic impacts are direct, indirect, and induced. Because it represents impacts from 305 GW of new wind starting in 2004 and ending in 2030, Figure C.8 shows three additional years when compared to other results.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

C.7. Conclusion As a nation, the United States has made much progress recently in developing its wind resources. With advancements in wind technologies and increasing demand for electricity projected, however, significant opportunities to develop this domestic renewable resource will continue to arise. Actions toward this goal, as identified in the 20% Wind Scenario, offer residents and businesses in the rural and urban United States potential for economic development opportunities and potential for employment. The United States is a prime location for developing wind resources and new wind manufacturing facilities. At the same time, relocating or expanding existing industries can give businesses opportunities to meet many of the material needs associated with wind technology manufacturing, installation, and facility operation. In many areas of the country, renewable resources provide an opportunity to boost the local economy significantly. Wind plants offer employment during construction and continue to support permanent jobs during operation. Today, tax revenues from wind plants help to fund local schools, hospitals, and government services. Based on the scenario presented in this report, a new and expanding wind manufacturing industry can meet 20% of our domestic electricity needs through 2030.

C.8. References Laxson, A., M. Hand, and N. Blair. 2006. High Wind Penetration Impact on U.S. Wind Manufacturing Capacity and Critical Resources. NREL/TP-500 40482. Golden, CO: National Renewable Energy Laboratory. MIG IMPLAN. “IMPLAN Professional Software.” Stillwater, MN: Minnesota. IMPLAN Group, Inc. (MIG) www.implan.com/software.html. O’Connell, R., R. Pletka, et al. 2007. 20 % Wind Energy Penetration in the United States: A Technical Analysis of the Energy Resource. Overland Park, KS: Black & Veatch. Sterzinger, G., and M. Svrcek. 2004. Wind Turbine Development: Location of Manufacturing Activity. Washington, DC: Renewable Energy Policy Project (REPP).

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 319

APPENDIX D. PARTICIPANTS IN THE 20% WIND SCENARIO

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The U.S. Department of Energy would like to acknowledge the authors and reviewers listed below. Their contributions and support were important throughout the development of this report. The final version of this document was prepared by the U.S. Department of Energy. This technical report is the culmination of contributions from more than 90 individuals and more than 50 organizations over 15 months beginning in June 2006. Contributions included strategic planning and guidance, workshop participation, topical task force participation, section writing, report review, management and coordination, and management oversight. Many participants contributed in several of these capacities. Members of the following advisory group supplied strategic guidance: Rashid Abdul Stan Calvert Edgar DeMeo* Robert Gates Robert Gramlich Thomas O. Gray Steven Lindenberg James Lyons Brian McNiff Bentham Paulos Bonnie Ram* Janet Sawin Brian Smith J. Charles Smith Randall Swisher Robert Thresher James Walker

Mitsubishi Power Systems U.S. Department of Energy Renewable Energy Consulting Services, Inc. Clipper Windpower American Wind Energy Association American Wind Energy Association U.S. Department of Energy GE Global Research McNiff Light Industries Energy Foundation Energetics Incorporated Worldwatch Institute National Renewable Energy Laboratory Utility Wind Integration Group American Wind Energy Association National Renewable Energy Laboratory enXco

*

Also provided management and logistic support under subcontract to the National Renewable Energy Laboratory Individual sections were prepared and reviewed by the following teams. Authors are shown in bold, task force members are underlined, and task force chairpersons are identified with an asterisk. Reviewers are shown in italics. Reviewers did not help to draft the sections they reviewed. Their participation is not meant to imply that they or their respective organizations either agree or disagree with the findings of the effort.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

320

U.S. Department of Energy

Section 1. Overview of the 20% Wind Scenario Elizabeth Salerno Robert Gramlich Alison Silverstein Paget Donnelly Edgar DeMeo Larry Flowers Thomas O. Gray Maureen Hand Bonnie Ram Brian Smith

American Wind Energy Association American Wind Energy Association Consultant Energetics Incorporated Renewable Energy Consulting Services, Inc. National Renewable Energy Laboratory American Wind Energy Association National Renewable Energy Laboratory Energetics Incorporated National Renewable Energy Laboratory

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Section 2. Wind Turbine Technology Michael Robinson* Paul Veers Sandy Butterfield Jim Greene Walter Musial Robert Thresher Edgar DeMeo Robert Gramlich Robert Poore Scott Schreck Alison Silverstein Brian Smith James Walker Lawrence Willey Jose Zayas Rashid Abdul Jim Ahlgrimm James Lyons Amir Mikhail

National Renewable Energy Laboratory Sandia National Laboratories National Renewable Energy Laboratory National Renewable Energy Laboratory National Renewable Energy Laboratory National Renewable Energy Laboratory Renewable Energy Consulting Services, Inc. American Wind Energy Association Global Energy Concepts, LLC National Renewable Energy Laboratory Consultant National Renewable Energy Laboratory enXco GE Energy Sandia National Laboratories Mitsubishi U.S. Department of Energy GE Global Research Clipper Windpower

Section 3. Manufacturing, Material Resources, and Impacts on the Nation’s Economy Lawrence Willey* Corneliu Barbu Maureen Hand Edgar DeMeo Kate Gordon

GE Energy GE Energy (formerly) National Renewable Energy Laboratory Renewable Energy Consulting Services, Inc. Apollo Alliance

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 321 Steve Lockard Brian O ’Hanlon Elizabeth Salerno Brian Siu Brian Smith Paul Veers James Walker Stephen Connors Brian McNiff

TPI Composites U.S. Department of Commerce American Wind Energy Association Apollo Alliance National Renewable Energy Laboratory Sandia National Laboratories enXco Massachusetts Institute of Technology McNiff Light Industries

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Section 4. Transmission and Integration into the U.S. Electric System J. Charles Smith* Robert Gramlich Mark Ahlstrom Jeff Anthony Jack Cadogan James Caldwell Henri Daher Edgar DeMeo Ken Donohoo Abraham Ellis Douglas Faulkner Robert Fullerton Stephen Gehl Jay Godfrey John Holt Karen Hyde Mike Jacobs Brendan Kirby Ronald L. Lehr Charles Linderman Michael Milligan Dale Osborn Philip Overholt Brian Parsons Richard Piwko Steve Ponder Craig Quist Kristine Schmidt Matthew Schuerger Alison Silverstein Beth Soholt John Stough Robert Thomas

Utility Wind Integration Group American Wind Energy Association WindLogics American Wind Energy Association U.S. DOE Retired Los Angeles Department of Water and Power National Grid USA Renewable Energy Consulting Services, Inc. Electric Reliability Council of Texas Public Service Company of New Mexico Puget Sound Energy Western Area Power Administration Electric Power Research Institute American Electric Power National Rural Electric Cooperative Association Xcel Energy American Wind Energy Association Oak Ridge National Laboratory American Wind Energy Association Edison Electric Institute National Renewable Energy Laboratory Midwest Independent System Operator U.S. Department of Energy National Renewable Energy Laboratory GE Energy Sierra Pacific Resources PacifiCorp Xcel Energy Energy Systems Consulting Services, LLC Consultant Wind on the Wires AEP Cornell University

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

322

U.S. Department of Energy Gary Thompson Robert Zavadil Ellen Lutz

Nebraska Public Power District EnerNex U.S. Department of Energy (formerly)

Section 5. Wind Power Siting and Environmental Effects Laurie Jodziewicz* Bonnie Ram James Walker Wayne Walker Abby Arnold John Coequyt Edgar DeMeo Nathanael Greene Alan Nogee Janet Sawin Alison Silverstein Tom Weis Katherine Kennedy Jim Lindsay Laura Miner Robert Thresher

American Wind Energy Association Energetics Inc. enXco Horizon Wind Energy Resolve Greenpeace Renewable Energy Consulting Services, Inc. Natural Resources Defense Council Union of Concerned Scientists Worldwatch Institute Consultant enXco Consultant Natural Resources Defense Council (formerly) Florida Power & Light Company U.S. Department of Energy (formerly) National Renewable Energy Laboratory

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Section 6. Wind Power Markets The contributions of this Task Force (Markets and Stakeholders) spanned a broad spectrum of issues and are reflected in many of the sections in this report. Larry Flowers* Ronald L. Lehr David Olsen Technologies Brent Alderfer Jeff Anthony Lori Bird Lisa Daniels Trudy Forsyth Robert Gough Steven Lindenberg Walter Musial Kevin Rackstraw Roby Robichaud Susan Sloan Tom Wind

National Renewable Energy Laboratory American Wind Energy Association Center for Energy Efficiency and Renewable Community Energy American Wind Energy Association National Renewable Energy Laboratory Windustry National Renewable Energy Laboratory Intertribal Council on Utility Policy U.S. Department of Energy National Renewable Energy Laboratory Clipper Windpower U.S. Department of Energy American Wind Energy Association Wind Utility Consulting

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 323 Bob Anderson Ruth Baranowski Edgar DeMeo Robert Fullerton Robert Gramlich Karen Hyde Bonnie Ram Kristine Schmidt Michael Skelley Brian Smith Dennis Lin Roby Roberts Wayne Walker

Bob Anderson Consulting National Renewable Energy Laboratory Renewable Energy Consulting Services, Inc. Western Area Power Administration American Wind Energy Association Xcel Energy Energetics Incorporated Xcel Energy Horizon Wind Energy National Renewable Energy Laboratory U.S. Department of Energy Goldman Sachs Horizon Wind Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Appendices A, B, and C and Supporting Analysis Task Force Maureen Hand* (A, B, C) Nate Blair (A, B) Suzanne Tegen (C) Mark Bolinger (A) Dennis Elliott (B) Ray George (B) Marshall Goldberg (C) Donna Heimiller (B) Tracy Hern (A) Bart Miller (A) Ric O’Connell (A, B) Marc Schwartz (B) Ryan Wiser (A) Jeff Anthony Steven Clemmer Edgar DeMeo Robert Gramlich Christopher Namovicz Elizabeth Salerno Alison Silverstein Brian Smith Ian Baring-Gould Jack Cadogan Eric Gebhardt Gary Jordan Brian Parsons Ryan Pletka Walter Short Martin Tabbita

National Renewable Energy Laboratory National Renewable Energy Laboratory National Renewable Energy Laboratory Lawrence Berkeley National Laboratory National Renewable Energy Laboratory National Renewable Energy Laboratory MRG Associates National Renewable Energy Laboratory Western Resource Advocates Western Resource Advocates Black & Veatch National Renewable Energy Laboratory Lawrence Berkeley National Laboratory American Wind Energy Association Union of Concerned Scientists Renewable Energy Consulting Services, Inc. American Wind Energy Association U.S. DOE Energy Information Administration American Wind Energy Association Consultant National Renewable Energy Laboratory National Renewable Energy Laboratory U.S. DOE Retired GE Energy GE Energy National Renewable Energy Laboratory Black & Veatch National Renewable Energy Laboratory GE Energy

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

324

U.S. Department of Energy Hanson Wood Michael DeAngelis Alejandro Moreno

enXco Sacramento Municipal Utility District U.S. Department of Energy

Workshops and Outreach

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Two strategic workshops took place during the course of this work. At the first of these, held August 17–18, 2006, attendees developed the initial statement of the 20% Wind Scenario and defined work plans. At the second, held November 9–10, 2006, participants shared and discussed preliminary results and obtained input from a group of invited individuals from key stakeholder sectors. Previously, these individuals had been external to the effort. Many of the authors, reviewers, and task force members listed in this appendix attended one or both of these workshops. The invited participants at the November workshop brought along important feedback and perspectives from their respective sectors that have helped to shape this report. Some also reviewed sections of the report. Their participation is not meant to imply that they or their respective organizations either agree or disagree with the findings of the effort. These participants are listed below: Aaron Brickman Jennifer DeCesaro Michael Fry Matt Gadow Stephen Gehl David Hamilton John Holt Robert Hornung Karen Hyde Ed Ing Debra Jacobson Miles Keogh Commissioners Charles Linderman Steve Lockard Craig Mataczynski Christopher Namovicz Administration Alan Nogee Jim Presswood Kristine Schmidt Linda Silverman Brian Siu Kate Watson

U.S. Department of Commerce Clean Energy Group American Bird Conservancy DMI Industries Electric Power Research Institute Sierra Club National Rural Electric Cooperative Association Canadian Wind Energy Association Xcel Energy Law Office of Edwin T. C. Ing DJ Consulting National Association of Regulatory Utility Edison Electric Institute TPI Composites Renewable Energy Systems Americas U.S. Department of Energy, Energy Information Union of Concerned Scientists Natural Resources Defense Council Xcel Energy U.S. Department of Energy Apollo Project Horizon Wind Energy

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 325

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

On November 28, 2006, a topical outreach workshop was held with representatives from nongovernmental organizations concerned about wildlife conservation and the environment. Participants discussed the early findings of the Environment and Siting Task Force and offered insights into issues important to their organizations. Workshop attendees are listed below. Their participation is not meant to imply that they or their respective organizations either agree or disagree with the findings of the effort. Matthew Banks Laura Bies Brent Blackwelder John Coequyt Amy Delach Tom Franklin Michael Fry Robert Gramlich Tony Iallonardo Laurie Jodziewicz Katie Kalinowski Katherine Kennedy Betsy Loyless Laura Miner Amber Pairis Cliff Scher Kate Smolski Robert Thresher James Walker Wayne Walker Tim Warman Tom Weis Peggy Welsh Marchant Wentworth

World Wildlife Fund The Wildlife Society Friends of the Earth Greenpeace Defenders of Wildlife Izaak Walton League American Bird Conservancy American Wind Energy Association National Audubon Society American Wind Energy Association Resolve/National Wind Coordinating Collaborative Natural Resources Defense Council National Audubon Society U.S. Department of Energy Association of Fish and Wildlife Agencies Energetics Incorporated Greenpeace National Renewable Energy Laboratory enXco Horizon Wind Energy National Wildlife Federation enXco Energetics Incorporated Union of Concerned Scientists

The Communications and Outreach Task Force advised on outreach strategy and facilitated engagement of key stakeholders. These functions will continue beyond release of this report. Members of this task force include Mary McCann-Gates* Jill Pollyniak* Thomas O. Gray Susan Williams Sloan Peggy Welsh

Clipper Windpower Clipper Windpower American Wind Energy Association American Wind Energy Association Energetics Incorporated

Document Coordination, Lead Editors and Other Contributions including managing report production/editing, and developing graphics and Web site materials. Members of this team include

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

326

U.S. Department of Energy Bonnie Ram Cliff Scher Russell Raymond Julie Chappell Tommy Finamore Susan Kaczmarek Kathleen O’Dell Donna Heimiller

Energetics Incorporated, Team Manager Energetics Incorporated Energetics Incorporated Energetics Incorporated, Graphics Lead Energetics Incorporated, Cover Graphic Energetics Incorporated, Document Coordinator National Renewable Energy Laboratory National Renewable Energy Laboratory

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

APPENDIX E. GLOSSARY Area control error (ACE): The instantaneous difference between net actual and scheduled interchange, taking into account the effects of frequency deviations. Balancing area (balancing authority area): The collection of generation, transmission, and loads within the metered boundaries of the balancing authority. The balancing authority maintains load-resource balance within this area. Before-and-after control impact (BACI): A schematic method used to trace environmental effects from substantial anthropogenic changes to the environment. The overall aim of the method is to estimate the state of the environment before and after any change and the specific objectives is to compare changes at reference sites (or control sites) with the actual area of impact. Bus: An electrical conductor that serves as a common connection for two or more electrical circuits. Bus-bar: The point at which power is available for transmission. Cap and trade: An established policy tool that creates a marketplace for emissions. Under a cap and trade program, the government regulates the aggregate amount of a type of emissions by setting a ceiling or cap. Participants in the program receive allocated allowances that represent a certain amount of pollutant and must purchase allowances from other businesses to emit more than their given allotment. Capability: The maximum load that a generating unit, generating station, or other electrical apparatus can carry under specified conditions for a given period of time without exceeding approved limits of temperature and stress. Capacity: The amount of electrical power delivered or required for which manufacturers rate a generator, turbine, transformer, transmission circuit, station, or system. Capacity factor (CF): A measure of the productivity of a power plant, calculated as the amount of energy that the power plant produces over a set time period, divided by the amount of energy that would have been produced if the plant had been running at full capacity during that same time interval. Most wind power plants operate at a capacity factor of 25% to 40%. Capacity penetration: The ratio of the nameplate rating of the wind plant capacity to the peak load. For example, if a 300-megawatt (MW) wind plant is operating in a zone with a 1,000-MW peak load, the capacity penetration is 30%. The capacity penetration is related to the energy penetration by the ratio of the system load factor to the wind plant capacity factor. For example, say that the system load factor is 60% and the wind plant capacity

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 327 factor is 40%. In this case, and with an energy penetration of 20%, the capacity penetration would be 20% × 0.6/0.4, or 30%. Capital costs: The total investment cost for a power plant, including auxiliary costs. Carbon dioxide (CO2): A colorless, odorless, noncombustible gas present in the atmosphere. It is formed by the combustion of carbon and carbon compounds (such as fossil fuels and biomass); by respiration, which is a slow form of combustion in animals and plants; and by the gradual oxidation of organic matter in the soil. CO2 is a greenhouse gas that contributes to global climate change. Carbon monoxide (CO): A colorless, odorless, but poisonous combustible gas. Carbon monoxide is produced during the incomplete combustion of carbon and carbon compounds, such as the fossil fuels coal and petroleum. Circuit: An interconnected system of devices through which electrical current can flow in a closed loop. Competitive Renewable Energy Zones (CREZ): A mechanism of the renewable portfolio standard in Texas designed to ensure that the electricity grid is extended to prime wind energy areas. The designation of these areas directs the Electric Reliability Council of Texas to develop plans for transmission lines to these areas that will connect them with the grid. See also “Electric Reliability Council of Texas” and “renewable portfolio standard.” Conductor: The material through which electricity is transmitted, such as an electrical wire. Conventional fuel: Coal, oil, and natural gas (fossil fuels); also nuclear fuel. Cycle: In AC electricity, the current flows in one direction from zero to a maximum voltage, then back down to zero, then to a maximum voltage in the opposite direction. This comprises one cycle. The number of complete cycles per second determines the frequency of the current. The standard frequency for AC electricity in the United States is 60 cycles. Dispatch: The physical inclusion of a generator’s output onto the transmission grid by an authorized scheduling utility. Distribution: The process of distributing electricity. Distribution usually refers to the series of power poles, wires, and transformers that run between a high-voltage transmission substation and a customer’s point of connection. Effective load-carrying capability (ELCC): The amount of additional load that can be served at the target reliability level by adding a given amount of generation. For example, if adding 100 MW of wind could meet an increase of 20 MW of system load at the target reliability level, the turbine would have an ELCC of 20 MW, or a capacity value of 20% of its nameplate value. Electricity generation: The process of producing electricity by transforming other forms or sources of energy into electrical energy. Electricity is measured in kilowatt- hours. Electric Reliability Council of Texas (ERCOT): One of the 10 regional reliability councils of the North American Electric Reliability Council. ERCOT is a membership-based 501(c)(6) nonprofit corporation, governed by a board of directors and subject to oversight by the Public Utility Commission of Texas and the Texas Legislature. ERCOT manages the flow of electric power to approximately 20 million customers in Texas, representing 85% of the state’s electric load and 75% of the Texas land area. See also “North American Electric Reliability Council.”

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

328

U.S. Department of Energy

Energy: The capacity for work. Energy can be converted into different forms, but the total amount of energy remains the same. Energy penetration: The ratio of the amount of energy delivered from one type of resource to the total energy delivered. For example, if 200 megawatt-hours (MWh) of wind energy supplies 1,000 MWh of energy consumed, wind’s energy penetration is 20%. Externality: A consequence that accompanies an economic transaction, where that consequence affects others beyond the immediate economic actors and cannot be limited to those actors. Feed-in law: A legal obligation on utilities to purchase electricity from renewable sources. Feed-in laws can also dictate the price that renewable facilities receive for their electricity. Frequency: The number of cycles through which an alternating current passes per second, measured in hertz. Gearbox: A system of gears in a protective casing used to increase or decrease shaft rotational speed. Generator: A device for converting mechanical energy to electrical energy. Gigawatt (GW): A unit of power, which is instantaneous capability, equal to one million kilowatts. Gigawatt-hour (GWh): A unit or measure of electricity supply or consumption of one million kilowatts over a period of one hour. Global warming: A term used to describe the increase in average global temperatures caused by the greenhouse effect. Green power: A popular term for energy produced from renewable energy resources. Greenhouse effect: The heating effect that results when long-wave radiation from the sun is trapped by greenhouse gases produced by natural and human activities. Greenhouse gases (GHGs): Gases such as water vapor, CO2, methane, and low- level ozone that are transparent to solar radiation, but opaque to long-wave radiation. These gases contribute to the greenhouse effect. Grid: A common term that refers to an electricity transmission and distribution system. See also “power grid” and “utility grid.” Grid codes: Regulations that govern the performance characteristics of different aspects of the power system, including the behavior of wind plants during steady- state and dynamic conditions. These fundamentally technical documents contain the rules governing the operations, maintenance, and development of the transmission system and the coordination of the actions of all users of the transmission system. Heat rate: A measure of the thermal efficiency of a generating station. Commonly stated as British thermal units (Btu) per kilowatt-hour. Note: Heat rates can be expressed as either gross or net heat rates, depending whether the electricity output is gross or net generation. Heat rates are typically expressed as net heat rates. Instantaneous penetration: The ratio of the wind plant output to load at a specific point in time, or over a short period of time. Investment tax credit (ITC): A tax credit that can be applied for the purchase of equipment such as renewable energy systems. Kilowatt (kW): A standard unit of electrical power, which is instantaneous capability equal to 1,000 watts.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 329 Kilowatt-hour (kWh): A unit or measure of electricity supply or consumption of 1,000 watts over a period of one hour. Leading edge: The surface part of a wind turbine blade that first comes into contact with the wind. Lift: The force that pulls a wind turbine blade. Load (electricity): The amount of electrical power delivered or required at any specific point or points on a system. The requirement originates at the consumer’s energy-consuming equipment. Load factor: The ratio of the average load to peak load during a specified time interval. Load following: A utility’s practice in which more generation is added to available energy supplies to meet moment-to-moment demand in the utility’s distribution system, or in which generating facilities are kept informed of load requirements. The goal of the practice is to ensure that generators are producing neither too little nor too much energy to supply the utility's customers. Megawatt (MW): The standard measure of electricity power plant generating capacity. One megawatt is equal to 1,000 kilowatts or 1 million watts. Megawatt-hour (MWh): A unit or energy or work equal to 1,000 kilowatt-hours or 1 million watt-hours. Met tower: A meteorological tower erected to verify the wind resource found within a certain area of land. Modified Accelerated Cost Recovery System (MACRS): A U.S. federal system through which businesses can recover investments in certain property through depreciation deductions over an abbreviated asset lifetime. For solar, wind, and geothermal property placed in service after 1986, the current MACRS property class is five years. With the passage of the Energy Policy Act of 2005, fuel cells, microturbines, and solar hybrid lighting technologies became classified as five-year property as well. Nacelle: The cover for the gearbox, drivetrain, and generator of a wind turbine. Nameplate rating: The maximum continuous output or consumption in MW of an item of equipment as specified by the manufacturer. Nondispatchable: The timing and level of power plant output generally cannot be closely controlled by the power system operator. Other factors beyond human control, such as weather variations, play a strong role in determining plant output. Nitrogen oxides (NOx): The products of all combustion processes formed by the combination of nitrogen and oxygen. NOx and sulfur dioxide (SO2) are the two primary causes of acid rain. Power: The rate of production or consumption of energy. Power grid: A common term that refers to an electricity transmission and distribution system. See also “utility grid.” Power marketers: Business entities engaged in buying and selling electricity. Power marketers do not usually own generating or transmission facilities, but take ownership of the electricity and are involved in interstate trade. These entities file with the Federal Energy Regulatory Commission (FERC) for status as a power marketer. Power Purchase Agreement (PPA): A long-term agreement to buy power from a company that produces electricity. Power quality: Stability of frequency and voltage and lack of electrical noise on the power grid.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

330

U.S. Department of Energy

Public Utility Commission: A governing body that regulates the rates and services of a utility. Public Utility Regulatory Policies Act (PURPA) of 1978: As part of the National Energy Act, PURPA contains measures designed to encourage the conservation of energy, more efficient use of resources, and equitable rates. These measures included suggested retail rate reforms and new incentives for production of electricity by cogenerators and users of renewable resources. Production tax credit (PTC): A U.S. federal, per-kilowatt-hour tax credit for electricity generated by qualified energy resources. Originally enacted as part of the Energy Policy Act of 1992, the credit expired at the end of 2001, was extended in March 2002, expired at the end of 2003, was renewed on October 4, 2004 and was then extended through December 31, 2008. Radioactive waste: Materials remaining after producing electricity from nuclear fuel. Radioactive waste can damage or destroy living organisms if it is not stored safely. Ramp rate: The rate at which load on a power plant is increased or decreased. The rate of change in output from a power plant. Renewable energy: Energy derived from resources that are regenerative or that cannot be depleted. Types of renewable energy resources include wind, solar, biomass, geothermal, and moving water. Regional Greenhouse Gas Initiative (RGGI): An agreement among 10 northeastern and midAtlantic states to reduce CO2 emissions. Through the initiative, the states will develop a regional strategy to control GHGs. Fundamental to the agreement is the implementation of a multistate cap and trade program to induce a market-based emissions controlling mechanism. Renewable energy credit (REC) or certificate: A mechanism created by a state statute or regulatory action to make it easier to track and trade renewable energy. A single REC represents a tradable credit for each unit of energy produced from qualified renewable energy facilities, thus separating the renewable energy’s environmental attributes from its value as a commodity unit of energy. Under a REC regime, each qualified renewable energy producer has two income streams—one from the sale of the energy produced, and one from the sale of the RECs. The RECs can be sold and traded and their owners can legally claim to have purchased renewable energy. Renewable portfolio standard (RPS): Under such a standard, a certain percentage of a utility’s overall or new generating capacity or energy sales must be derived from renewable resources (e.g., 1% of electric sales must be from renewable energy in the year 200x). An RPS most commonly refers to electricity sales measured in megawatt-hours, as opposed to electrical capacity measured in megawatts. Restructuring: The process of changing the structure of the electric power industry from a regulated guaranteed monopoly to an open competition among power suppliers. Rotor: The blades and other rotating components of a wind turbine. Solar energy: Electromagnetic energy transmitted from the sun (solar radiation). Sulfur dioxide (SO2): A colorless gas released as a by-product of combusted fossil fuels containing sulfur. The two primary sources of acid rain are SO2 and NOx. Trade wind: The consistent system of prevailing winds occupying most of the tropics. Trade winds, which constitute the major component of the general circulation of the atmosphere, blow northeasterly in the northern hemisphere and southeasterly in the

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 331 southern hemisphere. The trades, as they are sometimes called, are the most persistent wind system on Earth. Turbine: A term used for a wind energy conversion device that produces electricity. See also “wind turbine.” Turbulence: A swirling motion of the atmosphere that interrupts the flow of wind. Utility grid: A common term that refers to an electricity transmission and distribution system. See also “power grid.” Variable-speed wind turbines: Turbines in which the rotor speed increases and decreases with changing wind speeds. Sophisticated power control systems are required on variablespeed turbines to ensure that their power maintains a constant frequency compatible with the grid. Volt (V): A unit of electrical force. Voltage: The amount of electromotive force, measured in volts, between two points. Watt (W): A unit of power. Watt-hour (Wh): A unit of electricity consumption of one watt over the period of one hour. Wind: Moving air. The wind’s movement is caused by the sun’s heat, the earth, and the oceans, which force air to rise and fall in cycles. Wind energy: Energy generated by using a wind turbine to convert the mechanical energy of the wind into electrical energy. See also “wind power.” Wind generator: A wind energy conversion system designed to produce electricity. Wind power: Power generated by using a wind turbine to convert the mechanical power of the wind into electrical power. See also “wind energy.” Wind power density: A useful way to evaluate the wind resource available at a potential site. The wind power density, measured in watts per square meter, indicates the amount of energy available at the site for conversion by a wind turbine. Wind power class: A scale for classifying wind power density. There are seven wind power classes, ranging from 1 (lowest wind power density) to 7 (highest wind power density). In general, sites with a wind power class rating of 4 or higher are now preferred for largescale wind plants. Wind power plant: A group of wind turbines interconnected to a common utility system. Wind resource assessment: The process of characterizing the wind resource and its energy potential for a specific site or geographical area. Wind speed: The rate of flow of wind when it blows undisturbed by obstacles. Wind speed profile: A profile of how the wind speed changes at different heights above the surface of the ground or water. Wind turbine: A term used for a device that converts wind energy to electricity. Wind turbine rated capacity: The amount of power a wind turbine can produce at its rated wind speed. Windmill: A wind energy conversion system that is used primarily to grind grain. Windmill is commonly used to refer to all types of wind energy conversion systems.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

332

U.S. Department of Energy

GRATEFUL APPRECIATION TO PARTNERS The U.S. Department of Energy would like to acknowledge the in-depth analysis and extensive research conducted by the National Renewable Energy Laboratory and the major contributions and manuscript reviews by the American Wind Energy Association and many wind industry organizations that contributed to the production of this report. The costs curves for energy supply options and the WinDS modeling assumptions were developed in cooperation with Black & Veatch. The preparation of this technical report was coordinated by Energetics Incorporated of Washington, DC and Renewable Energy Consulting Services, Inc. of Palo Alto, CA. All authors and reviewers who contributed to the preparation of the report are listed in Appendix D. Available electronically at http://www.osti.gov/bridge

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Available for a processing fee to U.S. Department of Energy and its contractors, in paper, from: U.S. Department of Energy Office of Scientific and Technical Information P.O. Box 62 Oak Ridge, TN 37831-0062 phone: 865.576.8401 fax: 865.576.5728 email: mailto:[email protected] Available for sale to the public, in paper, from: U.S. Department of Commerce National Technical Information Service 5285 Port Royal Road Springfield, VA 22161 phone: 800.553.6847 fax: 703.605.6900 email: [email protected] online ordering: http://www.ntis.gov/ordering.htm

Notice This report is being disseminated by the Department of Energy. As such, the document was prepared in compliance with Section 515 of the Treasury and General Government Appropriations Act for Fiscal Year 2001 (Public Law 106-554) and information quality guidelines issued by the Department of Energy. Further, this report could be "influential scientific information" as that term is defined in the Office of Management and Budget's Information Quality Bulletin for Peer Review (Bulletin). This report has been peer reviewed pursuant to section II.2 of the Bulletin. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends … 333 rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or any agency thereof.

ENDNOTES

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

1

AEO data from 2007 were used in this report. AEO released new data in March of 2008, which were not incorporated into this report. While the new EIA data could change specific numbers in the report, it would not change the overall message of the report. 2 According to AWEA, the U.S. wind energy industry installed 5,244 MW in 2007, expanding the nation's total wind power generating capacity by 45% in a single calendar year and more than doubling the 2006 installation of 2,454 MW. American Wind Energy Associations 2007 Market Report, January 2008. Government sources for validation of 2007 installed MW were not available at the time this report was written 3 The model, developed by NREL’s Strategic Energy Analysis Center (SEAC), is designed to address the principal market issues related to the penetration of wind energy technologies into the electric sector. For additional information and documentation, see text box entitled “Wind Energy Deployment Model Assumptions,” Appendices A and B, and http://www.nrel.gov/analysis/winds/ 4 AEO data from 2007 were used in this report. AEO released new data in March of 2008, which were not incorporated into this report. While new EIA data could change specific numbers in this report, it would not change the overall message of the report 5 The modeling assumptions prescribed annual wind energy generation levels that reached 20% of projected demand by 2030 so as to demonstrate technical feasibility and quantify costs and benefits. Policy options that would help induce this growth trajectory were not included. It is assumed that a stable policy environment that recognizes wind’s benefits could lead to growth rates that would result in the 20% Wind Scenario. 6 Appendix B presents a full analysis of changes in the capacity mix and energy generation under the 20% Wind Scenario. 7 CO2 can be converted to carbon equivalent by multiplying by 12/44. Appendix A presents results in carbon equivalent, not CO2. In addition, the WinDS model projects higher CO2 emissions than the EIA model because it assumes a higher share of coal-fired generation. 8 Carbon mitigation policies were not modeled in either the 20% wind or no new Wind Scenarios, which results in conventional generation mixes typical of current generation capacity. Under carbon mitigation scenarios, additional technologies could be implemented to reduce the need for conventional generation technology (see Appendix A) 9 See Appendix A for specific assumptions. 10 Compared to consumption of the high price scenario of EIA (2007), used in this report. 11 One hectare = 2.47 acres 12 AEO data from 2007 were used in this report. AEO released new data in March of 2008, which were not incorporated into this report. While the new EIA data could change specific numbers in the report, it would not change the overall message of the report.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

334

U.S. Department of Energy

13

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The model, developed by NREL’s Strategic Energy Analysis Center (SEAC), is designed to address the principal market issues related to the penetration of wind energy technologies into the electric sector. For additional information and documentation, see http://www.nrel.gov/analysis/winds/. 14 All dollar values in appendices A and B are in $US2006. These capital costs include construction financing, which adds approximately 5% to the “overnight” capital cost given in Appendix B. The WinDS model applies financing costs in each solution period that requires overnight capital costs as input. 15 These costs reflect the model inputs and could vary significantly with different fossil fuel price assumptions, carbon taxes or caps, or additional breakthroughs in renewable technologies. 16 For more information on NERC, see http://www.nerc.com/regional/. 17 Capacity factors for 2000 and 2005 fit to actual data. For the higher wind power classes (6 and 7), however, limited data are available for operating plants, so capacity factors were extrapolated from the linear relationships between wind classes. 18 When an impact analysis is conducted in this manner, the definitions of direct and indirect are changed somewhat. Typically, the change in final demand to an industry (in this instance the wind industry) is seen as the direct effect. In the JEDI model, the direct effect includes what are usually called first-round indirect effects (e.g., demand to manufacturers and other goods and service suppliers). The JEDI indirect effects are all subsequent rounds of the industry indirect effects.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

In: Wind Power: Technology, Economics and Policies ISBN 978-1-60692-323-8 Editor: Cedrick N. Osphey, pp. 335-385 © 2009 Nova Science Publishers, Inc.

Chapter 4

WIND AND HYDROPOWER TECHNOLOGIES PROGRAM. 2007 PEER REVIEW REPORT U.S. Department of Energy SUMMARY

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Objective review and advice from peers—peer review—provides Department of Energy (DOE) managers, staff, and researchers with a powerful and effective tool for enhancing the management, relevance, effectiveness, and productivity of all of the Office of Energy Efficiency and Renewable Energy (EERE) research, development, demonstration, deployment, and supporting business management programs. A peer review is defined as: A rigorous, formal, and documented evaluation process using objective criteria and qualified and independent reviewers to make a judgment of the technical/ scientific/business merit, the actual or anticipated results, and the productivity and management effectiveness of programs and/or projects.

The Wind Program peer review focused on technology application and acceptance activities that were planned, underway, or recently completed. The findings are considered by Wind Program managers, staff, and researchers in setting priorities, conducting operations, and improving projects. The DOE Wind Program peer review was conducted July 11-12, 2007, at the Denver Marriott West Hotel in Golden, CO. Presentations were given on specific technical projects within the Systems Integration, Market Policy and Analysis, Environmental and Siting, and Technology Acceptance Activities program areas. The following document is the peer review panel’s observations and findings, the response from the Wind Program to these, and supporting meeting materials including an agenda and participants list. In accordance with the DOE Peer Review Guide Section 6.0, peer reviewers provided both quantitative and narrative evaluations of the materials and projects presented at the peer review meeting. The comments herein are the most direct reflection of reviewers’ written evaluations, and where possible have been included verbatim.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

336

U.S. Department of Energy

PEER REVIEW MEETING PROCESS

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The U.S. Department of Energy (DOE) Wind and Hydropower Program’s strategic planning framework has two elements (Figure 1). First, the Program has an ongoing technical assessment activity to monitor the status of wind technology and progress in achieving program cost goals, to evaluate that status within the context of marketplace needs, and to identify technological pathways that will lead to successful competition in the marketplace. The program also uses a formal peer review process to benefit from the guidance of industry and the research community, and to provide an outside view of the Program. As shown in Figure 1, technical assessment and peer review provide inputs that the program management team considers in making decisions about strategic program directions and funding priorities. The peer review is designed to provide feedback to Wind Program management on the research and development areas chosen for review. Peer reviews are conducted in conformance with departmental guidance. The results of the review are considered when the program management team evaluates potential adjustments to program direction. The DOE Wind Technologies Program peer review was held on July 11-12, 2007, at the Denver Marriott West hotel in Golden, CO. The review focused on specific technical projects within the Systems Integration, Market Policy and Analysis, Environmental and Siting, and Technology Acceptance Activities program areas.

Figure 1. Strategic Planning Framework.

The Wind Energy Program peer review panel was comprised of experts in the wind energy field. All committee members are independent of affiliation with the Wind Energy Program. The Wind Energy Program review panel included:

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report Name

Affiliation

Carl Weinberg (Chair)

Weinberg Associates

John Mankins

Artemis Innovation Management Solutions, LLC

Steve Connors

Massachusetts Institute of Technology

*

Ken Karas

Former CEO, Enron Wind Corp.; Former CEO, Zond Corp. **

Mike Kelly

Dale Osborn *

337

**

Direction of Operations, Horizon Wind Energy Transmission Technical Manager, MISO

Not present for this year’s Peer Review. New Peer Review Panelist in 2007.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

**

Reviewers received briefing materials to aid in the program review process prior to attending the meeting. This information included an agenda, the Wind Energy Multi-Year Program Plan 2007-20 12, Wind Energy Program FY 2007 Annual Operating Plan, the 2007 Wind Power Strategic Planning Meeting report, and DOE’s DOE Annual Report on Wind Power 2007. Reviewers also received copies of the review evaluation forms and the EERE evaluation guidelines as provided in the EERE Peer Review Guide. Reviewers were also provided an outline of the Wind Energy Program’s mission and goals. The peer review meeting was conducted as a two-day event. The first day focused on System Integration, and Market and Policy Analysis program activities. The second day covered Environmental and Siting and Technology Acceptance program activities. Peer reviewers completed their reviews in a separate location and provided an initial summary of their findings to members of the Wind Energy Program at the conclusion of the peer review meeting. In accordance with DOE Peer Review Guide Section 6.0, the peer review team chose to submit both quantitative (i.e., numerical scores) and qualitative (i.e., narrative accounts) evaluations as part of their review of the materials and projects presented. The comments herein are the most direct reflection of their written evaluations, and where possible have been included verbatim. The project evaluation forms were distributed to the Peer Review Panel members prior to the meeting, as well as detailed guidance on how to complete the forms. The panel was asked to rate the projects in the following categories: 1. Effectiveness (considering the elements of quality, productivity, and accomplishments); 2. Relevance (to mission, goals, strategy, and technical and/or market barriers); and 3. Overall Impression (considering all measures, inputs and outputs, and program management). Numerical scores were based on a ten point scale, with qualitative descriptors given for the numerical scoring index (i.e., a score of 1-2 corresponded to a “Seriously Deficient” rating, 4-6 corresponded to an “Average” rating, and 9-10 corresponded to an “Outstanding” rating). Furthermore, the panel was asked to rate the projects with respect to the Program’s Mission and Goals, as shown on the following page.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

338

U.S. Department of Energy Program Mission and Goals

Mission: To lead the nation's efforts to improve wind energy technology through public/private partnerships that enhance domestic economic benefit from wind power development and coordinate with stakeholders on activities that address barriers to wind energy use. Program Strategic Goal: Collaborate with federal, state, industry, and stakeholder organizations and lead wind energy technology R&D and application efforts to support achieving the 20% wind vision for the Nation's electricity by 2030. Program Performance Goals: • •

•

•

•

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

•

By 2012, reduce the cost of electricity from large wind systems in Class 4 winds to 3.6 cents/kWh for land-based systems (from a baseline of 5.5 cents/kWh in 2002). By 2014, reduce the cost of electricity from large wind systems in Class 6 winds to 7 cents/kWh for shallow water (depths up to 30 meters) offshore systems (from a baseline of 9.5 cents/kWh in 2005). By 2016, reduce the cost of electricity from large wind systems in Class 6 winds to 7 cents/kWh for transitional (depths up to 60 meters) offshore systems (from a baseline of 12.0 cents/kWh in FY2006). By 2007, reduce the cost of electricity from distributed wind systems to 10-15 cents/kWh in 2007 in Class 3 wind resources (from a baseline of 17-22 cents/kWh in 2002). By 2012, complete program activities addressing electric power market rules, interconnection impacts, operating strategies, and system planning needed for wind energy to compete without disadvantage to serve the Nation's energy needs. By 2010, at least 30 states with wind momentum needed to ensure wind’s continued growth.

2007 WIND ENERGY PROGRAM PEER REVIEW AGENDA July 11-12, 2007 Denver Marriott West, Golden, CO Day 1 (Wednesday, July 11) 7:15 am Registration & Continental Breakfast 8:00 am Welcome, Program Overview Perspectives (Steve Lindenberg, Bob Thresher, Jose Zayas) 8:20 am 20% Wind Vision Report (Ed DeMeo) Utilities and Transmission (Charles Smith) Markets and Acceptance (Larry Flowers) 9:05 am Review Objectives (Stan Calvert/ Mike Reed) 9:15 am Technology Application Overview (Steve Lindenberg) 9:30 am Systems Integration Overview (Stan Calvert / Brian Parsons) Renewable Systems Interconnection (Stan Calvert) SI Activity Overview (Brian Parsons)

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report 9:45 am 10:00 am

11:30 am 12:00 pm 1:15 pm

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

2:45 pm 3:15 pm 3:30 pm

4:15 pm 4:45 pm

339

BREAK Systems Integration Activities (Brad Nickell / Brian Parsons) UWIG (Charles Smith) Stakeholder Collaboration and Outreach (Mike Milligan) Integration Studies (Brendan Kirby) NWCC Regional Transmission (Ed DeMeo) Western Interstate Energy Board/WGA (Doug Larson) Western Wind Integration Study (Kevin Porter) Panel Q&A Lunch & 2006 Wind Energy Awards Presentation Systems Integration Activities (Continued) Wind and Hydro Integration (Tom Acker) Grid Simulators (David Corbus) Generator Modeling (Ed Muljadi) Wind Farm Data Monitoring (Yih-huei Wan) Wind Integration Technical Assistance (Brian Parsons) Resource Assessment and Modeling Expanding Capacity on Existing Grid New Transmission Planning and Expansion Education and Outreach on Transmission/Grid Integration Panel Q&A BREAK Market and Policy Analysis (Steve Lindenberg / Maureen Hand) AWEA Critical Issues and FERC Activity (Ron Lehr) Competitive Power Markets (Mark Bolinger) WinDS Modeling (Maureen Hand) Panel Q&A Recess / Peer Review Panel Discussions (Closed Session)

Day 2 (Thursday, July 12) 7:00 am Continental Breakfast 8:00 am Welcome / Review Objectives (Steve Lindenberg) 8:15 am Environmental and Siting (Brian Connor) Radar Mitigation and Impacts (Gary Seifert) National Wind Coordinating Collaborative (Abby Arnold) Wildlife Research (Bob Thresher / Karin Sinclair) 9:00 am Panel Q&A 9:30 am Technology Acceptance Activity Overview (Phil Dougherty/Larry Flowers) Communications and Outreach (Ruth Baranowski) 9:55 am BREAK 10:15 am Technology Acceptance Activities- State Outreach (Larry Flowers) High Priority States (Larry Flowers) Low-Medium Priority States (Steve Palomo) Agricultural Outreach (Marguerite Kelly) Regional Wind Institutes (Marguerite Kelly) Air Quality and Emissions (Lori Bird)

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

340

12:00 pm 12:30 pm 1:30 pm

3:15 pm 3:45 pm 4:00 pm

Economic Impact Analysis (Suzanne Tegen) Wind Mapping (Dennis Elliott) Panel Q&A Lunch Technology Acceptance Activities - Priority Markets (Larry Flowers) Native Americans (Bob Gough) Distributed Wind (Trudy Forsyth) Public power (WAPA) (Randy Manion) Wind for Schools (Larry Flowers) Federal loads/Greening DOE (Robi Robichaud) Federal Wind Siting Collaborative (Phil Dougherty) Panel Q&A Adjourn Peer Review Panel Discussions (Closed Session)

WIND PROGRAM PEER REVIEW PANEL FINDINGS

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The following is a summary list of the Wind Program Peer Review Panel’s main findings and comments: 1. The 20% wind vision analysis gives the program a coordinated and unified systems focus, which was previously lacking. 2. With the implications of the 20% wind vision, the systems integration (SI) and technology hardware R&D programs should increase coordination. The findings of the SI studies and models need to be integrated into the technology hardware R&D portfolio decision-making process. This will improve the overall architecture of the Wind Program research portfolio. 3. In evaluating the job creation and economic development impacts resulting from the 20% wind vision analysis, a coordinated federal program effort (possibly with the Department of Labor and/or USDA) is necessary to ensure that policies are designed to maximize domestic economic development by maintaining or increasing domestic market share and manufacturing capabilities, and that wind turbine manufacturing jobs are created in the U.S. (e.g., DOE’s Solar America Initiative has targeted support to commercial or near-commercial solar energy domestic manufacturing capabilities). The program should not assume that the U.S. will achieve all the potential benefits of the 20% wind vision without such a coordinated policy. 4. There is a major need for increased educational programs, coordination, and outreach with academia. Academia needs access to free, peer-reviewed, industry- accepted models, as well as the data to train future wind integration analysts. Furthermore, academic coordination between engineering and economics departments is necessary, as the wind industry requires interdisciplinary engineering skills. a. The need for recruiting, educating/training, and retaining skilled staff is prevalent throughout the wind industry, and implementing the 20% wind vision will increase this need. For example, more detailed time series

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

5.

6.

7.

8.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

9.

10.

11. 12. 13. 14. 15.

16.

341

modeling for wind integration and more resources for stakeholder outreach are necessary, which require an increase in properly trained staff in the wind industry. Greater collaboration is needed between the two sectors of SI activities within the Wind Program. One sector seems focused on studies, assessments, modeling and data analysis, while the second sector engages in person-to-person interaction and interfaces with industry groups, states and policy makers (e.g., AWEA and NWCC). EERE should coordinate more with other federal agencies both within DOE, such as the Office of Electricity (OE), and outside of DOE, such as FERC. If a major focus of the Wind Program is transmission issues, it is critical to interact with OE, which has DOE jurisdiction over national interest transmission corridors. Generally, there are good marks for each of the projects. Most of the projects are working toward the same end; that is integrating wind into a system that “doesn’t want it” or is slow to accept it. The WinDS, UWIG, WPA and AWEA projects are excellent uses of taxpayer resources. The Wind Program is commended for working with UWIG for several years, because significant benefits have come from this effort, and has had the greatest return on investment compared to all other Program activities. The AWEA project should focus on: a. Helping to bridge the gap between political and national policy needs; b. Coordinating and facilitating a meeting of wind developers and DOE staff, so that DOE can make its case for the need to obtain real-time data from developers for modeling and analyses; c. Establishing a consistent set of rules for getting detailed time series “proprietary” data from wind power plants, including what will be scrubbed, averaged or kept confidential, and the timing and frequency of its reporting; d. Integrating the findings of regional modeling and systems studies into a consistent, national-level framework that incorporates the best practices discovered in the state and regional studies; and e. Filling the political void at the state/federal nexus. Increased accounting of, and coordination with, planned upgrades to the transmission system are necessary to recognize the value added by wind and optimize its integration. The Wind Program should take into account the Canadian energy system, particularly for bordering states and power areas. The focus on the integrated planning of wind/hydro and wind/solar projects is applauded and continued activities in these areas are encouraged. The detailed models being developed by the Program need to directly or indirectly feed into NEMS and other national or international energy models. A clear, stable, long-term energy policy, similar to EU efforts, is necessary to foster market development and technology acceptance. Wind Powering America (WPA) should coordinate more with SI activities. As more wind sites are developed this will be an increasingly important endeavor for the 20% wind vision plan. As such, while WPA has been operating on a low budget in the past, it needs to become a more entrenched part of the Program’s activities.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

342

WIND PROGRAM PEER REVIEW PROJECT EVALUATIONS Systems Integration Activities The Systems Integration (SI) activities have become a major focus of the Wind Program’s efforts, in support of the “20% Wind Vision”, which will require significant attention to system operation and transmission needs and planning. These efforts are guided by the: •

•

Programmatic Goal - “By 2012, complete program activities addressing electric power market rules, interconnection impacts, operating strategies, and system planning needed for wind energy to compete without disadvantage to serve the Nation's energy needs”; and Advanced Energy Initiative – “Areas with good wind resources have the potential to supply up to 20% of the electricity consumption of the United States”.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Utility Wind Integration Group (UWIG) (J. Charles Smith – Executive Director) UWIG is a non-profit corporation established by six utilities in 1989 with support from EPRI and DOE/NREL, with a current membership of 111 organizations. The purpose of the UWIG project is to focus on the technical issues of wind integration, with a mission of accelerating the appropriate integration of wind power into the electric system.

Peer Review Panel Scores: Scoring Category

Average

Range

1.

Effectiveness

8.3

7-9

2.

Relevance

9.0

8-10

3.

Overall Impression

7.8

5-9

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

343

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Peer Review Panel Comments: The role of an organization such as UWIG is very important, and is seen as an essential mission effort. Many view the problem of wind deployment as an integration challenge, and UWIG is the primary group for the coordination of integration efforts. A key question is whether there are additional power regulation problems due to the introduction of wind, and power plants require 1 second- scale data on wind power output (for at least the first 100 MW of wind power) to confirm that the systems/winds are stable at scales longer than 1-second. The UWIG project is and should continue looking at these questions. The panel feels the project has produced mixed results, but the quality of work is excellent, vitally needed, and impressive considering the budget and resources. There is opportunity for program expansion in terms of topics and entities. During the presentation, a lot of information was presented (i.e., somewhat of a “trees for the forest” challenge), and additional synthesis would have been helpful. The panel feels that UWIG has had and can continue to have a major impact on systems integration; that the budget is money well spent, which allows technical information to flow to the Transmission Technology community; and that this project is instrumental in achieving the 20% wind vision plan.

Stakeholder Collaboration and Outreach (Michael Milligan – Consultant, NREL) This project is focused on bringing together collaborators (e.g., NREL, 3Tier, Renewable Northwest Project, UWIG, Renewable Energy Consulting Services, Xcel Energy, Minnesota PUC, Energy Systems Consulting Services, Northern Arizona University, Enernex Corporation, Arizona Public Service Company, CEC, GE Energy, Exeter Associates, UC Davis) to perform outreach activities with stakeholders (e.g., state and local government agencies, utilities, NGOs). The types of outreach activities include one-time or limited interaction with external groups by giving presentations or attending meetings, writing technical papers, ongoing close association with UWIG, and on-going technical assistance with wind integration studies. Peer Review Panel Scores: Scoring Category

Average

Range

1.

Effectiveness

7.5

6-9

2.

Relevance

8.8

7-10

3.

Overall Impression

8.0

6-9

Peer Review Panel Comments: The panel acknowledges that this is a proper role for NREL, a recognized national authority in wind integration. The outreach efforts help greatly to conform the processes of wind studies, which is needed so time and effort are not wasted comparing results that vary due to differences in assumption or methodologies. The stakeholder collaboration provides a forum for all views to be heard and an avenue for discussion without rancor, which are a much needed part of issue resolution. Informing States about the technical requirements for local power driven by wind and the need for other power sources to be flexible in scaling up or down to complement integrated

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

344

U.S. Department of Energy

wind (e.g., gas turbines scale up or down very poorly) is important. Original analyses are also conducted as part of these activities, adding to the body of knowledge. This is deemed important as resources are a severe limit to spreading techniques for wind analysis. The panel recognizes the relationship between this effort and UWIG, and suggests continuing collaboration with UWIG along with a call to inform members of the IEEE – PE community.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Integration Studies (Brendan Kirby – ORNL) This project provides technical analysis support for wind integration studies. Specific studies depend on regional and utility interest, with support often requested by regulators to assure a non-biased analysis. The SI expertise helps to ensure the technical validity of the studies and furthers DOE and NREL interests in advancing analysis methodologies. These studies allow for improvements in the state of the art of study methodologies; better understanding of wind integration impacts; identifying physical causes and costs that wind imposes on power systems; and learning how to minimize cost impacts. Specific analyses performed under this project include the Minnesota/MISO, California CEC Intermittency Analysis Project, Xcel/PSCo, Arizona Public Service and the Pacific Northwest Integration studies.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

345

Peer Review Panel Scores: Scoring Category

Average

Range

1.

Effectiveness

8.3

8-9

2.

Relevance

9.3

8-10

3.

Overall Impression

7.8

7-9

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Peer Review Panel Comments: The panel feels that there is a great need to continue this program. The approach and participation of different players in the field was of superior quality, and essential to achieve the goals of systems integration. A major barrier to the outreach program is a lack of DOE- or NREL-validated models for all states. Lack of validated models is limiting progress towards the 20% wind vision. The panel also believes that an important component of what is missing in the computation of raw data, in addition to developing the integration models, is the sheer manpower (i.e., having many more competent people to handle the various barriers facing wind integration).

NWCC Regional Transmission (Ed DeMeo – Renewable Energy Consulting Services) This project is designed to create a forum to facilitate collaborative discussion between different stakeholder sectors (e.g., SeaWest Windpower, FPL, Western Governors Association, AWEA, National Conference of State Legislatures, NREL, BP, UWIG) to reduce later adversarial proceedings in regards to transmission. Dialogue amongst stakeholders, as well as regulators, legislators, and energy policy leaders, functions to identify issues that affect the use of wind power and catalyze activities aimed at sustainable wind markets. The NWCC facilitates these types of information exchange through a number of different platforms including workshops, newsletters, web forums, and webcasts.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

346 Peer Review Panel Scores:

Scoring Category

Averag

Range

1.

Effectiveness

7.3

6-9

2.

Relevance

7.8

7-9

3.

Overall Impression

7.0

6-9

Peer Review Panel Comments: The panel feels that the NWCC is an effective outreach program, which is a much needed part of dispute resolution that provides real data. The presentation itself lacked some integral information regarding the approach and the people involved within the NWCC. The types of methods employed by the NWCC appear to not translate well into actual action on overall national transmission integration, indicating that “machinery” must be added to affect change after the dialogue has been completed on these issues. With continued participation, the NWCC conferences are essential to jumpstart a national RPS policy. However, to achieve this goal, members of the NWCC work groups must actively lobby state legislators to achieve a proactive integration policy.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Western Interstate Energy Board /WGA (Doug Larson – Executive Director) This project is designed to remove barriers to integrating variable wind resources into the western grid. The implementation of this project involves addressing barriers to transmission, barriers to small wind, and the development of financial incentives for wind, with the additional supplemental task of conducting a wind/advanced coal hybrid concept feasibility study.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

347

Peer Review Panel Scores: Averag

Range

1. Effectiveness

8.3

6-10

2. Relevance

8.8

7-10

3. Overall Impression

9.0

8-10

Scoring Category

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Peer Review Panel Comments: The role of the Western Interstate Energy Board/WGA in transmission planning and development is absolutely critical to achieving the 20% wind vision. The presentation was clear in its statement of objectives to achieve this goal. The panel feels that there needs to be more study of both coordination with Canada and in the area of additional integration of wind and hydro with the western grids. More studies are also needed in the area of sub-regional planning for grid integration. Further work by the Western Interstate Energy Board/WGA is absolutely necessary to realizing the role of wind in achieving the 20% wind vision through further integration and more streamlined transmission development processes.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

348

Western Wind Integration Study (Kevin Porter – Exeter Associates, Inc.) This study examines the operating and cost impacts due to the variability and uncertainty of wind and solar on the grid and to investigate mitigation options for those impacts. This study also supports both the Western Governor’s Clean and Diversified Energy Initiative (30GW by 2015) and the President’s Advanced Energy Initiative (20% Wind Vision). Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

6.8

5-9

2. Relevance

8.0

7-9

3. Overall Impression

6.7

6-9

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Peer Review Panel Comments: The purpose of the study was found to be quite relevant by the panel towards future work in this area. The study highlighted the linkages and benefits to WestConnect and other ongoing grid projects in terms of wind and solar integration. The panel found the presentation to have some gaps in information on strategic implications and outcomes. The ‘innovative’ aspects of the work were not clear; however, the presentation was able to thoroughly cover the basics of the study (purpose, goal, etc.) as well as smaller details associated with specific tasks.

Wind and Hydro Integration (Tom Acker - Ph.D., Northern Arizona University) This project is designed to show the benefits that wind and hydro integration have on operational flexibility, opportunity cost to hydro, and the value of energy/water storage. In doing so, a working group consisting of a number of collaborating organizations (e.g., Arizona Power Authority, Oak Ridge National Laboratory, BPA, SMUD, 3Tier, Windlogics, GE, U.S. Bureau of Reclamation, U.S. Army Corp of Engineers) hopes to identify and answer a number of technical, institutional, economic, and political issues associated with integrating wind and hydroelectric generation.

Source: U.S. Army Corps of Engineers, National Inventory of Dams. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

349

Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

7.5

7-8

2. Relevance

7.3

7-8

3. Overall Impression

7.3

6-8

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Peer Review Panel Comments: The presentation gave a good characterization of the importance and necessity of analyzing wind and hydro systems simultaneously in order to avoid optimizing just hydro. Specific constraints on a river/dam provide promising opportunities for cogeneration with wind. Although the potential may be limited due to regional geographies, wind/hydro integration is still essential in those regions. Although most of the panel believed the preliminary findings to be promising, some questioned whether the result from wind/hydro integration was practical. However, it is too soon to make any final judgments without more studies of applicability. The panel agreed that there was much potential in wind/hydro integration, but the prerequisite to bypassing political and public barriers was a thorough economic study to gain approval for pilot facilities and further field case studies.

Grid Simulators (Dave Corbus, NREL) This project is designed to model wind plant grid interactions to gain a better understanding of the impacts that wind plants have on the grid. A working group, which consists of NREL, DOE, and EnerNex Corporation, seeks to develop tools to simulate the

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

350

impact of wind plants on utility grids, familiarize grid operators with this impact, and allow utilities to evaluate wind power impacts on their control areas through hands-on training using wind simulators and models. Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

7.5

5-9

2. Relevance

8.0

6-10

3. Overall Impression

7.8

6-9

Peer Review Panel Comments: There is a definite need for this program as grid operators need exposure to wind metrics before they encounter it in real time. The presentation was exemplary in its statement of the study’s project goals, objectives, and approach. The panel found it hard to judge the overall quality of the project without it being complete. The models require further tweaking of details in order to match the models to actual conditions. Operator feedback in the final draft would be useful in further tailoring the programs to match the requirements of grid operators and utilities.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Generator Modeling (Ed Muljadi – NREL) This project represents a collaborative effort by NREL, CEC, and WECC to standardize wind generating models through the use of aggregate data to allow for model validation and equivalencing for different size wind farms. The project will further collaborate with UWIG, WECC, IEEE, utilities, wind developers or operators, and universities to gain access to data and disseminate the end results in order to give grid stakeholders reliable, validated models. Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

7.5

4-9

2. Relevance

8.3

6-10

3. Overall Impression

7.5

4-9

Peer Review Panel Comments: This work is absolutely necessary to create a standard method for accurate industry studies on interconnection impact assessments. The presentation was able to aptly create a delineation of the challenges of getting good data, particularly regarding ‘faults’ on the generator. Some on the panel believed that the driving need for this collaborative to handle these models and validation was not compelling – believing that OEMs should provide models so the industry and NREL can focus on wind farm equivalencing.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

351

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wind Farm Data Monitoring (Yih-huei Wan – NREL) The objective of this project is to collect long-term, high-resolution, actual wind power plant output data to analyze variability of wind power in order to provide data to study wind impacts on the power grid. Initially, a ~1,000MW portfolio of 14 wind farms located in Texas, Oklahoma, Iowa, Minnesota, and Oregon will be monitored with hopes of adding more wind farms in other regions in order to create a better characterization of wind power’s spatial diversity. This data will be made available to researchers and industry for model validation and integration studies.

Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

6.8

6-8

2. Relevance

8.5

8-9

3. Overall Impression

7.3

6-8

Peer Review Panel Comments: This project is indispensable due to the need for a longterm dataset with a common format for a relatively new technology like wind. This project has demonstrated a successful pursuit of goals. The presentation was very useful in its use of data on wind farm performance and variability. However, it would have been useful to see monitoring data as well as a comparison of daily, seasonal and inter-annual

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

352

variability. The presentation seemed to miss the big picture in failing to suggest necessary means for data dissemination for maximal benefit of consumers.

Wind Integration Technical Assistance (Brian Parsons – NREL) This project focuses on four areas: Resource Assessment & Modeling; Expanding Capacity on the Existing Grid; New Transmission Planning & Expansion; and Education & Outreach on Transmission/Grid Integration. The purpose of this project is to decrease barriers associated with the siting and existing line capacity to benefit the upstream wind resource. Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

6.8

6-8

2. Relevance

8.8

8-9

3. Overall Impression

8.0

8-8

Peer Review Panel Comments: This report provides a well-focused list of tasks, which has been tailored to support the wind program’s missions and goals. The panel feels that there was insufficient time to assess productivity and accomplishments. Despite the unfinished work, it is clear that there needs to be more staff doing this type of work, which is essential to forecasting necessary future activities in the wind industry.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Market and Policy Analysis The Market & Policy Analysis activities provide information and analysis to stakeholders seeking to include wind energy generation in the electric power market controlled by incumbents. For these efforts, approximately $1.185 million dollars have been allocated as follows:

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

353

AWEA Critical Issues and FERC Activity (Ron Lehr – AWEA) This project represents a five-year contract awarded to AWEA, which has the objective of investigating the critical issues for wind deployment. AWEA has four broadly defined task areas: 1) develop information products; 2) targeted outreach; 3) broad dissemination; and 4) final report and performance metrics. For the first two intertwined tasks, AWEA has conducted a number of seminars/meetings relevant to forecasting as well as transmission and interconnection with system operators. To ensure the broadest dissemination possible, AWEA plans to complete a White Paper by the fourth quarter, 2008. As a concluding task, AWEA’s final report will assess performance metrics based on outreach performance and record operator issues that were not addressed. Peer Review Panel Scores:

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Scoring Category

Average

Range

1. Effectiveness

5.3

3-8

2. Relevance

6.0

4-8

3. Overall Impression

5.5

4-8

Peer Review Panel Comments: AWEA’s particular project area is quite relevant to the goals and is necessary to move forward toward the 20% wind vision. The presentation was able to convey a clear picture of project goals and objectives. The presentation failed to provide very much detail concerning the accomplishments to date under this particular “Critical Issues” contract. In moving forward, the panel feels that it is very important to carefully word any materials being put forth for broad dissemination. The panel feels this project was weakened by the fact that there was an interruption in progress due to the loss of a project manager, which significantly reduced the speed and focus of the project. The panel further questioned the need for this effort as it appeared that AWEA’s tasks were redundant with other separate efforts, and therefore suggests specific focuses for this project to take in future years.

Competitive Power Markets (Mark Bolinger – LBNL) These projects are part of the Lawrence Berkeley National Laboratory’s (LBNL) portfolio of wind-related tasks involving economic, market, and policy analysis. Approximately $375,000 is allocated by the DOE to LBNL’s Wind research budget. Within this budget, LBNL publishes a number of annual, publicly available reference documents summarizing key trends in the U.S. wind market, with a focus on the year just ended. These reference documents include the “Annual Market Data,” which covers such topics as wind turbine prices, wind project performance, O&M cost trends, evolution of wind pricing, as well as a prediction of what the remainder of 2007 will hold for the aforementioned variables. LBNL’s second main area of interest regards wind project financing structures, where their goal is to survey the principal financing structures currently being used for wind projects, and publish a report describing their mechanics, as well as their impact on the cost of wind energy.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

354

Third, LBNL analyzes wind’s impact on property values (8-12 wind farm sites, with data collected on house values within a 5-7 miles radius of the wind farm) where their objective is to use state-of-the-art field methods and statistical models to evaluate the impact of wind projects on local property values. Peer Review Panel Scores:

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Scoring Category

Average

Range

1. Effectiveness

7.3

6-9

2. Relevance

8.3

8-9

3. Overall Impression

7.5

6-8

Peer Review Panel Comments: A competent effort was made on the part of LBNL to present high quality information on the activities involved in fully realizing the potential of wind. The panel feels that more time should have been spent on key details, and insights from recent reports would have added much to their report. LBNL needs to address the relative impact that increases in such essential items as steel, copper, etc. will have on cost increases in the price of wind. A further examination of transmission costs is necessary to create a more comprehensive forecast for cost recovery on wind projects.

WinDS Modeling (Maureen Hand – NREL) This project focuses on further refining the WinDS (Wind Deployment Systems Model) model to conduct analyses of the national potential of wind energy under different policy and technology scenarios to assess R&D opportunities, identify market barriers, and evaluate policy initiatives. WinDS is designed to address the principal market issues for wind, which included access to and cost of transmission as well as resource variability.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

355

Peer Review Panel Scores:

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Scoring Category

Average

Range

1. Effectiveness

8.3

8-9

2. Relevance

8.5

8-9

3. Overall Impression

8.5

8-9

Peer Review Panel Comments: This project is a key strategic effort to assure program efforts are prudently focused, as well as an important program management tool. The panel found that the transmission model being presented by WinDS was somewhat weak. One further weakness was the MISO model that was utilized with full constraints only had about a six-day duration per year of study, which may have been a limiting factor in terms of sample size. However, with a few tweaks the panel feels the project can provide a good long-term overview of market potential in the U.S.

Environmental and Siting The goal of the environmental and siting programs is to conduct research and outreach to overcome significant barriers to the construction of wind installations. The most prominent of these barriers include the delay or cancellation of wind farms because of radar interference issues and/or wildlife interaction issues. Radar and wildlife concerns have the potential to prevent attainment of the Program’s 20% wind vision. As a result, the bulk of environmental and siting funding is directed towards addressing these two issues.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

356

Radar Mitigation and Impacts (Gary Seifert – INL) This is a relatively new effort by Idaho National Laboratory (INL) to help ensure that radar interference issues are not a significant barrier to wind development. The project achieves its goals by performing case studies, engaging regulatory agencies, and identifying ways in which radar interference can be mitigated.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

7.2

6-9

2. Relevance

9.2

8-10

3. Overall Impression

8.2

6-9

Peer Review Panel Comments: The panel agrees that radar interference is an important issue that needs to be dealt with, as it can present a major barrier to the development of a wind farm. The presentation provided a good overview of the project, and the panel praises the effort’s scope, approach, and management. The reported “slow start” for the project is unfortunate given the evident importance of the issues involved. A possible improvement to the project would be the use of more concise metrics to gauge success. Another possible goal for the project going forward should be for political processes to be coordinated to obtain legislation to create a single contact (i.e., a “one stop shop”) for both the FAA and the military.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

357

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

National Wind Coordinating Collaborative- Wildlife Workgroup (Abby Arnold RESOLVE) The National Wind Coordinating Collaborative (NWCC) Wildlife Workgroup provides a forum for stakeholders to find solutions to wildlife issues and problems related to wind development, such as impacts on birds and bats. The NWCC Wildlife Workgroup conducts research on these issues and helps to disseminate relevant information to stakeholders.

Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

8.4

8-9

2. Relevance

9.2

8-10

3. Overall Impression

8.8

8-10

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

358

Peer Review Panel Comments: This is an important area for funding because it is necessary to have answers to potential wildlife concerns because of the possible denial of sites for wind development. Even though the problem is expansive and it is difficult to quantify results, it is important to address because it will pose a “clear and present barrier” to the 20% wind vision as deployment scales up. The project has made significant gains in a difficult area showing a thoughtful, careful effort and effective focus on a multi-faceted issue. The presentation provided a good overview of the project’s status and further challenges. The presentation could have been clearer – perhaps by pulling forward the high level information concerning the project. Still, more work needs to be done in accord with other agencies because many wind sites face unique wildlife issues.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wildlife Research (Karin Sinclair – NREL) Wildlife research at NREL and the National Wind Test Center (NWTC) is focused on conducting credible research on the problem of wind-wildlife interaction and finding ways to mitigate the problem. The findings of this research are distributed to relevant stakeholders.

Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

8.0

7-9

2. Relevance

8.4

8-10

3. Overall Impression

8.4

8-9

Peer Review Panel Comments: Addressing wildlife concerns is a tough but essential job given their complexity and site-specificity. It is a difficult area for engineers to comprehend, but it is an important issue because of the number of wind sites that have been denied already, and if not remedied, will continue to be a problem. The panel feels that the presentation did a good job of presenting the project’s purpose, approach, and specific tasks. The presentation was a quality effort providing necessary attention to technical and policy barriers to the 20% wind vision.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

359

The presentation lacked data on the impacts of the project, and requires more information about how many before-and-after studies have been done as well as more attention to the “Fly Way 5.” The topic of wildlife research has been under-emphasized in the context of the 20% wind vision.

Technology Acceptance Activities – State Outreach

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Technology acceptance activities are carried out under the leadership of the Wind Powering America (WPA) program. These activities can be grouped into those focused on State Outreach, which target states and regions where wind development can benefit the most from an additional effort, and Priority Markets, which target interest groups that are likely to be important players in wind development. WPA’s goal is the installation of at least 100 MW in each of 30 different states by 2010. The program works primarily though the creation and dissemination of targeted information, analyses, and tools, and by working with and creating strategic partners and working groups.

High Priority States (Larry Flowers – NREL) This aspect of WPA is focused on developing wind capacity in 13 states (e.g., Alaska, Arizona, Indiana, Maryland, Massachusetts, Michigan, Nebraska, Nevada, North Carolina, Ohio, South Dakota, Utah, and Virginia) that are identified as priority states based on their

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

360

installed wind capacity, the effectiveness of the Wind Working Group in that state, and the policy environment in that state.

Peer Review Panel Scores:

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Scoring Category

Average

Range

1. Effectiveness

9.0

8-10

2. Relevance

9.4

9-10

3. Overall Impression

8.8

8-10

Peer Review Panel Comments: The focus on state-level education is an appropriate response to the current policy environment. The panel identifies this program as the “spark plug” in getting wind Renewable Portfolio Standards (RPS) approved by states, which is seen as an effective tool to achieve the 20% wind vision. The panel regarded the program’s leadership by Larry Flower’s as overwhelmingly positive, calling him “a super salesman for wind.” The program is exemplary in its precise performance metrics, its tangible results, its effective leverage of state programs, and its broad contribution and support. The program understood the necessity of starting small and getting at least one project installed in regions and states that are currently lagging. One panelist comments that the presentation was mostly organizational, and that more detail on best practices/lessons learned and how these can help the efforts in medium- and low-priority states was needed. Furthermore, it was suggested that the Regional Transmission Organizations (RTO) should be treated as utilities are and coordinated with in WPA’s regional focus.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

361

Low-Medium Priority States (Steve Palomo – DOE/WPA) This aspect of WPA is focused on developing wind capacity in 21 states that are identified as low or medium priority states based on their installed wind capacity, the effectiveness of the Wind Working Group in that state, and the policy environment in that state. Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

8.2

8-9

2. Relevance

9.2

8-10

3. Overall Impression

8.4

7-10

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Peer Review Panel Comments: Again, the focus on state-level education is an appropriate response to the current policy environment, and this program is a good way to spark wind development in states that have been lagging. The panel praises the speaker for his enthusiasm and his good overview, and again cites WPA for its good leadership and broad contribution and support. The medium and low priority states are an area that would benefit from funding increases, which could facilitate more interaction with the high-priority states effort (e.g., including sharing best practices/lessons learned). The presentation itself was mostly organizational and could have discussed the project activities in more detail, and one panel member questioned whether WPA has a “toolkit” similar to the NWCC.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

362

Agricultural Outreach (Marguerite Kelly – DOE/WPA) This aspect of WPA is focused on building acceptance of wind technology in rural areas. The program’s objectives are increasing awareness of the benefits and issues of wind energy in rural areas, providing information to decision makers from multiple credible sources, increasing support for wind energy development among rural leaders and residents, and providing information about opportunities for local ownership and economic development. Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

8.4

8-9

2. Relevance

8.8

8-10

3. Overall Impression

9.0

8-10

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Peer Review Panel Comments: The panel believes this effort is important, including the fact that the magnitude of transmission and distribution infrastructure located in rural areas will make these areas critical to achieving the 20% wind vision. The panel applauds the clear and logical presentation. The effort is a prudent part of a plan to achieve the 20% wind vision, and the panel praises the effort for taking advantage of diverse opportunities to promote wind. In particular, the panel likes the project's emphasis on best practices and on bringing in interested people at the local level to accelerate the effort. The panel suggests a tie to energy markets would greatly improve the economics of this program, and suggests that LBNL may be able to help with that.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

363

Regional Wind Institutes (Marguerite Kelly – DOE/WPA) This part of WPA is focused on developing a support system for priority states, developing a Strategic Wind Outreach Team in each state, and addressing key regional issues, with an emphasis on building in-state human capacity. Three Regional Wind Energy Institutes (RWEI) have been established, including the Great Lakes led by Windustry, the Mid-Atlantic/Southeast led by the Southern Alliance for Clean Energy, and the Southwest led by the CORE Foundation. Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

7.2

6-8

2. Relevance

8.0

7-9

3. Overall Impression

7.6

6-9

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Peer Review Panel Comments: The panel feels that this program is a prudent step towards realizing the 20% wind vision and an appropriate compliment to other efforts. The panel feels this project can lead to increased coordination with RTO’s and utilities, which is important for transmission to be developed to a point that it can support 20% wind generation on the system. The focus, quality, and clarity of this effort indicate a good way to achieve state collaboration in forming an effective strategy for spreading best practices. However, one panel member notes that the focus and purpose of the institutes needs to be clearer.

Air Quality and Emissions (Lori Bird – NREL) In partnership with AWEA, NREL, SEAC, and consultants, this aspect of WPA focuses on creating and disseminating information on the air emissions benefits of wind development. Wind power presents opportunities for states to meet air quality goals (e.g., SIPs), mitigate air quality violations (e.g., SEPs), and formulate cap-and-trade programs and carbon reduction strategies. Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

7.0

6-8

2. Relevance

8.5

8-10

3. Overall Impression

7.3

7-8

Peer Review Panel Comments: The panel finds that this project is important for establishing the benefits of wind and renewables in general, and for informing states about how wind can help achieve air emissions objectives, which will become an even bigger issue in the future.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

364

This project has an effective approach and a prudent strategy, with a great deal of attention to high quality inputs and outputs. However, it is unclear how this project connects with the modeling and other studies being conducted as part of the systems integration activities, and the panel felt that some coordination with WinDS may be useful. The panel suggests this project be better thought through, more up to date, and more ambitious in targets and in partnering with entities such as the EPA.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Economic Impact Analysis (Suzanne Tegen – NREL) This project by WPA conducts analyses and distributes information on the economic development benefits of wind, including job creation, property tax increases, land leases, and increased revenue. These impacts can be seen as direct impacts both on- and off-site, indirect impacts of payments made to supporting businesses, and induced impacts of money trickling through the local economy.

Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

7.8

7-9

2. Relevance

8.2

7-10

3. Overall Impression

8.2

7-9

Peer Review Panel Comments: This project provides some of the background data that is needed for wind to make a breakthrough, and as such it is a prudent part of the effort to achieve the 20% wind vision. The panel praised the project for its good management, good analysis, and concise results. However, some additional information on the details of the project, rather than the

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

365

JEDI model, might have been useful for the panel to review this project. Moreover, there is an apparent need to show transportable insights relative to labor and direct/indirect multipliers.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Wind Mapping (Dennis Elliott – NREL) This effort is conducted by NREL and supported by several consultants (i.e., AWS Truewind and V-BAR) and state energy offices/organizations. Wind resource maps are generated for 50 m elevation and 70 to 100 m elevation. The purpose of this project is to provide validated wind resource data needed by policy makers, state officials and wind developers.

Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

9.0

7-10

2. Relevance

9.8

9-10

3. Overall Impression

9.2

7-10

Peer Review Panel Comments: The panel feels that this project is very important, as it gets people to realize that there are wind resources at specific locations. This is extremely important for fostering policy and development efforts, and is essential for advancing the 20% wind vision, with the case of Indiana’s RPS being a good example.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

366

U.S. Department of Energy

The panel also praises the high quality of the management, results, and impacts for the project, with one panel member noting the presentation was “very succinct and useful.” The panel calls for the creation of more maps and an increase in resources for this effort, with individual states being a possible source of resources, and emphasizes the importance of adding a time-series element to the data to allow for the creation of seasonality and daily profiles and analysis of variability and other statistical topics.

Technology Acceptance Activities – Priority Markets Native Americans (Bob Gough - Secretary, Intertribal Council on Utility Policy) This WPA project seeks to foster the development of wind resources on Native American lands. Activities include the creation of wind maps, an anemometer loan program, and outreach and training efforts.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

367

Peer Review Panel Scores:

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Scoring Category

Average

Range

1. Effectiveness

8.0

7-10

2. Relevance

8.8

7-10

3. Overall Impression

8.0

7-10

Peer Review Panel Comments: The panel finds that this work is a valuable contribution to the 20% wind vision, particularly with the magnitude of wind resources on Native American land. The panel feels that the work being done is very good and innovative, and that the presentation was interesting. However, the presentation is criticized for not addressing the objectives, approach, and budget/schedule of the project. Furthermore, the anecdotal approach to the presentation made it difficult to compare to other projects. One panel member suggests trying to find opportunities for linking this effort into other program activities and applying lessons learned to other WPA efforts. Another panel member recommends increased efforts be undertaken to identify a market for wind energy produced on reservations, possibly through green tags, and study how transmission factors might impact these efforts.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

368

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Distributed Wind (Trudy Forsyth – NREL) This WPA effort seeks to foster broad acceptance of small-scale distributed wind by creating consumer guides, economic tools, and conducting installer certification. This effort is in conjunction with the Interstate Renewable Energy Council, the American Solar Energy Society, the USDA, and rural stakeholders.

Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

7.8

7-9

2. Relevance

7.8

7-9

3. Overall Impression

7.5

7-8

Peer Review Panel Comments: The panel feels that this effort is not as significant as others in terms of its contribution to attaining the 20% wind vision, but that based on public response it is clearly filling a need. The panel praises the hard work on this effort, feels the presentation gave a good overview of the project, and notes that this project’s leveraging and partnering with other organizations, particularly the solar industry, is excellent. The panel feels that the presentation could have contained a more detailed plan of future action and a more strategic perspective on how this effort contributes to the 20% wind vision, and also would like to have seen economic data on the cost of distributed wind electricity relative to grid electricity costs.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

369

Public Power Partnership Program (WAPA) (Randy Manion – WAPA) This WPA effort is focused on communicating information about wind and its benefits to the nation’s 2900 consumer-owned utilities. Consumer-owned utilities represent 13.5% of the Nation’s energy generation (approximately 142 GW), and while they are free to choose the generation technologies of their liking, they can play a vital role in alleviating the transmission constraints and other barriers to wind development.

Peer Review Panel Scores:

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Scoring Category

Average

Range

1. Effectiveness

6.8

5-9

2. Relevance

7.0

5-9

3. Overall Impression

7.3

7-9

Peer Review Panel Comments: The panel feels that this is an important and appropriate niche to be filled towards achievement of the 20% wind vision, even though its overall contribution to the goal is likely to be small. The panel feels that this effort is well- organized, and praises the presentation for its detail and organization. One panel member suggests more focus be devoted to synthesizing and disseminating best practices/lessons learned, and to include or partner with non-wind renewable projects for the effort’s case studies.

Wind for Schools (Larry Flowers – DOE/WPA) The goal of this WPA effort is to engage rural America and rural school teachers and students in wind issues and to equip college juniors and seniors with the interest and tools the wind industry needs to grow. The Wind for Schools project approach is to assist the community and local utility to implement a sustainable school wind project using a low- cost replicable system, work with AWEA/NEED on K-12 curriculum, build in-state capacity to provide TA for community-scale projects, and work with State Universities on college-level program and curricula.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

370

Peer Review Panel Scores:

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Scoring Category

Average

Range

1. Effectiveness

8.0

7-9

2. Relevance

8.0

7-9

3. Overall Impression

8.4

7-10

Peer Review Panel Comments: Panelists feel that this program is useful for its role in training new people in the wind industry and familiarizing communities with wind. The panel feels that the modest funding level appropriately reflects the fact that this project is likely to have a smaller impact on the 20% wind vision than other projects. The panel feels that the project is well organized and managed, and praises the project for its creativity in managing hardware funding. One panel member suggests a greater geographic diversity for the project, and another suggests that state working groups or the financial leverage of states with renewable benefit funds could be used to expand the project beyond more than a handful of deployments. Finally, the panel feels that three years is too short of a timeframe for building capabilities and curricula at colleges, and suggests this timeframe be extended.

Federal Lands/Greening DOE (Robi Robichaud – NREL) This WPA program is designed to take advantage of renewable energy mandates for federal programs by fostering partnerships with federal agencies to develop wind projects. The project’s objectives include entering into 3 Interagency partnerships by

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

371

2007, identifying at least 20 viable wind projects at Federal agencies by 2008, demonstrating at least 1 wind power purchase arrangement between the Federal and private sectors by 2009, and providing technical assistance that leads to 10 new wind turbine projects at Federal sites by 2010.

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

7.0

5-8

2. Relevance

7.8

6-10

3. Overall Impression

7.0

4-8

Peer Review Panel Comments: The panel finds this program useful because it taps into federal policy requirements for renewable energy purchasing and because it shows that the government can “walk the talk.” The project has a good scope and is well-planned, with planners looking at a variety of alternative approaches. The panel feels the program has made good progress for its short life, but cautions that it may be a bit early to judge. The panel suggests that instead of only looking at federal wind projects for the lessonslearned aspect of the program, the program might look at all types of renewable projects, particularly the government’s experience with solar. Also, the panel feels that the project’s objective is not well-stated and that the presentation did not communicate how the project fits into WPA and the high priority states program. Finally, the panel cautions that the substantial resources required for this effort would not be worthwhile unless the funding can be leveraged, possibly through a public-private partnership.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

372

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Federal Wind Siting Collaborative (Phil Dougherty – DOE) This WPA effort was created in response to the wind-radar interference issue. The collaborative is a team composed of people from a variety of agencies that are relevant to wind development. The focus of the program is to create real-time interactions on information and technology exchanges, provide limited DOE technical assistance and facilitation to agencies and industry, and develop a Federal Wind Siting Information Center.

Peer Review Panel Scores: Scoring Category

Average

Range

1. Effectiveness

6.7

5-8

2. Relevance

9.0

7-10

3. Overall Impression

8.3

8-9

Peer Review Panel Comments: The panel has few comments on this presentation; however, the panel applauds that this essential effort has started. The panel feels that a multi-agency pre-approval screening for “show-stoppers” for states and developers might be helpful, and that an assessment of this effort in the context of the 20% wind vision would be useful.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

373

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

SUMMARY OF PEER REVIEW PANEL SUGGESTIONS AND PROGRAM RESPONSES 1. There is a major need for increased educational programs, coordination, and outreach with academia. DOE response: The Wind and Hydropower Technologies Program agrees that there is a major need for increased educational programs, coordination and outreach with academia. The Program continues to advance its coordination with NREL and Sandia in its efforts to broaden the educational opportunities and initiatives that are intended to increase the size and widen the capability of the future workforce that serves the wind industry. The DOE, in concert with the National Laboratories, the U.S. wind industry, and AWEA estimates that nearly 500,000 jobs could be supported by 2030 if the 20% wind scenario is realized. These positions will be best served if universities, community colleges and the K-12 schools are supported to educate and inform about wind technologies and opportunities. The Wind for Schools project is being piloted by Wind Powering America in FY07 with plans to expand beyond the original six participating states in FY08, and will eventually be applied in all WPA high and medium priority states if funding permits. One of the key focuses of this project is to develop wind application centers at universities in each state, developing curricula and creating a coordinated university wind network. The Program intends to expand its partnership with Universities through solicitations aimed at furthering coordinated educational and outreach activities, especially if Congressional appropriations allow for these increased activities in our budget. In addition, the Program plans to work with the Power Systems Engineering Research Center, a collaboration of power systems university programs, in FY08 to provide funding support and stimulation for wind integration research at Universities. In addition, NREL and Sandia continue to expand participation in established laboratory intern programs that support students from undergraduate to PhD level. Examples include the DOE “Student Undergraduate Laboratory Internship” program, NREL’s “Research Participant Program”, and direct laboratory subcontracts with university partners for professor-directed student support of Program activities. The Wind Program has a proven track record of leveraging such programs to attract promising high-caliber science and engineering students to wind energy technology. The laboratories also have strong post-doc and visiting professional programs that match the expertise of these highly skilled individuals to specific Program areas of need. Typically, 10-20% of DOE Wind Program laboratory staff are student interns and post-doc researchers. The Program is acutely aware of its responsibility to support development of the next generation of wind professionals and help ensure that they are well prepared to contribute toward the goals for future growth of deployment of wind power. The Program has also provided funds in technical assistance to a number of organizations to develop programs and curricula such as Iowa Lakes Community College and St. Francis University. 2. A coordinated intra-federal program effort is necessary to ensure that policies are designed to maximize domestic economic development by maintaining/increasing domestic market share and wind-turbine manufacturing jobs in the U.S.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

374

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

The Wind and Hydropower Technologies Program understands the importance of the U.S. market for wind technology and the impacts that federal and state policy play in the development of that market. To the extent possible, the Program seeks to promote policies that will support U.S. manufacturers or expand domestic wind energy related economic development. Through the Department of Energy the Program does work to inform policy makers, on the state and federal level. The Program is currently in the process of expanding technical support in the area of manufacturing, building on the industry testing work that has been a mainstay of the Program for many years. It is clearly felt that the expansion of the Program’s new large wind turbine blade testing facilities will support the U.S. manufacturing sector, and eliminate the need to transport U.S. manufactured wind turbine blades to Europe for certification testing. Further, the Program included manufacturing as a research area of interest in its first call for proposals that was released in September 2007 under the Collaborative Research and Development Agreement Opportunity for the Research and Development of Systems and Components for Utility-Scale Wind Turbines and Ocean Energy Technology. The Program also actively engaged in the Federal Interagency Wind Siting Collaboration which was formed to address the siting issues within the purview of federal agency missions. The broad and diverse siting requirements and policies in place across federal agencies, such as the Department of Defense, Transportation, Homeland Security, Commerce, and Interior, have delayed the development of many wind projects. The federal collaboration will continue to expand the understanding of wind across federal agencies, unifying requirements, and make tools available to ensure compliance and timely approvals for wind projects. 3. SI Collaboration The systems integration (SI) and technology hardware R&D programs should increase coordination. Findings from the SI studies and models need to be integrated into the technology hardware R&D portfolio decision-making process. This will improve the overall architecture of the Wind Program research portfolio. DOE Response: The Wind and Hydropower Technologies Program has also recognized this need for more coordination between the Systems Integration and Large Turbine Technology R&D activities, and has begun exploring areas of common ground to better facilitate coordination. The Program has initiated a new Gearbox Reliability Collaborative R&D activity that will necessitate strong ties to the needs of SI power industry partners. One specific area of support requested by industry is in the design and testing of integrated drivetrain systems (gearbox, generators and power electronics) to meet anticipated electric grid-fault ride-through standards. Test results will be used to refine turbine drivetrain models used by SI power system modeling codes to better simulate wind farm level grid impacts. The Program’s Reliability Collaborative and Systems Analysis R&D activity is focusing on optimizing operations and maintenance practices and improving wind turbine performance and reliability. This work is being done through industry partnerships, including the Utility Wind Integration Group’s (UWIG) Wind Turbine O&M User Group and the American Wind Energy Association’s O&M Working Group. The UWIG O&M User Group plans to survey UWIG members on O&M research needs that will be useful to prioritize Program R&D activities. Another opportunity for increased collaboration will occur in FY08 as the Program’s R&D resource assessment activities are expanded to support meso-scale modeling needed for ramped-up SI wind integration transmission studies.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

375

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Greater collaboration is needed between the two sectors of SI activities within the Wind Program in order to create better exchange, use and application of data. NOTE: We believe that this question is referring to the two major parts of SI: “Tools & Methods Development” vs. “Application & Implementation” (i.e. research vs. outreach). DOE Response: The Wind and Hydropower Technologies Program’s SI application and implementation activities rely heavily on factual information and data produced by other SI staff conducting studies and testing to develop new wind grid integration tools and methods for the power industry. The Program agrees with the Peer Review committee that increased collaboration between these two internal SI groups would benefit both, and improve SI’s ability to better support power industry wind integration needs. FY08 plans include increased SI staffing and project activities in both of these SI groups. SI project leaders are aware of the need for increased collaboration and have restructured SI management strategies accordingly. Also, greater levels of collaboration are already evident in that recent ramped-up SI integration studies (e.g. meso-scale modeling and transmission planning) have necessitated increased coordination and interaction between the groups. 4. The A WEA project should focus on coordination and facilitating a meeting of wind developers and DOE staff in order to obtain real-time data from developers for modeling and analyses. DOE Response: Coordination with stakeholders is in progress. There have been two major Wind Turbine Reliability workshops in addition to the Gearbox Reliability Collaborative. Real-time data has been collected and data partners are being recruited. The data warehouse infrastructure development is currently underway at Sandia, and has been populated with data from one of the data partners. Failure data will be used for baseline statistics while real- time data may be more helpful in forensic analysis of individual component failures. Additional meetings are anticipated including a meeting with wind farm operators and reliability engineers planned in the spring of 2008 that will include modeling and analyses as part of the meeting agenda. 5. Increased accounting of, and coordination with, planned upgrades to the transmission system are necessary to recognize the value added by wind and optimize its integration. DOE Response: The Wind and Hydropower Technologies Program plans to continue to expand collaboration on wide area, high penetration wind interconnection studies in FY08. DOE is an active participant in studies being conducted by regional transmission organizations, providing expert wind integration advice and wind regime modeling support. The Program will continue its active representation of wind characteristics at regional transmission planning processes and through the National Wind Coordination Collaborative (NWCC) Transmission Workgroup activities and regional meetings. This activity increases wind participation and coordination in regional and sub-regional transmission expansion forums, including WECC, MISO, and SPP reliability regions. 6. The detailed models being developed by the Program need to directly or indirectly feed into NEMS and other national or international energy models. DOE Response: The Wind and Hydropower Technologies Program has invested in the development of the Wind Energy Deployment System (WinDS) model in order to best Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

376

U.S. Department of Energy

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

represent the unique nature of a geographically dispersed resource. The capability of WinDS exceeds the capability of NEMS to model regional variations. However, the WinDS model was used in a project initiated by EIA to re-evaluate multipliers that are used by NEMS to incorporate some of these regional variations. The WinDS modeling team also has provided many comments and suggestions to the developers of the wind module of the PNNL MiniCAM global climate change model. In addition to these personal interactions, the Wind Program seeks to provide information on methods of modeling wind energy used in the WinDS model through publications. By sharing these methods, it is hoped that other developers can incorporate these ideas or data into other national or international energy models. In addition to modeling methods, input data to these models is critical. The Program produced the first of what is intended to be an annual publication of the status of the wind energy industry in the U.S. As additional data is collected and refined, the information presented will cover more aspects of the wind industry. This resource should be valuable to energy modelers requiring accurate cost and performance data for wind technology. 7. Wind Powering America (WPA) should coordinate more with SI activities – WPA needs to become a more entrenched part of the Program’s activities. DOE Response: Although not highlighted in the presentations, coordination between the WPA and SI activities occurs on a regular basis. WPA outreach efforts to the power industry rely heavily on factual information and data resulting from SI studies and activities. The Power Partnerships activity within Wind Powering America has historically been the conduit between WPA and SI in providing information to consumer- owned utilities. The Program agrees that increased coordination and integration between SI and WPA in this area will benefit both. FY08 plans include increased SI staffing and project activities focused on providing information needed to better support WPA and other Program outreach activities to the power industry. New staffing will enable increased public outreach on wind grid integration and transmission issues, and will also enable greater SI representation at WPA outreach events such as State Summit meetings. 8. The Wind Program should take into account the Canadian energy system, particularly for bordering states and power areas. DOE Response: The Program, through AWEA, is collaborating with the Canadian Wind Energy Association (CanWEA) on a transmission workshop to discuss wind and transmission challenges and the solutions being pursued throughout North America. The Wind Program agrees that more coordination with and account of the Canadian energy system, particularly in the Northeast and Northwest is needed.

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind and Hydropower Technologies Program. 2007 Peer Review Report

377

APPENDIX A: LETTER FROM CARL WEINBERG TO STEVE LINDENBERG, PRELIMINARY FINDINGS OF THE PEER REVIEW PANEL Steve Lindenberg Program Manager, Wind and Hydropower Technologies Program U.S. Department of Energy Carl Weinberg 42 Green Oaks Ct Walnut creek, CA 94596 September 2, 2007

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Dear Steve, The following preliminary findings are presented on behalf of the membership of the Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) Wind and Hydropower Technologies Program Review Panel that met on July 11- 12, 2007 in Golden, Colorado. The review focused mainly on the System Integration activities of the Program on the first day, and the Technology Acceptance activities on the second day. The Panel commends the program for formulating the “20% wind vision”, a vision of achieving 20% of US electrical energy to be produced by wind power, to serve as a coordinated and unified program focus. The program provides US taxpayers with excellent value. The program clearly has taken into account previous recommendations of the Panel. The Panel is also aware that changes in Administration often impact overall goals. We urge continued planning and strategy underpinning to allow R&D, not only on technology, but also the technology-system interface in order to foster a long term energy policy.

Strategic and Program Level Recommendations In order to implement the 20% wind vision there is a need for increased coordination of wind projects within DOE, other departments of the Administration, as well as States and Utilities. Wind System Integration needs to consider the Office of Electricity for transmission issues, the EIA for inclusion in the NEMS model, the Department of Agriculture, state-level activities stemming from RPS policies, and even FERC for overall electricity system policy direction. The need for the increased coordination will make highly skilled labor even more important for the Wind Program. The availability of skilled personnel will become crucial as the industry expands, and there is a crucial need for recruiting, educating, training and retaining the labor force. Engineers, economists, and planners need to be trained at universities. While the panel touched on this need, it is not clear, who, how or what the role of the Wind Program should have in fulfilling this need. The panel would suggest some discussion of this issue at future Peer Review Panel meetings

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

U.S. Department of Energy

378

Specific Program Recommendations The WinDS, UWIG, WPA and AWEA projects are excellent uses of taxpayer money. The support of UWIG (Utility Wind Integration Group) has had a major impact on the integration of wind. Just the name change from the Utility Wind Interest Group represents a major development. The studies produced under the management of this Group play a major role in presenting data to the utility industry. The AWEA project needs to undertake an increased effort to assure that crucial data is available for real-time modeling and analyses. A consistent set of procedures need to be developed so that “proprietary” data from wind power plants can be utilized in the modeling and analyses effort. The focus on the integration of wind with hydropower is to be commended. Continued activities are encouraged including involvement of Canadian energy systems. More clarity and analyses is needed to detail the tradeoffs involved with maximizing the hydro system as potential cost effective storage for wind. Wind Powering America (WPA) should increase its coordination with System Integration activities. The expansion of the transmission system integration with wind will touch on state issues. There is a synergistic relationship between WPA and other System Integration activities that can speed the development of wind power. Please consider the above points as input to continued planning efforts. Sincerely,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Carl J. Weinberg

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

APPENDIX B: MEETING ATTENDEE LIST 2007 DOE WIND AND HYDROPOWER PROGRAM PEER REVIEW MEETING JULY 11-12, 2007 DENVER MARRIOTT WEST GOLDEN, COLORADO Contact Rashid Abdul Tom Acker Mark Ahlstrom Doug Arent Abby Arnold Lisa Barnett Peggy Beltrone Keith Bennett Lori Bird Nate Blair Steve Blazek Mark Bolinger Michael Brower Michael Bruce Stanley Bull Stacey Burge Jack Cadogan Stan Calvert Palmer Carlin

Organization Mitsubishi Power Systems Americas, Inc. Northern Arizona University WindLogics Inc. NREL RESOLVE US Department of Energy Cascade County US Department of Energy National Renewable Energy Laboratory National Renewable Energy Laboratory US Department of Energy (Golden, CO) Lawrence Berkeley National Laboratory AWS Truewind, LLC US Department of Energy National Renewable Energy Laboratory National Renewable Energy Laboratory Cadogan Consulting US Department of Energy National Renewable Energy Laboratory

E-mail [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected]

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Appendix B. Continued Contact Kim Cierpik Joe Cohen Brian Connor Stephen Connors Dave Corbus Martina Dabo Ted De Rocher Jennifer DeCesaro Edgar DeMeo Phil Dougherty Dennis Elliot Stephen Enyeart Mary Fischer Larry Flowers Trudy Forsyth Curtis Framel Bobi Garrett Michael Goggin Peter Goldman Chico Gonzalez Bob Gough Bruce Green Maureen Hand Eric Hass William Holley Cathy Iverson

Organization Navarro Research & Engineering Princeton Energy Resources International US Department of Energy Massachusetts Institute of Technology National Renewable Energy Laboratory Alaska Energy Authority Caithness Operating Company, LLC Clean Energy States Alliance Renewable Energy Consulting Services, Inc. US Department of Energy - Wind Program National Renewable Energy Laboratory - NWTC Bonneville Power Administration SENTECH, Inc. National Renewable Energy Laboratory National Renewable Energy Laboratory US Department of Energy (Golden, CO) National Renewable Energy Laboratory SENTECH, Inc. PRG Consulting Navarro Research and Engineering, Inc. Intertribal Coup, Council on Utility Policy National Renewable Energy Laboratory - NWTC National Renewable Energy Laboratory Navarro Research and Engineering, Inc. GE Energy GO - US Department of Energy

E-mail [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected]

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Laurie Jodziewicz Marguerite Kelly Brendan Kirby Daniel Laird Doug Larson Ronald Lehr Steve Lindenberg Steve Lockard Randy Manion John Mankins Laura Margason Jim McVeigh Michael Milligan Walt Musial Bradley Nickell Kathleen O'Dell Amanda Ormond Dale Osborn Steven Palomo Brian Parsons Michael Pehosh Al Pless Robert Poore Kevin Porter Tom Potter Karl Rabago Bonnie Ram

American Wind Energy Association National Renewable Energy Laboratory Oak Ridge National Lab Sandia National Laboratories Western Interstate Energy Board American Wind Energy Association US Department of Energy TPI Composites Western Area Power Administration Artemis Innovation Management Solutions US Department of Energy - Navarro SENTECH, Inc. National Renewable Energy Laboratory National Renewable Energy Laboratory US Department of Energy National Renewable Energy Laboratory Ormond Group LLC Midwest ISO US Department of Energy (Golden, CO) National Renewable Energy Laboratory National Rural Electric Cooperative Association Southeastern Power Administration Global Energy Concepts, LLC Exeter Associates, Inc. All American Energy AES Alternative Energy Energetics Inc.

[email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected]

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Appendix B. Continued Contact Tim Ramsey Russell Raymond Michael Reed Lori Rhodes Robi Robichaud Rush Robinett Mike Robinson Michael Schledorn Marc Schwartz Gary Seifert Aaron Severn Walter Short Alison Silverstein Karin Sinclair Mike Skelly Brian Smith James Smith James Snelson James Spaeth Roya Stanley Michele Suddleson Suzanne Tegen Bob Thresher Paul Veers Yih-huei Wan Carl Weinberg

Organization US Department of Energy - Navarro Energetics Inc. SENTECH, Inc. US Department of Energy National Renewable Energy Laboratory Sandia National Laboratories National Renewable Energy Laboratory US Department of Energy (Golden, CO) National Renewable Energy Laboratory Idaho National Laboratory AWEA National Renewable Energy Laboratory Alison Silverstein Consulting National Renewable Energy Laboratory Horizon Wind Energy National Renewable Energy Laboratory Utility Wind Integration Group Renewable Energy Systems Americas Inc. US Department of Energy National Renewable Energy Laboratory American Public Power Association National Renewable Energy Laboratory National Renewable Energy Laboratory Sandia National Laboratories National Renewable Energy Laboratory Weinberg Associates

E-mail [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected]

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Tom Weis Mary Wheeler Susan Williams Stone Robert Zavadil Jose Zayas

enXco National Renewable Energy Laboratory American Wind Energy Association EnerNex Corporation Sandia National Laboratories

[email protected] [email protected] [email protected] [email protected] [email protected]

APPENDIX C: SUMMARY OF PEER REVIEW PANEL EVALUATION SCORES Peer Reviewer Project/Program Evaluation Form Scores Numerical Scoring Index

1

2

3

Qualitative Descriptors

Seriously Deficient

4

5

6

7

8

Average

9

10

Outstanding

Western Wind Integration Study

Wind & Hydro Integration

Grid Simulators

8.3

Stakeholder Integration NWCC Western Regional Interstate Collaboratio Studies Energy Transn & Outmission Board/reach WGA 7.5 8.3 7.3 8.3

6.8

7.5

7.5

Generator Wind Farm ModeData ling Monitoring 7.5 6.8

9.0

8.8

8.0

7.3

8.0

8.3

Scoring Category\Projects

UWIG

Effectiveness (consider the elements of quality, productivity, and accomplishments Relevance (to mission, goals, strategy, and technical and/or market barriers)

9.3

7.8

8.8

8.5

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Appendix C. Continued Overall Impression (consider 7.8 all measures, inputs and outputs, and program management) 8.3 Average Category Score

8.0

7.8

7.0

9.0

7.3

7.3

7.8

7.5

7.3

8.1

8.4

7.3

8.7

7.3

7.3

7.8

7.8

7.5

Peer Reviewer Project/Program Evaluation Form Scores Scoring Category\Projects

Wind Integration Technical Assistance 6.8

Effectiveness (consider the elements of quality, productivity, and accomplishments 8.8 Relevance (to mission, goals, strategy, and technical and/or market barriers) 8.0 Overall Impression (consider all measures, inputs and outputs, and program management) 7.8 Average Category Score Scoring Category\Projects

AWEA Critical Issues & FERC Activity 5.3

Competitive Power Markets

WinDS Radar Mode- Mitigation & ling Impacts

National Wildlife High Wind Research Priority Coordinating States Collaborative

LowMedium Priority States

Agricultural Outreach

7.3

8.3

7.2

8.4

8.0

9.0

8.2

8.4

6.0

8.3

8.5

9.2

9.2

8.4

9.4

9.2

8.8

5.5

7.5

8.5

8.2

8.8

8.4

8.8

8.4

9.0

5.6

7.7

8.4

8.2

8.8

8.3

9.1

8.6

8.7

Regional Air Quality Economic Wind & Impact Mapping Wind Institutes Emissions Analysis

Native Americans

Distributed Wind

Public Power

Wind for Schools

Federal Federal Wind Loads/ Siting Greening Collaborative DOE

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Effectiveness (consider the elements of quality, productivity, and accomplishments Relevance (to mission, goals, strategy, and technical and/or market barriers) Overall Impression (consider all measures, inputs and outputs, and program management) Average Category Score

7.2

7.0

7.8

9.0

8.0

7.8

6.8

8.0

7.0

6.7

8.0

8.5

8.2

9.8

8.8

7.8

7.0

8.0

7.8

9.0

7.6

7.3

8.2

9.2

8.0

7.5

7.3

8.4

7.0

8.3

7.6

7.6

8.1

9.3

8.3

7.7

7.0

8.1

7.3

8.0

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved. Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

INDEX

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

A academic, 227, 340 access, 6, 27, 28, 63, 69, 114, 125, 130, 138, 157, 180, 194, 198, 199, 201, 202, 204, 205, 206, 240, 241, 284, 295, 340, 350, 354 access charges, 28 accessibility, 157, 244 accounting, 33, 58, 73, 83, 120, 275, 341, 375 accreditation, 152 accuracy, 151, 156, 332 ACE, 97, 99, 198, 326 achievement, 162, 369 acid, 118, 211, 217, 273, 329, 330 acidification, 118 acoustic, 25, 159, 227 acoustic emission, 159 acquisitions, 63 actuators, 135 adhesives, 166, 167 adjustment, 147, 289 administration, 29 Advanced Energy Initiative, 342, 348 advocacy, 106 AEP, 99, 117, 202, 207, 321 aeronautical, 225 aesthetics, 26, 212 affiliates, 95 AGC, 99, 185 age, 82, 138, 149, 150, 308 agent, 151 aggregation, 196, 198, 206 aging, 27, 250, 306 agricultural, 132, 159, 176, 216, 218 aid, 153, 337 air, 6, 7, 8, 10, 12, 17, 21, 26, 27, 39, 118, 119, 120, 136, 186, 210, 213, 222, 231, 270, 286, 287, 331, 363 air emissions, 21, 231, 363

air pollutants, 6 air quality, 120, 363 airports, 283 Alabama, 261, 273, 282, 285, 286 Alaska, 14, 244, 261, 273, 359, 380 Alberta, 25, 39 algorithm, 112 alloys, 148 alternative, vii, 1, 4, 21, 22, 31, 42, 86, 143, 160, 168, 169, 225, 226, 301, 371 alternative energy, 226 alternatives, vii, 1, 2, 23, 24, 33, 181, 212, 240 aluminum, 166, 168 Amsterdam, 126, 235 analysts, 19, 41, 204, 288, 340 analytical tools, 118, 151 animals, 25, 327 annual rate, 41, 169, 238, 242, 310 anthropogenic, 217, 326 API, 99, 155 appendix, 247, 248, 275, 306, 307, 324 appetite, 63, 65 application, x, 86, 142, 143, 148, 225, 230, 335, 338, 373, 375 appropriations, 39, 98, 373 arbitrage, 96 argument, 30, 134 arid, 121, 214 arithmetic, 186 Arizona, 84, 85, 273, 282, 302, 343, 344, 348, 359, 379 Arkansas, 15, 273, 282 Army, 104, 225, 348 Army Corps of Engineers, 104, 225, 348 arsenide, 101, 146 ash, 118 Asia, 15 Asian, 160 assessment, 155, 201, 220, 231, 238, 261, 331, 336, 372, 374

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Index

388

assets, 190, 226, 275 assimilation, 287 assumptions, 21, 23, 24, 33, 36, 42, 93, 106, 107, 108, 111, 112, 114, 115, 116, 124, 125, 193, 204, 212, 220, 247, 248, 249, 250, 251, 253, 254, 256, 257, 259, 261, 272, 275, 276, 283, 286, 291, 295, 305, 306, 309, 310, 311, 332, 333, 334 asthma, 214 asynchronous, 40 Athens, 41, 163 Atlantic, 86, 102, 171, 204, 206, 277, 330, 363 Atlas, 284, 305 atmosphere, 7, 212, 287, 327, 330, 331 attacks, 214 authority, 26, 28, 34, 39, 46, 153, 198, 206, 224, 225, 229, 326, 343 automation, 174 automobiles, 127, 175 availability, 11, 20, 32, 59, 85, 87, 88, 124, 132, 149, 151, 156, 165, 166, 167, 178, 194, 238, 245, 271, 297, 298, 377 average costs, 77 averaging, 82 aviation, vii, 2, 11, 148 avoidance, 260 awareness, 198, 229, 362

biological systems, 212 biomass, 20, 32, 302, 327, 330 bipartisan, viii, 2 birds, 25, 43, 211, 212, 216, 217, 218, 219, 225, 227, 229, 237, 357 birth, 128 BLM, 99, 225, 234 blocks, 20 boilers, 194, 270 bonds, 35, 123 Bonneville Power Administration, 20, 22, 48, 93, 99, 241, 380 Bonneville Power Administration (BPA), 93, 241 bonus, 87, 194 Boston, 230, 234, 236, 273 bottlenecks, 173 broad spectrum, 322 Brussels, 126, 210, 235 Btus, 36 buffer, 20, 284 buildings, 138, 141, 222 Bureau of Land Management(BLM), 99, 225, 234 Bureau of Reclamation, 348 business management, x, 335 bust, 19, 50

C

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

B balance sheet, 65 banking, 65 banking industry, 65 banks, 3 barrier, 28, 85, 86, 130, 144, 161, 180, 345, 356, 358 barriers, viii, 2, 11, 13, 86, 88, 155, 158, 169, 180, 204, 337, 338, 345, 346, 349, 352, 354, 355, 358, 369, 383, 384, 385 base case, 107, 118, 251, 275, 278, 281, 284 base year, 278, 279 batteries, 12 battery, 131, 159 behavior, 10, 25, 156, 181, 183, 191, 328 Belgium, 126, 210, 235 benchmark, 152 beneficial effect, 186 benefits, 3, 5, 30, 64, 65, 74, 105, 107, 111, 125, 137, 148, 196, 198, 202, 204, 205, 206, 210, 211, 212, 221, 228, 232, 233, 243, 248, 260, 270, 273, 296, 303, 333, 340, 341, 348, 362, 363, 364, 369 benign, 65 Best Practice, 236 bias, 95 binding, 37

cables, 154 caliber, 373 CAM, 376 Canada, 44, 51, 218, 347 CAP, 104 capital cost, 21, 22, 23, 24, 33, 34, 77, 89, 91, 92, 107, 119, 124, 125, 127, 128, 144, 146, 147, 148, 149, 154, 162, 201, 202, 244, 252, 268, 275, 288, 293, 302, 334 capital intensive, 19 caps, 334 carbide, 103, 143 carbon, 4, 6, 7, 17, 18, 21, 22, 24, 31, 33, 34, 38, 42, 87, 88, 89, 100, 102, 118, 120, 121, 136, 140, 142, 167, 168, 169, 181, 210, 212, 242, 250, 256, 257, 259, 260, 268, 270, 300, 306, 327, 333, 334, 363 Carbon, 22, 23, 31, 42, 126, 136, 168, 212, 248, 259, 273, 274, 275, 327, 333 carbon dioxide, 6, 18, 21, 22, 24, 31, 33, 38, 42, 100, 118, 212, 242 carbon emissions, 22, 121, 259, 268, 270 cardiovascular disease, 214 cargo, 40, 135 carrier, 240

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Index cash flow, 33, 45 cast, 26 casting, 26 catalyst, 238, 247 categorization, 94 CEC, 100, 181, 194, 208, 274, 343, 344, 350 cell, 282, 286, 287 Census, 304 centralized, 198 CEO, 337 CERCLA, 43 certificate, 48, 54, 176, 177, 240, 330 certification, 148, 151, 152, 155, 161, 368, 374 chemicals, 167 chicken, 28, 204 chickens, 25, 237 children, 214 China, vii, 2, 17, 41, 51, 52, 124, 168, 174 chopping, 160 CHP, 207 circulation, 330 citizens, 228 civilian, 26 classes, 10, 40, 112, 137, 251, 252, 254, 281, 284, 285, 286, 287, 288, 300, 331, 334 Clean Air Act, 100, 300 clean energy, 118, 121 Clean Renewable Energy Bond, 31, 87 Clean Renewable Energy Bonds, 31 Clean Water Act, 43 climate change, ix, 32, 104, 108, 118, 121, 210, 212, 215, 217, 226, 231, 233 climate warming, 212 closed-loop, 214 clouds, 26 CNV, 100, 277, 280, 281 CO2, 38, 100, 118, 119, 120, 121, 122, 212, 213, 237, 242, 274, 291, 292, 300, 327, 328, 330, 333 coal, 4, 6, 17, 21, 22, 23, 24, 31, 33, 35, 36, 38, 41, 42, 44, 49, 50, 77, 100, 112, 115, 116, 121, 123, 174, 194, 199, 201, 213, 215, 216, 251, 253, 257, 259, 260, 268, 271, 291, 293, 294, 296, 300, 327, 333, 346 coal mine, 35 Coast Guard, 39 coastal areas, 243 coastal communities, 244 codes, 133, 155, 173, 181, 188, 328, 374 collaboration, 82, 84, 148, 200, 237, 275, 341, 343, 344, 363, 373, 374, 375 Collaboration, 174, 234, 237, 339, 343, 374, 383 collaborative approaches, 232 colleges, 370, 373

389

collisions, 25, 218 Colorado, 13, 15, 28, 37, 39, 53, 54, 58, 59, 84, 86, 87, 93, 98, 176, 181, 188, 200, 205, 273, 274, 282, 302, 377, 379 Columbia, 32, 37, 177, 242 combustion, 17, 21, 100, 101, 116, 127, 148, 174, 193, 194, 251, 257, 272, 299, 305, 327, 329 combustion processes, 329 commercialization, 155 commodity, 242, 252, 330 communities, 106, 119, 151, 210, 211, 212, 214, 221, 222, 223, 224, 228, 232, 233, 244, 246, 370 community, 66, 151, 176, 205, 222, 224, 228, 231, 232, 233, 237, 244, 245, 246, 336, 343, 344, 369, 373 community conflict, 233 community support, 231 compatibility, 284, 286 compensation, 240 competition, 74, 122, 124, 214, 215, 230, 240, 276, 330, 336 competitiveness, vii, 1, 23, 24, 35, 42, 153, 199, 300 compilation, 79 complement, 343 complexity, vii, 1, 5, 148, 160, 228, 244, 358 compliance, 32, 72, 161, 242, 332, 374 components, 3, 5, 11, 19, 59, 60, 68, 78, 88, 108, 110, 124, 130, 131, 135, 138, 142, 143, 147, 149, 152, 157, 158, 161, 162, 166, 167, 168, 171, 172, 173, 174, 175, 194, 198, 247, 251, 262, 278, 307, 314, 330 composites, 133, 148, 166, 168, 169 composition, vii, 2 compounds, 223, 327 Comprehensive Environmental Response, Compensation, and Liability Act, 43 computation, 345 Computer simulation, 26 computing, 271 concentrates, viii, 48 concrete, 19, 138 conditioning, 7, 138 conductor, 326 confidence, 96, 150, 151, 152, 153, 155, 158 confidentiality, 76, 83, 91 configuration, 10, 138, 156 conflict, 142, 221 Congestion, 86 Congress, viii, 1, 2, 3, 9, 25, 26, 29, 30, 31, 32, 33, 37, 44, 206, 229, 241, 247, 301, 305 Congressional Budget Office, 31, 35, 42, 100 Connecticut, 72, 143, 273, 282, 285, 302 consensus, 138, 151, 161

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

390

Index

conservation, 118, 216, 228, 283, 330 consolidation, 16, 62, 90, 198 constant rate, 135, 137 constraints, 5, 27, 28, 62, 111, 114, 130, 134, 135, 243, 248, 291, 309, 349, 355, 369 construction, vii, viii, 1, 2, 5, 6, 8, 13, 17, 21, 25, 26, 27, 29, 32, 34, 38, 41, 59, 65, 77, 89, 91, 100, 106, 119, 121, 125, 153, 159, 168, 187, 199, 204, 211, 216, 225, 228, 229, 245, 252, 253, 268, 273, 275, 288, 293, 297, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 318, 334, 355 consultants, 42, 284, 363, 365 consulting, 105 consumers, vii, 1, 5, 19, 28, 114, 119, 123, 202, 204, 237, 352 consumption, 20, 40, 53, 89, 92, 115, 118, 121, 122, 124, 159, 165, 166, 168, 201, 207, 214, 215, 240, 242, 268, 270, 271, 272, 309, 328, 329, 331, 333, 342 consumption patterns, 309 consumption rates, 271, 272 continental shelf, 226 contingency, 196, 197 contract prices, 96 contractors, 308, 332 contracts, 54, 110, 198, 242 control, vii, 1, 5, 10, 17, 21, 28, 34, 40, 41, 73, 82, 97, 99, 103, 132, 135, 137, 138, 140, 142, 143, 144, 146, 154, 159, 160, 162, 168, 185, 188, 189, 190, 191, 192, 198, 207, 219, 220, 223, 224, 225, 231, 242, 243, 299, 326, 329, 330, 331, 350 control group, 223 convergence, 73 conversion, 12, 18, 137, 138, 143, 212, 331 cooling, 6, 121, 122, 143, 148, 214, 270, 271 Copenhagen, 164, 165 copper, 131, 143, 166, 168, 354 corn, 6, 38 corporations, 106 correlation, 145, 253, 287, 297, 298, 299 correlation coefficient, 145 corridors, 25, 86, 132, 341 corrosion, 142, 158 cost of debt, 42 cost of power, 19 cost-effective, ix, 5, 30, 104, 112, 201, 232, 242, 257, 261 cost-sharing, 284 coupling, 140, 141 coverage, 93, 285 covering, 32 CPS, 55 cracking, 14, 148

creativity, 370 CREB, 87 CREBs, 88 credibility, 76, 149, 219 credit, 2, 22, 23, 29, 30, 33, 34, 41, 42, 46, 65, 87, 103, 110, 328, 330 critical infrastructure, 199 crops, 6, 271 cross-border, 67 CRP, 167 CRS, vii, 1, 22, 30, 33, 36, 37, 38, 39, 44, 45 curiosity, 188 currency, 19 curriculum, 369 customers, 20, 29, 54, 66, 199, 204, 238, 239, 240, 242, 246, 327, 329 cycles, 19, 180, 327, 328, 331

D damping, 189, 190 data analysis, ix, 105, 341 data collection, 231 data processing, 288 data set, 285, 287 database, 51, 54, 58, 59, 61, 62, 63, 67, 68, 69, 70, 71, 74, 75, 76, 77, 78, 79, 80, 83, 84, 89, 90, 91, 92, 131, 152, 203, 271, 278, 283, 287, 295, 305 dead zones, 26 death, 214, 217 deaths, viii, 2, 5, 6, 25, 217, 218 debt, 30, 41, 42, 46, 65, 87, 311 decay, 303 deciduous, 215 decision makers, 165, 224, 233, 246, 362 decision making, 211 decision-making process, 219, 340, 374 decisions, 137, 178, 192, 211, 215, 219, 222, 224, 225, 231, 240, 246, 268, 294, 298, 336 defense, 26, 27, 43 deficit, 192 definition, 283 deforestation, 212 degradation, 3, 26, 27, 143, 147 degrading, 143, 188 Delaware, 9, 56 delivery, 58, 73, 95, 108, 115, 193, 199 demand, vii, ix, 1, 3, 5, 6, 12, 13, 15, 17, 20, 28, 50, 53, 62, 65, 72, 87, 97, 105, 107, 108, 112, 114, 115, 118, 119, 122, 124, 153, 161, 165, 166, 168, 169, 170, 175, 178, 180, 182, 192, 193, 199, 207, 210, 213, 214, 215, 238, 240, 243, 248, 249, 250, 251, 254, 256, 259, 260, 264, 265, 276, 278, 279,

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Index 280, 293, 297, 298, 299, 302, 306, 307, 309, 315, 318, 329, 333, 334 demobilization, 135 denial, 358 Denmark, 3, 16, 17, 51, 126, 137, 144, 154, 163, 164, 165, 178, 179, 209, 231 density, 8, 39, 112, 168, 223, 262, 281, 283, 284, 286, 287, 293, 331 density values, 286 Department of Agriculture, 38, 104, 226, 237, 377 Department of Commerce, 102, 210, 321, 324, 332 Department of Defense (DOD), 26, 43, 100, 226, 240, 374 Department of Energy(DOE), v, viii, ix, 2, 4, 5, 34, 37, 39, 43, 44, 46, 47, 48, 92, 99, 100, 105, 146, 163, 165, 206, 226, 234, 237, 238, 247, 272, 274, 289, 319, 320, 321, 322, 323, 324, 325, 332, 335, 336, 374, 377, 379, 380, 381, 382 Department of Homeland Security, 26, 43 Department of Interior, 100 Department of the Interior, 9, 43, 234 Department of Transportation, 235 depreciation, 33, 87, 94, 329 deregulation, 240 designers, 130, 133, 158, 181 desire, 134, 149 detection, 101, 103, 151, 157 developing nations, 124 deviation, 69 diesel, 41, 244 direct cost, 149, 205, 251, 254, 268, 270, 301 direct costs, 205, 254, 268, 270 discount rate, 269, 270, 293, 303, 312, 313 discrimination, 28 dispersion, 206, 299 displacement, 121, 216 disseminate, 350, 357 distortions, 94 distributed generation, 245, 251 distribution, 49, 61, 88, 111, 147, 154, 160, 183, 196, 239, 243, 244, 248, 256, 262, 285, 286, 328, 329, 331, 362 District of Columbia, 32, 37, 242 diversification, 123, 260, 273 diversity, 19, 98, 119, 124, 196, 197, 206, 224, 351, 370 division, 95 do-it-yourself, 160 domestic demand, 59 domestic resources, ix, 104 dominance, 156 draft, 9, 100, 161, 230, 319, 350 droughts, 193

391

durability, 138, 139 duration, 101, 278, 279, 355 duties, 144 dynamic scheduling, 198

E ears, 142 earth, 143, 160, 331 ecological, 215, 231, 233 ecological damage, 215 ecology, 211, 212, 229 economic activity, 306, 307, 308, 311 economic development, 205, 224, 244, 306, 307, 311, 318, 340, 362, 364, 373, 374 economic policy, 30 Economic Research Service, 38 economics, vii, 2, 3, 17, 22, 24, 35, 62, 119, 197, 238, 245, 340, 362 economies of scale, 12, 62, 76, 82, 96, 205, 228 ecosystem, 9, 210 Education, 39, 176, 228, 339, 352 educational programs, 175, 176, 340, 373 egg, 28, 204 elasticity, 259 electric energy, 179 electric power, 20, 24, 28, 38, 44, 45, 120, 124, 127, 179, 214, 275, 307, 327, 330, 338, 342, 352 electric utilities, 88, 90, 93, 105, 123, 204, 233 electrical power, 130, 138, 326, 328, 329, 331 electrical system, 130, 137, 166, 186 electricity system, 5, 377 electromotive force, 331 email, 332 embargo, 123 emission, 120, 242, 248, 250, 260, 292, 300 EMP, 127, 275 employees, 174, 175, 332 employment, ix, 7, 104, 120, 175, 306, 307, 308, 311, 312, 314, 315, 317, 318 encapsulated, 33 Endangered Species Act, 25, 225 end-users, vii, 1 energy density, 143 energy efficiency, ix, 30, 32, 104, 118, 238, 240, 251 Energy Efficiency and Renewable Energy (EERE), x, 30, 37, 38, 39, 43, 47, 92, 99, 100, 105, 234, 237, 274, 305, 335, 377 Energy Independence and Security Act, 32 Energy Information Administration (EIA), ix, 5, 32, 33, 35, 36, 37, 38, 48, 100, 115, 126, 163, 165, 179, 247, 248, 274, 275, 304, 323 energy markets, 124, 187, 362

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

392

Index

Energy Policy Act, 22, 28, 39, 45, 86, 87, 100, 110, 153, 198, 229, 240, 305, 329, 330 Energy Policy Act of 2005, 22, 28, 39, 45, 86, 87, 305, 329 energy supply, 169, 203, 332 engagement, 212, 246, 325 England, 67 Enron, 337 enthusiasm, 361 entrepreneurs, 3 environment, 106, 107, 110, 148, 156, 158, 178, 181, 186, 224, 244, 250, 273, 275, 325, 326, 333, 360, 361 environmental control, 21 environmental degradation, 3 environmental effects, ix, 105, 210, 232, 326 environmental impact, ix, 9, 100, 101, 104, 105, 155, 161, 204, 210, 211, 224, 225, 226, 230, 243 Environmental Impact Assessment, 235 environmental issues, 106, 119 environmental protection, 210 Environmental Protection Agency, 100, 213, 235, 240, 300, 304 environmentalists, 118 EPA, 100, 213, 235, 240, 300, 304, 305, 364 EPC, 100, 293 equilibrium, 123 equity, 29, 35, 42, 46, 63, 64, 65, 94, 311 esthetics, 161 estimating, 166, 259 ETA, 271 ethanol, 214, 215 Ethanol, 45, 235 EU, 100, 153, 158, 341 Euro, 78 Europe, 9, 15, 31, 56, 110, 131, 153, 176, 178, 207, 208, 218, 228, 229, 231, 233, 235, 374 European Union, 100, 153 evening, 26, 185 evolution, 8, 126, 127, 179, 182, 197, 214, 353 exchange rate, 18, 252 exclusion, 155, 219, 262, 283 exercise, 94 expenditures, 85, 92, 308, 311, 315 expert, 106, 153, 285, 295, 375 expert systems, 153 expertise, 178, 344, 373 exposure, 6, 213, 214, 282, 350 external costs, 242 extinction, 212 extraction, 130, 136, 151, 215 extrapolation, 92 eyes, 142, 149

F FAA, 25, 26, 27, 44, 100, 148, 222, 225, 226, 235, 356 fabrication, 157, 160 failure, 82, 132, 149, 150, 157 farmers, 6, 66, 244 farming, 216, 262 farms, viii, 38, 48, 49, 149, 238, 297, 351 fatalities, 25, 217, 218, 227 fatigue, 11, 136, 140, 168, 169 faults, 153, 188 fax, 332 February, 7, 18, 20, 28, 30, 39, 40, 41, 42, 43, 44, 56, 86, 88, 163, 179, 222, 275, 287 Federal Aviation Administration, 25, 26, 100, 148, 222, 235 Federal Energy Regulatory Commission, ix, 28, 37, 44, 45, 48, 101, 181, 208, 239, 329 federal government, 18, 46, 87, 174, 199, 225, 240, 241, 245 federal grants, 42 fee, 295, 297, 332 feedback, 309, 324, 336, 350 fees, 160, 288 feet, 8, 9, 11, 27, 40 FERC, ix, 28, 29, 32, 37, 44, 48, 71, 86, 90, 91, 94, 96, 101, 181, 198, 204, 205, 207, 208, 209, 239, 240, 241, 329, 339, 341, 353, 377, 384 fertilizer, 38 fetal, 213 fiber, 101, 136, 142, 167, 168, 178 fibers, 140 filament, 100, 169 finance, 29, 30, 63, 65 financial institution, 149 financial resources, 21 financing, 4, 30, 33, 35, 41, 42, 46, 63, 90, 95, 107, 149, 242, 252, 254, 268, 275, 288, 293, 309, 310, 334, 353 fines, 198 Finland, 208 firms, 15, 61, 173, 238 first generation, 135 fish, 232 Fish and Wildlife Service, 25, 43, 283 fisheries, 219 fission, 21 fixed costs, 17, 19, 20, 41 flexibility, 15, 193, 207, 348 flight, 216 floating, 95, 157 flooding, 215

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Index flow, 79, 136, 137, 190, 308, 327, 331, 343 fluctuations, 79, 142, 207, 297 fluid, 136 focusing, 53, 94, 270, 374 food, 308 football, 152 forecasting, 20, 157, 182, 186, 192, 207, 298, 352, 353 forensic, 375 Forest Service, 104, 226, 237, 283 forestry, 216, 219, 235, 275 forests, 226 fossil, vii, viii, 1, 2, 3, 4, 6, 17, 19, 20, 21, 22, 24, 33, 39, 47, 73, 89, 118, 119, 121, 122, 124, 148, 153, 163, 181, 201, 204, 210, 211, 212, 213, 214, 215, 216, 240, 242, 271, 294, 327, 330, 334 fossil fuel, vii, 1, 3, 4, 17, 20, 22, 39, 118, 119, 121, 122, 181, 201, 204, 210, 211, 212, 215, 216, 294, 327, 330, 334 fossil fuels, 3, 118, 119, 181, 210, 212, 327, 330 fouling, 137 fragmentation, 233 France, 51 free energy, 188, 194 frequency distribution, 286 fuel, vii, 1, 4, 6, 17, 20, 21, 23, 33, 34, 38, 39, 42, 107, 119, 121, 122, 123, 124, 125, 127, 186, 195, 198, 201, 204, 206, 210, 211, 212, 213, 214, 215, 216, 252, 254, 259, 260, 268, 269, 270, 291, 292, 294, 295, 302, 303, 305, 327, 329, 330, 334 fuel cell, 329 fuel efficiency, 127 fuel type, 195 full capacity, 5, 326 funding, vii, 3, 10, 28, 82, 98, 216, 230, 253, 336, 355, 358, 361, 370, 371, 373 funds, 87, 88, 174, 227, 302, 370, 373 furnaces, 167 futures, 294 FWS, 25, 43

G GaAs, 101, 146 gallium, 101, 146 gas, vii, 1, 4, 6, 17, 20, 21, 22, 23, 24, 30, 31, 32, 33, 36, 38, 39, 41, 42, 44, 45, 49, 50, 57, 77, 92, 95, 101, 110, 115, 116, 118, 121, 122, 123, 124, 148, 154, 155, 157, 165, 174, 194, 199, 202, 207, 213, 215, 238, 250, 251, 252, 257, 259, 260, 293, 294, 296, 299, 327, 330, 344 gas turbine, 148, 344 gases, 21, 328

393

gasification, 100, 101, 251 gasoline, 123 gauge, 356 GE, 14, 40, 58, 59, 84, 92, 94, 101, 148, 181, 188, 189, 190, 194, 236, 288, 319, 320, 321, 323, 343, 348, 380 General Electric, 14, 40, 55, 101, 103, 148, 181, 209, 288 General Services Administration, 240 generators, 28, 41, 96, 128, 137, 143, 146, 158, 159, 160, 168, 185, 190, 192, 193, 194, 196, 198, 207, 239, 240, 241, 242, 253, 276, 297, 299, 329, 374 geography, 70 Georgia, 56, 231, 273, 282, 285 geothermal, 20, 34, 329, 330 geothermal systems, 34 Germany, 4, 16, 17, 18, 31, 51, 52, 53, 63, 110, 137, 143, 144, 154, 178, 207, 208 GHG, 101, 118, 119, 120, 206, 212, 226 GIS, 101, 155, 203, 251, 254, 283, 286, 295, 305 glass, 101, 167, 178 glass-fiber, 167 global climate change, 49, 87, 118, 212, 221, 327, 376 global demand, 314 Global Insight, 35, 36 global markets, 59 Global Warming, 126, 304 globalization, 62 goals, 3, 37, 108, 142, 155, 169, 193, 205, 210, 226, 229, 300, 336, 337, 345, 350, 351, 352, 353, 356, 363, 373, 377, 383, 384, 385 goods and services, 308 government, ix, 6, 13, 18, 22, 24, 33, 34, 46, 87, 104, 106, 148, 156, 172, 174, 178, 199, 205, 210, 211, 225, 226, 227, 228, 229, 240, 241, 242, 244, 245, 294, 318, 326, 332, 343, 371 Government Accountability Office, 38, 43, 235 government policy, 24 graduate education, 177 grain, 131, 168, 331 grants, 42, 66, 87 graph, 202, 260 grassland, 216, 227 grasslands, 226, 285 gravity, 140 grazing, 6 Great Lakes, 80, 81, 96, 251, 314, 363 Greece, 41, 163 greenhouse, vii, 1, 2, 31, 101, 103, 120, 212, 233, 275, 327, 328 Greenhouse, 38, 103, 118, 120, 126, 234, 236, 275, 304, 328, 330

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Index

394

greenhouse gas, vii, 1, 2, 31, 101, 103, 120, 212, 233, 327, 328 greenhouse gases, 103, 233, 328 grid services, 144 grids, vii, 2, 16, 20, 53, 155, 213, 238, 241, 270, 347, 350 groups, 83, 84, 106, 227, 228, 246, 341, 343, 346, 359, 370, 375 growth, viii, ix, 3, 4, 13, 16, 18, 30, 36, 47, 49, 50, 53, 58, 59, 87, 88, 89, 94, 96, 105, 106, 107, 108, 109, 110, 111, 112, 116, 118, 119, 122, 124, 131, 133, 134, 135, 136, 144, 147, 149, 152, 153, 158, 168, 174, 178, 181, 187, 193, 214, 228, 238, 239, 242, 243, 244, 247, 248, 249, 250, 251, 265, 280, 293, 306, 333, 338, 373 growth rate, 36, 53, 89, 107, 168, 174, 178, 250, 251, 280, 306, 333 guidance, 28, 155, 222, 269, 270, 312, 313, 319, 336, 337 guidelines, 25, 64, 222, 225, 226, 229, 246, 303, 332, 337 Gulf Coast, 123, 217, 237

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

H H1, 279 H2, 279 habitat, 210, 212, 215, 216, 219, 227, 228, 233, 237 handicapped, 5 hands, 350 hanging, 144 harm, 6 harmonization, 155 harvest, 130, 137, 245 Hawaii, 14, 54, 80, 81, 95, 261, 273 health, 153, 212, 273 hearing, 29, 44 heart, 214 Heart, 81 heart attack, 214 heat, 21, 36, 292, 293, 294, 328, 331 heating, 7, 328 heavy metal, 118 heavy metals, 118 height, 11, 78, 130, 134, 135, 138, 147, 154, 222, 282, 283, 285, 286, 315 hemisphere, 330 high risk, 148, 158 high school, 176, 177 higher quality, 9, 157, 201 high-level, 151 high-risk, 140, 148 high-speed, 133, 254

highways, 130, 152 histogram, 186, 288 holding company, 94 home value, 223, 224 Homeland Security, 26, 43, 374 horizon, 174, 251, 254 hospitalization, 214 hospitals, 318 host, 228, 233, 246 House, 29, 30, 32, 44 household, 7, 40, 124 housing, 7, 65, 216 HSIL, 101 hub, 78, 79, 80, 130, 147, 286 human, 25, 26, 153, 212, 217, 229, 233, 237, 328, 329, 363 human activity, 212, 217, 237 hunting, 25 hurricane, 123 hybrid, 156, 158, 199, 207, 244, 329, 346 hydro, 186, 194, 302, 341, 347, 348, 349, 378 hydroelectric power, 12, 44 hydrogen, 199, 207 hydropower, 181, 186, 193, 199, 214, 241, 378

I ice, 158 ICE, 91 Idaho, 54, 60, 85, 97, 98, 140, 194, 273, 282, 287, 301, 356, 382 identification, 110, 248 IEA, 101, 164, 198, 209 Illinois, 13, 15, 53, 54, 58, 88, 224, 273, 282, 284, 285, 295, 302 images, 235 imbalances, 298 impact analysis, 334 impact assessment, 350 implementation, 36, 88, 154, 229, 238, 302, 330, 346, 375 imports, 124 incentive, viii, 2, 4, 13, 22, 24, 28, 29, 33, 37, 49, 110, 228, 243, 245, 300, 301 incentives, 3, 5, 13, 23, 24, 30, 33, 37, 45, 46, 56, 68, 73, 108, 131, 140, 205, 244, 245, 250, 300, 301, 306, 330, 346 inclusion, 327, 377 income, 6, 33, 38, 46, 65, 94, 119, 228, 244, 276, 308, 330 income tax, 33, 46, 94, 276 incomplete combustion, 327 increased competition, 31, 240

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Index incumbents, 352 independent variable, 184, 186 India, vii, 2, 40, 51, 52, 124 Indian, 14, 176, 234, 283 Indiana, 129, 130, 202, 261, 273, 285, 286, 295, 359 indication, 57, 175 indicators, 140 indices, 35 indigenous, 119, 153 indirect effect, 334 induction, 133, 138, 159, 160, 190 industrial, 26, 49, 159, 210, 213, 240 industry, vii, viii, ix, 2, 3, 4, 6, 7, 9, 12, 15, 18, 22, 25, 27, 29, 32, 36, 38, 45, 47, 60, 62, 63, 64, 65, 66, 68, 76, 77, 82, 87, 88, 89, 104, 105, 106, 108, 110, 112, 115, 119, 124, 127, 131, 133, 139, 144, 148, 149, 150, 151, 152, 153, 155, 156, 159, 160, 161, 162, 165, 166, 168, 169, 172, 173, 174, 178, 181, 193, 199, 206, 208, 209, 210, 211, 219, 226, 227, 228, 231, 238, 241, 245, 252, 273, 275, 288, 296, 306, 308, 309, 311, 315, 318, 330, 332, 333, 334, 336, 338, 340, 341, 350, 351, 352, 368, 369, 370, 372, 373, 374, 375, 376, 377, 378 infection, 214 inflammation, 214 inflation, 33, 34, 87, 110, 168, 200, 276, 288, 301 inflationary pressures, 309 Information Age, ix, 105 information exchange, 345 Information System, 72 infrastructure, vii, 1, 3, 5, 27, 28, 87, 111, 115, 124, 127, 128, 154, 156, 158, 199, 200, 205, 206, 208, 214, 215, 216, 225, 243, 244, 248, 262, 307, 317, 362, 375 initial state, 56, 324 initiation, 67 injection, 160 innovation, 12, 133, 139, 140, 142, 152, 154, 238, 240 Innovation, 139, 337, 381 insecurity, 3 insight, 91 inspection, 158, 159 inspections, 156 in-state, 37, 53, 90, 93, 363, 369 institutions, 211, 219, 227 instructors, 176 instruments, 198, 229 insulation, 143, 222 insurance, 81, 149, 288 integration, vii, viii, ix, 1, 5, 12, 16, 20, 22, 24, 47, 73, 83, 84, 92, 97, 104, 106, 112, 113, 125, 147, 182, 183, 186, 187, 192, 194, 198, 199, 207, 209,

395

236, 254, 255, 256, 270, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 351, 364, 373, 374, 375, 376, 378 intelligence, 207 intensity, 26 interaction, 156, 227, 341, 343, 355, 358, 361, 375 interactions, 78, 153, 221, 349, 372, 376 IntercontinentalExchange, 91 interdependence, 154 interdisciplinary, 340 interest groups, 359 interest rates, 30, 35, 149 interface, 190, 191, 377 interference, 11, 26, 27, 44, 355, 356, 372 Intergovernmental Panel on Climate Change, 101, 120, 126, 211, 235 Intergovernmental Panel on Climate Change (IPCC), 120, 211 intermediaries, 66 International Energy Agency, 38, 101, 209 international markets, 15 international standards, 151 interstate, 199, 200, 206, 284, 286, 329 interval, 196, 297, 299, 326, 329 interviews, 246 intrastate, 206 inventors, 3 investment, 3, 19, 26, 27, 28, 33, 34, 35, 46, 60, 62, 63, 65, 85, 86, 87, 89, 92, 101, 110, 124, 125, 127, 131, 140, 144, 149, 151, 156, 158, 166, 173, 178, 199, 200, 201, 202, 204, 205, 238, 254, 268, 272, 294, 301, 308, 310, 327, 341 investment bank, 3 investment incentive, 301 investors, 63, 64, 65, 94, 106 IPCC, 101, 120, 126, 211, 212, 215, 235 Iran, 122, 124 Ireland, 16, 17 IRP, 101, 240 irrigation, 121, 214 IRS, 64, 88 IS, 9, 28 ISO, 44, 48, 58, 86, 90, 93, 97, 101, 102, 181, 186, 194, 195, 198, 200, 202, 206, 209, 213, 253, 296, 297, 381 isolation, 180, 183, 186, 205 Italy, 51 ITC, 101, 110, 301, 328

J January, 26, 34, 37, 38, 40, 43, 60, 86, 163, 194, 218, 277, 333

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Index

396 job creation, 340, 364 jobs, 6, 7, 9, 61, 94, 119, 173, 174, 273, 306, 308, 312, 313, 314, 315, 316, 317, 318, 340, 373 joints, 142 Jordan, 209, 236, 323 judge, 350, 371 judgment, x, 90, 91, 335 Jun, 194 jurisdiction, 224, 239, 341 jurisdictions, 25, 228, 229, 240

K K-12, 369, 373 Kentucky, 215, 273, 282, 286 killing, 225 King, 210 Klamath River Basin, 236 Kyoto Protocol, 103

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

L LA, 214, 234 labor, 142, 156, 157, 165, 174, 175, 288, 307, 309, 365, 377 labor force, 175, 377 labor-intensive, 174 lakes, 214 land, 6, 12, 25, 29, 38, 42, 53, 56, 81, 111, 112, 115, 128, 130, 135, 136, 149, 153, 154, 155, 156, 157, 158, 159, 161, 162, 165, 194, 212, 215, 216, 224, 225, 226, 229, 242, 243, 244, 248, 249, 251, 253, 254, 256, 262, 282, 283, 284, 285, 286, 288, 293, 309, 310, 311, 314, 317, 327, 329, 338, 364, 367 land use, 112, 155, 215, 216, 224, 251, 284, 286 landscapes, 26, 221 language, 233 large-scale, 12, 24, 53, 127, 135, 139, 144, 158, 159, 166, 183, 199, 218, 231, 237, 243, 331 lattice, 43 law, 17, 18, 26, 33, 36, 46, 134, 135, 226, 228, 301, 328 law enforcement, 135 laws, 205, 224, 328 LC, 101, 254, 270, 303 lead, 5, 6, 13, 39, 53, 85, 110, 148, 151, 155, 196, 211, 214, 219, 226, 227, 250, 333, 336, 338, 363 leadership, 110, 158, 190, 226, 233, 359, 360, 361 leakage, 317 learning, 3, 36, 139, 144, 146, 147, 154, 161, 162, 176, 219, 227, 251, 289, 344 legislation, 2, 29, 30, 31, 33, 239, 356

legislative, 293 liberalization, 18 licensing, 174 life span, 268 lifecycle, 38, 211 life-cycle, 133, 146, 155, 156, 157, 168, 211, 233, 275 life-cycle cost, 133, 157, 168, 275 lifetime, 21, 147, 148, 329 limitation, 82 limitations, 34, 39, 40, 96, 156, 169, 172, 211 linear, 133, 219, 251, 298, 299, 334 linear function, 298 linear programming, 251 linkage, 159 links, 235 liquefied natural gas, 101, 122 liquidity, 95 livestock, 244, 271 LM, 225 LNG, 101, 122, 124 loan guarantees, 34, 42, 46 loans, 149 lobby, 346 local authorities, 224 local community, 228 local government, 6, 13, 242, 343 location, 14, 18, 22, 44, 59, 60, 73, 86, 87, 89, 107, 112, 147, 169, 172, 205, 222, 246, 251, 265, 296, 314, 318, 337 London, 208, 234, 236 long distance, 201, 243 long-distance, 199 longevity, 142 long-term, 33, 42, 54, 65, 66, 74, 82, 95, 107, 134, 138, 143, 149, 155, 156, 158, 206, 221, 229, 231, 247, 329, 341, 351, 355 Los Angeles, 321 losses, viii, 2, 65, 122, 143, 146, 147, 149, 154, 156, 162, 199 Louisiana, 261, 273, 282, 285, 286 Low cost, 168 low power, 12, 137, 143 low-density, 168 lower prices, 96 low-level, 216 low-power, 137 lung, 214 lung function, 214 lungs, 214

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Index

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

M machinery, 132, 162, 168, 169, 222, 308, 346 machines, 3, 10, 17, 123, 127, 130, 131, 132, 133, 135, 137, 138, 139, 144, 151, 158, 159, 161, 165, 166, 169, 188, 243 macroeconomic, 312 Madison, 59, 223, 235, 237 magnet, 143, 146, 159, 160, 168 magnetic, 143, 160, 168 magnetic field, 143 magnetic materials, 168 magnetic properties, 160 magnets, 143, 160, 166, 168, 178 Maine, 54, 176, 273, 282, 285 mainstream, vii, 1, 127 maintenance, viii, 17, 33, 38, 41, 47, 81, 91, 96, 102, 124, 132, 138, 139, 142, 143, 146, 147, 149, 153, 157, 158, 159, 177, 224, 228, 229, 244, 254, 288, 307, 318, 328, 374 Maintenance, 81, 91, 165 mammals, 219 management, ix, x, 152, 153, 177, 186, 199, 211, 219, 220, 221, 225, 231, 233, 283, 319, 335, 336, 337, 355, 356, 364, 366, 375, 378, 384, 385 management practices, 225 mandates, 225, 301, 370 manpower, 345 manufacturer, 14, 58, 59, 60, 68, 90, 97, 152, 174, 308, 329, 333 manufacturing, viii, ix, 7, 12, 14, 15, 19, 48, 59, 60, 61, 88, 90, 92, 104, 105, 106, 108, 111, 119, 127, 131, 134, 139, 141, 144, 146, 147, 149, 151, 154, 157, 158, 160, 161, 162, 165, 166, 168, 169, 170, 171, 172, 173, 174, 175, 178, 213, 240, 245, 249, 273, 307, 308, 310, 311, 314, 315, 316, 318, 340, 373, 374 mapping, 8, 39, 284, 285, 286 marine environment, 154, 244 marine mammals, 232 maritime, 9 market, viii, ix, 2, 6, 8, 10, 14, 19, 27, 30, 37, 45, 47, 48, 49, 50, 52, 58, 59, 62, 63, 65, 66, 71, 72, 74, 78, 83, 87, 89, 90, 91, 94, 95, 96, 97, 106, 110, 112, 123, 124, 127, 131, 143, 150, 151, 159, 160, 162, 173, 175, 180, 182, 186, 192, 193, 198, 206, 207, 211, 238, 239, 241, 242, 243, 244, 245, 247, 249, 251, 252, 254, 270, 273, 288, 298, 314, 330, 333, 334, 337, 338, 340, 341, 342, 352, 353, 354, 355, 367, 373, 374, 383, 384, 385 market failure, 30 Market forces, 247 market prices, 66, 71, 206, 243

397

market segment, 245 market share, 14, 58, 90, 270, 340, 373 market structure, 180, 239 market value, 96 marketing, 29, 90, 93, 95 markets, ix, 10, 15, 40, 59, 72, 88, 97, 105, 106, 108, 110, 115, 122, 124, 153, 179, 187, 188, 194, 198, 199, 206, 237, 238, 239, 240, 241, 242, 243, 245, 246, 247, 249, 256, 260, 262, 298, 345, 362 Maryland, 72, 103, 252, 273, 282, 285, 295, 302, 359 Massachusetts, 9, 22, 36, 39, 40, 43, 54, 56, 72, 176, 221, 230, 231, 273, 282, 285, 302, 321, 337, 359, 380 Massachusetts Institute of Technology, 22, 36, 321, 337, 380 maximum term, 18 measurement, 157, 165, 284, 305 measures, 25, 32, 89, 180, 194, 210, 330, 337, 384, 385 mechanical energy, 328, 331 median, 194 megawatt, ix, 5, 9, 14, 20, 21, 22, 23, 36, 40, 41, 42, 102, 105, 112, 122, 131, 138, 165, 178, 180, 186, 218, 252, 254, 267, 270, 271, 289, 292, 295, 297, 298, 299, 326, 328, 329, 330 membership, 327, 342, 377 mercury, 6, 101, 118, 121, 213, 235, 236, 242, 273, 292, 300 Mercury, 100, 234, 235, 236, 300 metals, 168 meteorological, 158, 192, 329 methane, 328 methylmercury, 214 metric, 22, 24, 31, 42, 53, 54, 79, 102, 118, 119, 120, 121, 166, 167, 168, 178, 193, 212, 247, 260 Mexico, 28, 39, 53, 54, 55, 67, 84, 87, 98, 103, 174, 176, 177, 181, 200, 205, 273, 282, 301, 302, 321 Mid-Atlantic states, 9 Middle East, 124 migration, 25, 217 migratory birds, 225 military, 6, 26, 27, 216, 225, 356 mineral resources, 39 Minerals Management Service, 9, 56, 102, 153, 164, 226 Minerals Management Service (MMS), 9, 153, 226 minimum price, 18 mining, 118, 142, 210, 215, 216, 217 Minnesota, 4, 13, 37, 53, 54, 55, 58, 59, 87, 97, 102, 176, 181, 183, 186, 187, 196, 198, 200, 205, 208, 210, 216, 245, 273, 282, 285, 286, 301, 302, 308, 318, 343, 344, 351 minority, 95, 221, 280

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Index

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

398

mirror, 78 misleading, 59, 93 missions, 18, 33, 38, 118, 119, 120, 121, 122, 212, 213, 236, 237, 274, 330, 352, 374 Mississippi, 261, 273, 282, 285, 286 Missouri, 54, 273, 286, 287 Mitsubishi, 14, 58, 59, 319, 320, 379 MMS, 9, 26, 39, 102, 153, 155, 164, 226, 229, 230, 243 model system, 268 modeling, 106, 108, 112, 122, 151, 157, 169, 170, 196, 211, 247, 250, 251, 268, 269, 270, 285, 310, 332, 333, 341, 364, 374, 375, 376, 378 models, 18, 25, 26, 82, 112, 133, 156, 157, 160, 169, 190, 191, 193, 205, 219, 245, 276, 340, 341, 345, 350, 354, 374, 375, 376 moisture, 158 momentum, 108, 199, 338 money, 33, 45, 298, 308, 309, 312, 343, 364, 378 monopoly, 330 Montana, 20, 39, 54, 94, 273, 282, 287, 302 Monte Carlo, 194 Moon, 210 moratorium, 26 morning, 26, 185 mortality, 25, 217, 218, 233 mortality risk, 217 mortgage, 33 motion, 7, 136, 142, 331 motion control, 142 motor system, 11 MOU, 102 movement, 68, 72, 183, 331 MS, 176 multiplier, 293 MVA, 102, 297

N NA, 291, 292 NAS, 102, 233 NASA, 148, 156 nation, ix, 27, 104, 105, 106, 111, 112, 118, 121, 123, 124, 165, 175, 194, 242, 243, 311, 318 national, ix, 3, 5, 8, 13, 26, 29, 32, 70, 90, 92, 93, 104, 107, 115, 118, 123, 124, 126, 161, 166, 168, 169, 173, 206, 210, 215, 226, 227, 229, 233, 240, 242, 249, 254, 256, 260, 262, 265, 271, 280, 283, 293, 294, 300, 307, 341, 343, 346, 354, 375, 376 National Academy of Sciences, 25, 43, 102, 226 National Academy of Sciences (NAS), 226 National Defense Authorization Act, 26 National Development and Reform Commission, 41

National Oceanic and Atmospheric Administration (NOAA), 102, 156 National Oceanic and Atmospheric Administration 156 National Park Service, 283 National Research Council, 43, 102, 217, 236 National Science and Technology Council, 102, 179 national security, 26 National Weather Service, 102, 156 Native American, 244, 245, 340, 366, 367, 384 Native Americans, 340, 366, 384 natural, vii, 1, 4, 6, 17, 21, 24, 26, 30, 31, 32, 33, 38, 39, 41, 44, 45, 49, 50, 57, 77, 95, 101, 110, 115, 116, 121, 122, 123, 124, 148, 165, 174, 176, 182, 199, 202, 212, 213, 215, 238, 250, 251, 257, 259, 260, 293, 294, 296, 327, 328 natural gas, vii, 1, 4, 6, 17, 21, 24, 30, 31, 32, 33, 38, 39, 41, 44, 45, 49, 50, 57, 77, 95, 101, 110, 115, 116, 121, 122, 123, 124, 148, 165, 174, 199, 202, 213, 215, 238, 250, 257, 259, 260, 293, 294, 296, 327 ND, 305 Nebraska, 39, 54, 55, 273, 283, 286, 322, 359 NEC, 173 NEMS, 102, 341, 375, 376, 377 nesting, 43 net income, 38 net present value, 102, 203, 270, 312, 313 Netherlands, 236 network, 27, 28, 29, 105, 199, 373 Nevada, 84, 100, 273, 277, 282, 302, 359 New England, 9, 58, 67, 70, 72, 77, 80, 81, 93, 101, 102, 171, 206, 252, 277, 293, 295 New Jersey, 56, 72, 103, 179, 252, 273, 282, 285, 295, 301, 302 New Mexico, 28, 39, 53, 54, 55, 84, 87, 98, 103, 176, 177, 181, 200, 205, 273, 282, 301, 302, 321 New York, 15, 25, 38, 54, 56, 58, 65, 67, 72, 93, 94, 102, 177, 181, 190, 202, 206, 209, 213, 223, 234, 235, 237, 252, 273, 277, 282, 284, 285, 286, 294, 295, 302 New York Mercantile Exchange, 294 New York Times, 38 newsletters, 345 next generation, 21, 130, 153, 373 NGO, 173 NGOs, 102, 226, 227, 228, 233, 343 niche market, 131 Nielsen, 164, 165, 234, 273 nitrogen, 6, 36, 102, 121, 213, 242, 329 nitrogen oxides, 36, 102, 121, 213, 242 NOAA, 102 nodes, 71, 73, 96

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Index noise, 6, 26, 160, 222, 234, 329 non-binding, 37 nongovernmental, 102, 226, 325 nongovernmental organization, 102, 226, 325 non-profit, 342 normal, 12, 95, 298 normal conditions, 12 North America, 14, 16, 60, 63, 102, 107, 161, 163, 173, 175, 177, 188, 237, 253, 283, 317, 327, 376 North Carolina, 15, 88, 273, 282, 285, 359 Northeast, 57, 102, 120, 171, 172, 236, 272, 273, 376 NRC, 102, 217, 219, 236 nuclear, 2, 3, 6, 12, 17, 19, 20, 21, 22, 23, 24, 33, 34, 41, 42, 44, 46, 112, 121, 174, 194, 199, 211, 212, 215, 223, 251, 253, 268, 293, 294, 327, 330 nuclear energy, 3, 34, 215 nuclear power, 6, 12, 17, 21, 23, 24, 34, 41, 46, 121, 174 nuclear power plant, 6, 12, 41, 46, 121, 174 nuclear reactor, 42, 174 nuclear technology, 19 NYMEX, 274

399

operator, 29, 48, 101, 183, 186, 188, 192, 198, 202, 203, 213, 329, 353 Operators, 19, 188, 209 opposition, 9, 11, 13, 25, 28, 205, 206, 221 optimization, 112, 115, 156, 201, 254, 287, 295, 298, 299 Oregon, 13, 53, 54, 88, 143, 177, 218, 273, 282, 285, 287, 302, 351 organic, 327 organic matter, 327 organization, 25, 48, 151, 172, 214, 227, 314, 343, 369 organizations, 28, 32, 57, 102, 106, 111, 120, 178, 190, 199, 205, 226, 246, 248, 319, 324, 325, 332, 338, 342, 348, 365, 368, 373, 375 outliers, 95, 96 overload, 135 oversight, 27, 37, 45, 319, 327 ownership, 65, 66, 67, 90, 94, 244, 245, 329, 362 oxidation, 327 oxides, 6, 103, 329 oxygen, 329 ozone, 102, 328

O

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

P objective criteria, x, 335 obligation, 328 obligations, 72 observations, x, 271, 335 obstruction, 222 oceans, 7, 331 Office of Management and Budget, 103, 269, 270, 303, 305, 312, 313, 332 Office of Surface Mining, 234 offshore, 7, 9, 12, 18, 26, 39, 40, 53, 56, 89, 107, 112, 115, 128, 130, 136, 153, 154, 155, 156, 157, 158, 161, 162, 163, 164, 165, 215, 221, 226, 229, 230, 231, 232, 234, 235, 237, 242, 243, 249, 251, 252, 253, 254, 256, 262, 275, 284, 285, 287, 288, 290, 309, 311, 314, 317, 338 offshore oil, 154, 155 Ohio, 56, 88, 115, 202, 261, 273, 285, 286, 295, 359 oil, 6, 30, 31, 39, 45, 78, 95, 110, 123, 154, 155, 157, 169, 174, 194, 213, 215, 217, 238, 327 oil spill, 217 Oklahoma, 15, 39, 54, 55, 159, 273, 286, 301, 302, 351 OMB, 103, 269, 270, 303, 305 online, 45, 94, 96, 176, 202, 237, 244, 315, 332 on-line, 4 open space, 222 openness, 246

Pacific, 13, 44, 55, 65, 171, 304, 321, 344 packaging, 168 paints, 106, 108 paper, 41, 92, 208, 209, 332 Paper, 38, 39, 179, 207, 353 Paris, 209 particles, 214 partnership, 64, 226, 227, 363, 371, 373 partnerships, vii, 2, 150, 338, 370, 374 passive, 140, 147, 159 pathways, 146, 147, 161, 336 pay-as-you-go, 94 PAYGO, 94 peak demand, 182, 280 peer, ix, x, 97, 216, 219, 332, 335, 336, 337, 340 peer review, ix, x, 97, 332, 335, 336, 337 peers, ix, 335 penalties, 11, 28, 32, 142, 293 penalty, 86, 293 Pennsylvania, 25, 54, 59, 60, 61, 72, 103, 173, 179, 234, 252, 273, 285, 286, 295, 302 percentile, 194 perceptions, 211, 233, 246 performance, viii, 21, 22, 26, 27, 36, 47, 74, 75, 79, 80, 89, 91, 93, 96, 106, 107, 108, 110, 112, 113, 114, 119, 124, 131, 134, 139, 140, 142, 143, 146, 147, 149, 151, 152, 153, 160, 162, 166, 181, 188,

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

400

Index

190, 191, 198, 249, 250, 251, 252, 253, 254, 255, 256, 275, 278, 288, 289, 290, 293, 294, 295, 306, 311, 328, 351, 353, 360, 374, 376 performance indicator, 256 periodic, 50, 238 permit, 9, 29, 77, 107, 224, 225, 230, 231, 249, 271 personal, 90, 240, 308, 309, 376 personal communication, 90 petroleum, 124, 167, 327 Petroleum, 45, 99, 123, 155 PGE, 103, 194 Phoenix, 237 phone, 332 photovoltaics, 160 physiology, 229 pilots, 222 pitch, 40, 130, 132, 135, 137, 140, 142, 160, 169 planetary, 138 planning, 6, 57, 62, 86, 87, 88, 101, 119, 179, 180, 182, 192, 193, 196, 201, 204, 216, 219, 226, 228, 229, 231, 232, 240, 247, 250, 251, 253, 254, 264, 265, 275, 294, 297, 319, 336, 338, 341, 342, 347, 375, 377, 378 plants, viii, 2, 3, 6, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 25, 26, 27, 28, 29, 30, 32, 33, 34, 36, 37, 38, 39, 41, 42, 44, 50, 59, 77, 81, 92, 100, 101, 114, 125, 128, 131, 137, 139, 143, 153, 156, 158, 174, 181, 182, 183, 186, 188, 191, 192, 194, 196, 198, 199, 201, 210, 213, 214, 215, 223, 229, 240, 243, 251, 252, 253, 257, 259, 268, 270, 271, 291, 292, 293, 294, 297, 305, 308, 309, 315, 318, 326, 327, 328, 331, 334, 349 plastic, 100, 101, 167, 169 plastics, 175 platforms, 157, 217, 345 play, 25, 76, 87, 121, 142, 180, 194, 212, 241, 242, 244, 329, 369, 374, 378 plug-in, 199, 207 PMA, 103, 241 point-to-point, 86 poisonous, 327 policy initiative, 354 policy makers, 118, 199, 341, 365, 374 pollutant, 326 pollutants, 121, 126, 213, 242 pollution, 17, 20, 30, 41, 118, 119, 214, 242, 270 polymer, 168 polynomial, 78 pond, 270 poor, 3, 13, 149, 287 population, 9, 56, 70, 173, 214, 221, 222, 244, 252, 276, 288, 293, 310 population density, 70, 244, 252, 288, 293, 310

population growth, 214 portfolio, viii, ix, 2, 3, 4, 13, 20, 48, 49, 104, 106, 108, 119, 120, 123, 180, 201, 204, 229, 233, 242, 256, 300, 327, 330, 340, 351, 353, 374 portfolios, 180 Portugal, 16, 17, 51, 63 posture, 192 powder, 21 power marketing administration, 29 power plant, 4, 6, 7, 8, 11, 17, 19, 21, 22, 28, 33, 37, 39, 44, 77, 89, 106, 124, 129, 138, 144, 149, 152, 154, 157, 174, 182, 188, 194, 213, 214, 216, 229, 239, 242, 243, 244, 245, 271, 272, 298, 307, 309, 311, 326, 327, 329, 330, 331, 341, 343, 351, 378 power plants, 4, 6, 7, 12, 19, 21, 22, 37, 39, 41, 46, 77, 89, 121, 124, 138, 144, 149, 157, 174, 182, 188, 213, 214, 216, 229, 239, 242, 243, 245, 271, 272, 307, 309, 311, 326, 341, 343, 378 power stations, 174 powers, 93 PPA, 48, 66, 95, 103, 240, 329 PPM, 16, 95 prediction, 106, 112, 353 predictors, 82 preference, 4, 240 premature death, 214 premium, 31, 35, 158, 159 present value, 33, 45, 102, 203, 270, 303, 312, 313 President Bush, ix, 104 pressure, 68, 77, 198 price changes, 309 price deflator, 35, 36, 42 price elasticity, 259 price signals, 199, 207 price stability, 124, 206 prices, vii, viii, ix, 1, 2, 3, 4, 5, 6, 12, 18, 19, 22, 23, 24, 32, 33, 36, 47, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 78, 79, 89, 90, 91, 95, 96, 104, 107, 110, 119, 123, 131, 138, 144, 174, 198, 202, 206, 225, 238, 242, 243, 252, 254, 259, 260, 294, 296, 305, 353 priorities, x, 227, 233, 239, 335, 336 pristine, viii, 2 private, vii, 2, 12, 25, 42, 91, 106, 216, 226, 227, 228, 238, 283, 284, 294, 338, 371 private property, 228 private sector, 12, 294, 371 proactive, 86, 178, 346 probability, 34, 101, 193, 288 producers, 15, 18, 30, 31, 34, 66, 81, 110, 197, 238 production, vii, viii, 1, 2, 3, 4, 5, 6, 13, 14, 15, 19, 20, 21, 22, 23, 24, 29, 30, 31, 32, 33, 34, 37, 38, 41, 42, 45, 48, 50, 58, 60, 89, 92, 93, 94, 103,

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Index 107, 108, 114, 115, 120, 122, 124, 127, 130, 131, 137, 138, 139, 144, 146, 147, 149, 156, 157, 165, 166, 168, 169, 172, 174, 175, 178, 192, 194, 195, 196, 197, 198, 199, 201, 202, 207, 210, 213, 214, 215, 216, 238, 245, 248, 250, 262, 271, 300, 301, 306, 309, 325, 329, 330, 332 production costs, 192 productivity, ix, x, 110, 112, 140, 143, 174, 309, 314, 326, 335, 337, 352, 383, 384, 385 profit, 288, 342 profitability, 11, 68, 78 program, x, 12, 22, 34, 45, 46, 87, 88, 148, 157, 176, 216, 227, 231, 232, 233, 243, 299, 302, 326, 330, 335, 336, 337, 338, 340, 342, 343, 345, 346, 350, 355, 359, 360, 361, 362, 363, 366, 367, 369, 370, 371, 372, 373, 377, 384, 385 proliferation, 200 promote, 28, 110, 115, 262, 302, 362, 374 property, 6, 81, 87, 211, 223, 224, 228, 232, 288, 310, 317, 329, 354, 364 property taxes, 6, 228, 288, 310, 317 proposition, 27 protection, 25, 137, 210, 225 prototype, 140, 142, 143, 151 PTCs, 94, 108, 238 public, vii, 2, 9, 12, 27, 28, 29, 33, 34, 36, 44, 46, 48, 56, 86, 91, 106, 150, 159, 162, 182, 205, 210, 211, 212, 216, 221, 224, 225, 226, 227, 228, 229, 232, 233, 238, 239, 240, 246, 307, 332, 338, 349, 368, 371, 376 public interest, 238 public notice, 29 public policy, 162, 227 public sector, 240 public service, 211, 225 public support, 150, 210, 211, 221, 233 public-private partnerships, vii, 2 pultrusion, 160 pumping, 131 pumps, 169 punitive, 86 purchasing power, 298

Q Qatar, 122, 124 quality assurance, 157 quality control, 158 quality of life, 224 Quebec, 67 query, 165

401

R R&D, 12, 40, 59, 92, 103, 156, 274, 338, 340, 354, 374, 377 radar, viii, 2, 5, 6, 11, 26, 27, 216, 225, 226, 355, 356, 372 radiation, 328, 330 radical, 143 radioactive waste, 17 radius, 354 rail, 135 rain, 118, 211, 217, 273, 329, 330 range, 20, 23, 32, 49, 66, 69, 70, 71, 73, 91, 96, 97, 106, 125, 146, 147, 151, 154, 155, 156, 159, 166, 175, 182, 185, 187, 188, 193, 196, 201, 202, 212, 214, 215, 216, 217, 233, 237, 243, 246, 272 rate of return, 205 rating agencies, 91 ratings, 133 raw material, 143, 165, 166, 167, 168, 170, 175, 178 raw materials, 143, 165, 166, 167, 170, 178 real time, 185, 350 reality, 115, 148, 193, 262 recall, 14 recognition, 57, 123, 206 reconcile, 89 reconciliation, 298 recovery, 33, 45, 156, 189, 190, 204, 354 recreation, 283 recreational, 232 recruiting, 340, 377 red light, 222 reduction, 3, 17, 87, 88, 115, 119, 121, 122, 124, 137, 144, 147, 154, 157, 174, 186, 214, 215, 238, 240, 242, 250, 253, 257, 260, 270, 271, 363 refining, 354 reflection, x, 335, 337 reforms, 94, 180, 206, 330 refuge, 283 regional, 28, 32, 48, 57, 70, 72, 73, 80, 86, 97, 119, 120, 125, 155, 169, 186, 198, 199, 200, 201, 205, 207, 239, 246, 249, 253, 259, 271, 275, 277, 284, 288, 293, 295, 297, 305, 307, 310, 327, 330, 334, 341, 344, 347, 349, 360, 363, 375, 376 regular, 376 regulation, 36, 84, 85, 88, 89, 108, 183, 188, 214, 228, 257, 259, 260, 299, 300, 306, 343 regulations, 29, 43, 121, 181, 224, 226, 239, 245, 250, 300 regulators, 199, 233, 344, 345 Regulatory Commission, 44 regulatory framework, 10, 211, 239 regulatory requirements, 220, 224

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

402

Index

relationship, 74, 245, 254, 344, 378 relationships, 8, 35, 309, 334 relevance, ix, 335 reliability, 3, 19, 28, 110, 116, 127, 128, 138, 139, 140, 142, 143, 146, 149, 152, 155, 158, 160, 168, 182, 183, 188, 192, 193, 197, 198, 199, 200, 204, 205, 206, 207, 238, 245, 257, 268, 288, 296, 327, 374, 375 Reliability, 20, 38, 48, 93, 100, 101, 102, 103, 105, 107, 110, 132, 152, 159, 165, 188, 193, 198, 208, 209, 236, 253, 276, 277, 317, 321, 327, 374, 375 renewable energy, ix, 2, 3, 4, 9, 18, 20, 28, 29, 30, 31, 32, 33, 34, 37, 39, 45, 48, 54, 67, 68, 72, 86, 87, 88, 103, 104, 108, 110, 118, 120, 124, 131, 150, 176, 177, 178, 203, 205, 211, 238, 240, 242, 247, 252, 301, 328, 330, 370, 371 Renewable Energy and Energy Conservation Tax Act, 30 renewable resource, 86, 318, 330 rent, 81 repair, 150, 157, 159 repeatability, 160 reproduction, 219 reputation, 3 research, vii, x, 3, 10, 12, 26, 84, 91, 103, 127, 139, 142, 144, 148, 155, 156, 158, 166, 176, 177, 180, 206, 211, 216, 218, 219, 220, 226, 227, 228, 229, 231, 232, 233, 238, 332, 335, 336, 340, 353, 355, 357, 358, 359, 373, 374, 375 research and development, vii, 3, 10, 12, 103, 336 Research and Development, 12, 102, 209, 374 researchers, ix, x, 3, 218, 228, 335, 351, 373 reserves, 124, 180, 182, 183, 186, 187, 188, 192, 193, 197, 298, 299 reservoir, 12 reservoirs, 214 residential, 159, 204, 223, 239, 270 resins, 166, 167, 178 resistance, 136 resolution, 278, 282, 283, 284, 286, 287, 343, 346, 351 resources, vii, ix, 2, 5, 6, 7, 8, 13, 14, 18, 21, 27, 29, 32, 39, 44, 45, 56, 57, 86, 104, 105, 107, 110, 111, 112, 114, 121, 122, 124, 125, 130, 147, 153, 165, 166, 169, 176, 180, 181, 182, 183, 185, 186, 193, 194, 199, 201, 203, 204, 205, 206, 207, 209, 211, 214, 215, 219, 225, 229, 240, 242, 243, 248, 249, 250, 251, 253, 254, 257, 261, 265, 268, 271, 275, 284, 286, 306, 309, 318, 328, 330, 338, 341, 342, 343, 344, 346, 365, 366, 367, 371 respiration, 327 respiratory, 214 responsibilities, 56, 224

restructuring, 18, 45, 108, 110, 199, 240 retail, 32, 54, 90, 93, 159, 160, 199, 239, 240, 245, 330 retained earnings, 46 retirement, 123 retrenchment, 89 revenue, viii, 2, 6, 8, 31, 38, 66, 67, 72, 73, 95, 131, 134, 149, 224, 241, 247, 364 rewards, 228 Rhode Island, 56, 72, 115, 216, 273, 282, 285, 302 Richland, 126, 304, 305 rights-of-way, 229 risk, 7, 21, 45, 64, 66, 125, 127, 139, 140, 142, 148, 149, 150, 151, 152, 153, 156, 157, 158, 161, 193, 211, 214, 219, 221, 227, 231, 232, 233, 240 risk management, 221, 231 risk profile, 21 risks, 123, 124, 139, 149, 210, 211, 212, 217, 219, 220, 226, 227, 231, 232, 233, 241, 247 rivers, 247 Roads, 225 Robert Gates, 319 robustness, 207 rolling, 194 roughness, 133, 282, 283, 285 routines, 256 royalties, 288 royalty, 6 RP, 169 rural, 6, 29, 119, 131, 132, 224, 238, 239, 244, 245, 317, 318, 362, 368, 369 rural areas, 362 rural communities, 317 rural development, 6 Russia, 122, 124

S safety, 9, 26, 39, 135, 137, 155, 212 salaries, 41, 309, 311 salary, 308 sales, 41, 49, 54, 65, 66, 67, 68, 69, 70, 73, 74, 90, 93, 95, 163, 175, 223, 330 sample, ix, 48, 69, 70, 71, 73, 74, 76, 77, 79, 80, 82, 93, 94, 95, 96, 97, 355 sand, 167, 237 satellite, 156 savings, 119, 122, 123, 136, 202, 203, 214, 215, 248, 261, 271, 272, 303 scaling, 78, 134, 136, 139, 158, 343 scarcity, 81, 121 scatter, 74 scheduling, 5, 28, 85, 185, 192, 198, 327

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Index school, 49, 66, 176, 177, 317, 318, 369, 373 scientific understanding, 211 scientists, 3 scores, 337 seabed, 154 searches, 91 seasonal variations, 287 seasonality, 366 Seattle, 55 Securities and Exchange Commission, 91 security, vii, 2, 5, 26, 106, 118, 119, 120, 123, 124, 183, 206, 210 selecting, 206, 240 Self, 146, 164, 245 semiconductor, 146 senate, 44 Senate, viii, 2, 30, 31, 32, 39, 304 sensitivity, 106, 137, 227, 248 sensors, 130, 137, 146, 207 SEPA, 103 separation, 204 series, viii, 45, 47, 81, 82, 305, 327, 340, 341, 366 services, 91, 119, 144, 151, 185, 186, 188, 198, 207, 214, 240, 308, 311, 317, 318, 330 Shanghai, 41 shape, 140, 280, 324 shaping, 186 shareholders, 239 shares, 228, 240 sharing, 198, 284, 296, 361, 376 shear, 134, 142, 147, 154, 157, 286 Shell, 62, 95 shelter, 65 shingles, 178 shipping, 15, 39, 157, 160 shocks, 238 short period, 174, 180, 182, 328 shortage, 5, 18, 19, 29, 65, 66, 68, 78, 110 short-term, 54, 66, 73, 192, 214 Short-term, 155 shy, 25 SI, 338, 340, 341, 342, 344, 374, 375, 376 Siemens, 14, 40, 58, 59, 154 signaling, 198 signals, 27, 137, 199, 207 silicon, 103, 143 silver, 106 simulation, 190, 272, 301 simulations, 222 sites, 2, 9, 12, 14, 18, 27, 49, 59, 80, 112, 135, 137, 159, 194, 212, 215, 217, 218, 219, 221, 225, 226, 227, 229, 233, 244, 253, 293, 297, 298, 299, 326, 331, 341, 354, 358, 371

403

skilled labor, 175, 377 skilled personnel, 175, 377 skills, 175, 340 sludge, 17 smog, 214 SO2, 103, 242, 291, 292, 293, 300, 329, 330 social costs, 73 socioeconomic, 155, 232, 233 software, 27, 198, 308, 318 soil, 124, 154, 327 solar, 7, 18, 19, 34, 44, 89, 328, 329, 330, 340, 341, 348, 368, 371 solar energy, 34, 340 solid waste, 118 solid-state, 133, 138 solutions, 27, 106, 110, 118, 205, 219, 357, 376 songbirds, 226 sounds, 222 South Carolina, 60, 273, 275, 282, 285 South Dakota, 15, 37, 39, 53, 54, 98, 181, 200, 205, 273, 282, 285, 359 Southeastern Power Administration, 103, 241, 381 Southeastern Power Administration (SEPA), 241 Southwestern Power Administration (SWPA), 103, 241 Spain, 16, 17, 51, 52, 110, 144, 145, 221 spare capacity, 187 spatial, 196, 216, 285, 351 species, 25, 210, 212, 215, 216, 218, 225, 227 specificity, 358 spectrum, 57, 136, 322 speed, 8, 10, 11, 12, 40, 112, 130, 133, 134, 135, 136, 137, 138, 142, 146, 154, 156, 157, 159, 160, 161, 168, 188, 191, 245, 254, 281, 284, 286, 287, 328, 331, 353, 378 spills, 217 spin, 10, 12, 130 sponsor, 65 sporadic, 110 spot market, 66, 193, 206 spot-market, 72 SR, 163, 164, 274, 304 stability, 123, 124, 182, 188, 197, 206 stabilization, 120 stabilize, 118, 123 staffing, 375, 376 stages, 56, 139, 143, 146, 231 stakeholder, 106, 221, 246, 247, 324, 338, 341, 343, 345 stakeholders, viii, 2, 106, 108, 110, 210, 211, 219, 227, 228, 231, 232, 233, 244, 246, 247, 325, 338, 343, 345, 350, 352, 357, 358, 368, 375 standard deviation, 69, 103, 195, 196

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

404

Index

standardization, 164 standards, 4, 13, 20, 49, 69, 108, 110, 151, 155, 161, 162, 163, 188, 198, 210, 224, 229, 238, 242, 260, 300, 374 Standards, 31, 45, 103, 151, 163, 164, 247, 300, 301, 360 state borders, 284 statistical analysis, 183, 186 statistics, 208, 250, 375 statutes, 226 steel, 19, 43, 78, 131, 138, 142, 154, 160, 166, 168, 169, 175, 308, 354 steel mill, 308 storage, 12, 17, 20, 186, 210, 299, 348, 378 strain, 175 strategic, 152, 182, 232, 319, 324, 336, 348, 355, 359, 368 strategic planning, 319, 336 strategies, ix, 105, 153, 157, 158, 160, 162, 178, 182, 211, 229, 231, 232, 233, 242, 338, 342, 363, 375 streams, 8, 214, 241, 247, 270, 303, 330 strength, 35, 70, 96, 140, 143, 168, 169 stress, 326 strokes, 214 students, 176, 369, 373 subgroups, 302 subjective, 222 subjectivity, 56 subsidies, 18, 30, 31, 44, 162, 229 subsidy, 34 sulfur, 6, 36, 103, 121, 213, 291, 329, 330 sulfur dioxide, 36, 103, 121, 213, 329 sulfur oxides, 103 summaries, 140 summer, 8, 186, 215, 281, 292 Superfund, 43 supervisors, 211 supplemental, 287, 305, 346 supplements, 271 suppliers, 6, 14, 15, 32, 59, 105, 110, 124, 128, 154, 160, 173, 237, 308, 330, 334 supply, vii, viii, ix, 1, 2, 5, 13, 15, 32, 50, 53, 56, 59, 62, 72, 90, 93, 95, 104, 105, 106, 110, 115, 118, 119, 120, 121, 123, 124, 130, 167, 168, 173, 174, 175, 178, 180, 186, 188, 192, 199, 211, 213, 214, 233, 238, 239, 240, 243, 244, 246, 251, 252, 253, 254, 256, 261, 265, 276, 295, 296, 298, 299, 308, 328, 329, 342 supply chain, 59, 90, 119, 173, 238 supply curve, 106, 254, 256, 295, 296 supply disruption, 123 surface roughness, 133, 282, 283, 285 surging, 57

surplus, 32, 72, 192, 299 surprise, 70 sustainability, 206, 271 sustainable growth, 228 Sweden, 164, 234 SWPA, 103 synchronous, 138, 159 synergistic, 378 synthesis, 343 system analysis, 156 systems, viii, 20, 26, 27, 28, 34, 47, 53, 72, 83, 85, 97, 108, 110, 118, 136, 137, 138, 139, 143, 146, 153, 157, 158, 159, 160, 161, 162, 180, 181, 188, 192, 193, 197, 200, 207, 212, 214, 220, 239, 241, 243, 244, 245, 251, 253, 254, 264, 268, 278, 288, 293, 295, 298, 300, 302, 328, 331, 338, 340, 341, 343, 344, 345, 349, 364, 373, 374, 378

T talent, 178 tangible, 360 targets, 27, 32, 242, 364 tariff, 18, 31, 245, 253 tariffs, 31, 241 task force, 106, 108, 319, 324, 325 tax base, 228, 244 tax credit, viii, 2, 4, 13, 19, 20, 21, 22, 23, 24, 29, 30, 32, 33, 34, 37, 41, 42, 46, 48, 50, 65, 94, 101, 103, 107, 108, 110, 131, 238, 250, 300, 301, 306, 328, 330 tax credits, 30, 37, 41, 94, 108, 110, 238, 300 tax incentive, vii, 1, 3, 15, 30, 45, 49, 63, 67, 87, 88 tax incentives, vii, 1, 3, 15, 30, 45, 49, 63, 67, 87, 88 tax increase, 364 taxes, 6, 29, 31, 33, 46, 81, 228, 288, 310, 317, 334 tax-exempt, 65, 87 taxpayers, 377 teachers, 369 technical assistance, 343, 371, 372, 373 technician, 176, 177 technological advancement, 79, 127, 144 technological progress, 152, 166 telecommunications, 159 temperature, 143, 148, 212, 270, 287, 326 Tennessee, 29, 49, 103, 215, 218, 241, 273, 282, 286 Tennessee Valley Authority (TVA), 29, 49, 103, 241 tension, 211 terawatt, 103, 192, 256 testimony, 209 Texas, 3, 4, 5, 9, 13, 15, 20, 28, 38, 39, 48, 53, 54, 56, 57, 60, 62, 67, 70, 72, 81, 86, 93, 95, 96, 97, 100, 103, 110, 115, 130, 153, 177, 181, 200, 202,

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

Index 203, 205, 208, 230, 273, 275, 276, 277, 282, 285, 286, 302, 321, 327, 351 thermal efficiency, 328 thinking, 193 third party, 34, 244, 246 threat, 32, 118 threatened, 217, 225 threats, 9, 124, 212 time consuming, 8, 27 time frame, 29, 183, 192, 195, 253, 298 time periods, 187, 195, 251, 287 time series, 81, 82, 340, 341 timing, 193, 329, 341 TM, 126, 163, 179 topology, 143 torque, 137, 142, 152, 154, 160 total costs, 260 total energy, 18, 180, 192, 328 tourism, 9, 18, 232 toxic, 118 Toyota, 175 TPI, 321, 324, 381 tracking, 72, 91, 110, 242 trade, 5, 144, 174, 178, 182, 199, 200, 206, 217, 242, 298, 300, 326, 329, 330, 333, 363 trade-off, 144, 174, 217, 298 trading, 32, 206, 242 training, 125, 198, 216, 307, 340, 350, 366, 370, 377 trajectory, ix, 105, 250, 306, 333 trans, 41, 49, 86, 135, 208, 260, 304 transaction costs, 87 transactions, 63, 64, 72, 78, 91, 94, 96 transfer, 148 transformations, 238 transition, 123, 144, 154, 159, 310 transparent, 31, 204, 328 transport, 6, 10, 11, 135, 152, 264, 265, 295, 374 transportation, 119, 131, 135, 141, 142, 158, 174, 199, 246 travel, 135 Treasury, 332 trees, 168, 216, 222, 343 trend, 62, 66, 70, 78, 79, 80, 82, 87, 96, 131, 159, 160, 169, 176, 178, 195, 242 tribal, 245 tribal lands, 245 tribes, 244, 245 trucks, 127 trust, 219, 246 TT, 208 tubular, 160 turbulence, 132, 137, 140, 147, 151, 154, 156, 289 turbulent, 289

405

TVA, 49, 84, 103, 241 two-way, 246

U U.S. Department of Agriculture (USDA), 38, 104, 226, 237 U.S. economy, 306, 315 U.S. Geological Survey, 104, 126, 235, 274 UK, 103, 207, 208 uncertainty, 23, 34, 49, 111, 114, 131, 182, 183, 186, 192, 199, 211, 248, 348 undergraduate, 373 uniform, 33, 45, 82, 222 unit cost, 19 United Kingdom, 153, 221 United Nations, 120 United Nations Environment Program, 120 universities, 148, 177, 242, 244, 350, 373, 377 updating, 137, 275 uranium, 6, 215, 216, 295 urban centers, 119 USDA, 38, 66, 87, 104, 226, 237, 283, 340, 368 Utah, 159, 273, 282, 301, 359

V validation, 151, 284, 333, 350, 351 validity, 344 values, 36, 81, 82, 146, 211, 223, 224, 228, 232, 235, 270, 271, 275, 285, 286, 287, 288, 293, 298, 301, 310, 312, 313, 334, 354 vapor, 328 variability, vii, 1, 5, 16, 19, 20, 28, 70, 73, 91, 96, 97, 114, 180, 182, 183, 184, 186, 187, 188, 195, 196, 198, 199, 206, 209, 250, 253, 280, 297, 298, 299, 348, 351, 354, 366 variable, 5, 6, 12, 17, 19, 20, 40, 81, 82, 96, 133, 135, 137, 138, 140, 154, 159, 160, 179, 180, 185, 192, 193, 195, 196, 198, 238, 249, 270, 288, 293, 331, 346 variable costs, 17, 19 variables, 17, 33, 74, 80, 184, 186, 287, 353 variance, 298 variation, 80, 298, 306 vehicles, 25, 127, 175, 199, 201 velocity, 8, 39 Vermont, 273, 282, 302 vessels, 157 village, 159, 244 visible, 57, 222

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,

Index

406

vision, 338, 340, 341, 343, 345, 347, 353, 355, 358, 359, 360, 362, 363, 364, 365, 367, 368, 369, 370, 372, 377 voids, 118 volatility, 6, 119 vulnerability, 124

Copyright © 2008. Nova Science Publishers, Incorporated. All rights reserved.

W wage rate, 174 wages, 81, 309 Wall Street Journal, 35, 40, 41 WAPA, 49, 58, 93, 104, 340, 369 waste disposal, 17 wastewater, 214 water, 6, 12, 118, 119, 121, 122, 123, 131, 153, 154, 156, 157, 161, 210, 214, 215, 224, 234, 237, 244, 268, 270, 271, 272, 283, 284, 288, 328, 330, 331, 338, 348 water quality, 214, 224 water resources, 6, 122, 214, 215 water supplies, 214, 215, 270 water vapor, 328 watershed, 219 weakness, 68, 355 wealth, 181, 308 wear, 142, 147 web, 35, 43, 91, 345 Weibull, 288 weight ratio, 140 Weinberg, 337, 377, 378, 382 Westinghouse, 60 wetlands, 225 wholesale, vii, viii, 1, 38, 47, 67, 71, 72, 73, 74, 90, 91, 93, 95, 96, 182, 187, 199, 202, 206, 239, 240, 243, 244, 245, 251 wilderness, 283 wildlife, 25, 39, 106, 119, 210, 211, 212, 215, 216, 219, 225, 226, 228, 229, 233, 234, 236, 237, 283, 325, 355, 357, 358, 359 wildlife conservation, 325

wind farm, viii, ix, 2, 3, 8, 18, 26, 37, 105, 131, 138, 139, 149, 150, 165, 174, 177, 218, 221, 262, 288, 295, 297, 298, 299, 303, 307, 350, 351, 354, 355, 356, 374, 375 wind gusts, 140 wind maps, 156, 284, 287, 366 wind speeds, 40, 85, 135, 159, 160, 286, 287, 331 wind tunnels, 133 wind turbines, vii, viii, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 18, 19, 20, 25, 26, 40, 49, 53, 58, 59, 61, 78, 79, 127, 128, 130, 133, 134, 135, 136, 137, 144, 145, 154, 155, 156, 157, 158, 159, 160, 161, 162, 165, 166, 167, 168, 170, 171, 172, 173, 174, 175, 178, 190, 191, 195, 196, 211, 213, 216, 217, 218, 221, 222, 227, 238, 243, 244, 248, 252, 256, 261, 286, 288, 297, 299, 303, 311, 331 windows, 157 winter, 8, 186, 215 wires, 240, 327 Wisconsin, 15, 177, 181, 218, 237, 273, 282, 285, 286, 302 withdrawal, 271 wood, 133, 168 workers, 19, 119, 240, 308, 311, 314, 315, 317 workforce, 373 working groups, 359, 370 World Resources Institute, 43, 215 worry, 219 writing, 206, 245, 319, 343 Wyoming, 28, 39, 54, 84, 98, 200, 205, 273, 282, 287, 301

Y yield, 8, 35, 96, 97, 192, 228

Z zoning, 159, 160, 224, 245

Wind Power : Technology, Economics and Policies, Nova Science Publishers, Incorporated, 2008. ProQuest Ebook Central,