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Power Grid Resiliency for Adverse Conditions Nicholas Abi-Samra

artechhouse.com

Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the U.S. Library of Congress British Library Cataloguing in Publication Data A catalog record for this book is available from the British Library.

ISBN 13: 978-1-63081-017-7 Cover design by John Gomes © 2017 Artech House 685 Canton Street Norwood, MA All rights reserved. Printed and bound in the United States of America. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher. All terms mentioned in this book that are known to be trademarks or service marks have been appropriately capitalized. Artech House cannot attest to the accuracy of this information. Use of a term in this book should not be regarded as affecting the validity of any trademark or service mark. 10 9 8 7 6 5 4 3 2 1

Introduction

This aim of this book is to provide in-depth discussions of some extreme weather phenomena that can impact the different components of the power system. The emphasis will be on those impacts that either are not covered, or not covered in depth, in other texts or the open literature. Sometimes the topics presented may not seem to be apparent; therefore, I will try to support those claims by detailed technical analysis. I have attempted to present related chapters in a logical sequence in order to keep the reader from having to flip back and forth in the book. Chapters 1 through 6 discuss the impacts of heat storms and droughts on distribution transformers, underground cables, power generation, and the performance of transmission lines under lightning conditions. The relation between the effectiveness of the overall transmission lines’ lightning protection and droughts is one of those cases that is not apparent, and has not covered in the open literature. Heat waves and droughts are different extreme weather events, and their cumulative impact is more severe when they occur together, especially on power generation. Chapter 7 discusses the impact of rain and snow on the insulation characteristics of transmission lines. Although heavy precipitation has known mechanical stresses on power lines that could lead to their failures, I decided against writing on these since they are well covered in a variety of excellent resources. Chapter 8 covers another aspect of heavy precipitation on transmission lines, which is the increase in corona losses. Typically an order of lower magnitude, corona losses are normally low in comparison to the resistance losses in transmission lines during fair weather; however, they can increase dramatically during extreme weather. Chapters 9, 10, and 11 cover the effect of high winds on power systems. Chapter 9 discusses in detail the risks of high intensity winds on transmission and distribution systems and covers firestorms that are repeatedly threatening wide areas of the western United States and Canada. Chapter 10 presents the impact of high winds on wind turbines. There have been several reported cases of wind turbine damage worldwide, although researchers have indicated that a large number of damaged turbines go unreported. There also have been reports of multiple turbines in wind farms affected by a wind storm shutting down together due to high wind conditions. Chapter 11 covers the physical hardening of power systems—mainly distribution lines—to high winds. Also covered in Chapter 11 is the subject of hardening of substations against floods and storm surges. Flooding is often considered to be one of the worst types of extreme weather events because of the long-term damage that floodwater can do to power substations and underground electrical systems. xvii

xviii

Introduction

Chapter 12 covers grid resilience. Despite all best efforts, it is impossible to avoid occasional large outages caused by extreme weather. In contrast to other threats to the power system, it is impossible to lessen the likelihood of extreme weather events. Hence resilience to extreme weather should be more focused on learning from past experiences (case histories) to better deal with future events by limiting the scope and impact of outages when they occur and rapidly restoring power and services afterward. There has been significant growth in the instrumentation and automation that can improve grid reliability and resilience in the face of outages; however, this added complexity can also introduce cybersecurity vulnerabilities. Thus, this book concludes with a discussion on the cyber and physical security of the grid in Chapter 12. I hope you find this book both informative and useful. I welcome you to email me feedback on this book including comments or errors, and invite you to share your own experiences on the topic. Additionally, please feel free to reach out if there are any situations in which you may need my assistance at [email protected].

Contents Foreword by Gerry Cauley

xiii

Foreword by Mark Lauby

xv

Introduction

xvii

CHAPTER 1 Heat Waves

1

Introduction 1 1 Effects of Heat Waves on Power Systems Effect of High Ambient and Water Temperatures on Power Generation Systems 3 Effect of High Ambient and Water Temperatures on Thermoelectric Power Generation Systems 3 Case Histories 4 5 2003 and 2006 Heat Waves: France 2006 Heat Wave: North America 8 10 Heat Wave of 2011 Heat Wave of 2012 12 13 2015 Heat Wave in Europe 2015 Heat Wave in Texas 15 Preparation for Heat Waves 16 17 Demand Response Demand Response in the United States 18 19 Conclusions References 19 20 Appendix 1A: Defining a Heat Wave CHAPTER 2 Effect of Droughts on Hydroelectric Power Plants

23

Introduction: Defining Droughts Water Use by Hydroelectric Plants Classifications of Hydroelectric Plants Conversion of Water Potential Energy into Electric Energy Sizing of the Penstock and the Hydroelectric Turbine Sizing of the Penstock Effects of Droughts on Different Hydroelectric Plant Types Impoundment-Type Hydroelectric Plants Diversion-Type Hydroelectric Plants

23 24 25 26 27 28 29 29 30 v

Contents

vi

Pumped-Storage Type Hydroelectric Plants Variability of Hydroelectric Generation in the United States Case Histories Case History: Drought Effects on Hydroelectric Generation in California Case History: Drought Effects on Lake Mead and the Hoover Dam Conclusions Exercises Exercise 2.1 Exercise 2.2 References Appendix 2A: Summaries of Recent Case Histories of the Effects of Droughts and Heat Waves on Power Plants in the United States

32 33 35 35 38 40 41 41 42 42 43

CHAPTER 3 Effect of Droughts on Thermoelectric Power Plants

47

Introduction Thermoelectric Plant Water Usage in the United States Thermoelectric Cooling Technologies Once-Through Cooling (OTC) System Recirculating Systems Dry Cooling Hybrid Cooling Industry Sponsoring Cooling System R&D Case Study: Phaseout of OTC in California Conclusions Case History: Drought of 2011 in Texas References Selected Bibliography

47 48 50 50 52 53 55 55 56 57 58 58 59

CHAPTER 4 The California Heat Wave of 2006 and the Failure of Distribution Transformers

61

Introduction Impact on the California Power System Distribution System Event Transmission and Generation Systems Behaviors During the Heat Wave Failure of Distribution Transformers During Heat Waves Rating Practices of Distribution Transformers in the United States Knowledge of Actual Loading and Failure Mechanisms of Distribution Transformers Hot Spot and Top Oil Temperatures During Heat Waves Estimating Remaining Life of Transformer Formulation of Transformer Loss of Life Based on IEEE C57.91-1995 IEEE C57.91-1995 Clause 7 Thermal Model for Transformer Aging Derivation of Hot Spot Temperature Solar Heating of the Pole-Top Distribution Transformer

61 62 62 63 64 64 64 65 67 67 69 69 72

Contents

vii

Lessons Learned Conclusions References Selected Bibliography

77 78 79 79

CHAPTER 5 Extreme Weather Effects on Directly Buried Underground Cables

81

Introduction Cable Ampacity and Thermal Conditions Factors Influencing Thermal Resistivity of the Soil Moisture Dry Density and Composition Other Factors Influencing Thermal Resistivity Variations Along the Circuit Backfill Thermal Runaway Simplified Approach for Underground Cable Derating Calculations Ambient and Conductor Temperature Adjustment Factor (Ft) Case Histories 1998 Auckland, New Zealand Cable Failures Auckland 2006 Blackout Australia Wind Farm Cable Failures Water Treeing Conclusions Exercise References Selected Bibliography

81 82 85 85 87 89 89 89 90 91 92 95 95 97 97 98 99 100 101 101

CHAPTER 6 Effect of Lack of Moisture on Line Lightning Performance

103

Introduction Brief Overview on Line-Insulation Coordination Lightning and Switching Impulse Withstands (Tower Insulation Strength) Lightning Overvoltages (Stress on the Tower Insulation) Strokes to Transmission Lines Backflashovers Backflash Rate (BFR) General Practical Transmission Lines Grounding Systems Grounding of Transmission Towers Grounding System for Transmission Lines Tower Footing Resistance (TFR) Impulse and Low-Frequency Resistances A Simplified Method for Calculating the Tower Impulse Resistance Example: Estimation of the Impulse Resistance of Tower Footing Soil Electrical Resistivity Dependence of the Soil Electrical Resistivity on Temperature

103 104 105 107 108 109 110 111 111 113 115 115 116 117 119 122

Contents

viii

Where to Find Earth Electrical Resistivity Measurements Conclusions Exercise Solution References Selected Bibliography Appendix 6A: Summary of Line-Insulation Coordination Requirements

123 123 124 124 124 125 126

CHAPTER 7 Effects of Heavy Winter Precipitation on Transmission Line Insulation

129

Effects of Rain on Insulator Dielectric Strength Effects of Rain on the Power Frequency Withstand of Insulators Effects of Rain on the Lightning and Switching Surge Withstand Effects of Snow and Ice on Insulator Dielectric Strength Mechanism of Dielectric Failures of Snow- or Ice-Covered Insulators Chronological Sequence of Flashover of Partially Covered Insulators Quantifying the Electrical Withstand Reduction of Insulators Due to Ice and Snow IEEE Standard 1783 Case Histories Japan Snow Storm of 2005 China Snow Storm of 2008 Conclusions References Selected Bibliography

129 129 131 131 132 132 134 136 137 137 139 140 141 142

CHAPTER 8 Transmission Line Corona Losses

145

Introduction Conductor and Surface Gradients Conductor and Surface Gradient: Single Conductors Conductor Surface Gradient: Bundled Conductors Corona Onset Gradient Example Calculations for the Corona Onset Gradient Relation of Surface and Corona Onset Gradients Surface Irregularity Parameter m: Influence of Rain, Ice, and Snow Occurrence of Corona Losses Corona Loss in Fair Weather Corona Losses in Foul Weather Effect of Rain on Corona Losses Effect of Snow, Ice, and Hoarfrost on Corona Losses Annual Transmission Line Corona Losses Estimating Corona Losses Peek’s Approach for Calculating Fair-Weather Corona Losses Peterson’s Approach for Calculating Fair Weather Corona Losses BPA’s Approach for Calculating Corona Losses Under Extreme Weather

145 145 146 150 153 155 156 156 157 157 158 158 159 160 161 161 161 163

Contents

ix

Voltage Considerations and Corona Losses Transmission Line Voltage Upgrades Voltage Reduction as a Means of Reducing Corona Losses Reduction of Corona Losses Case Histories Measurements of Corona Losses Under Hoarfrost: Finland Corona Losses due to Extreme Contamination Conclusions Exercise Solution References Selected Bibliography

167 167 168 169 170 170 170 171 171 171 173 173

CHAPTER 9 Effect of High Winds on the Power Delivery System

175

Introduction Defining HIWs Types of HIWs That Threaten the Power System Infrastructure Damage to Transmission and Distribution Infrastructures from Tornadoes Examples of Tornado Damage on the Power Grid Case Histories of Some Tornado Damage in the United States Failure Analysis from HIWs Wind Force on Transmission Lines’ Aerial Conductors Selected Case Histories Pacific DC Intertie 1989, United States 345-kV Line Cascade, Nebraska, 1993 Anatol, Lothar, and Martin Windstorms, Europe, December 1999 Other Case Histories Selection of Salient Lessons Learned from Several Windstorm Events Data Collection after the Storm Design Considerations Upgrading and Retrofitting Existing Transmission Structures Lessons Learned from Cascade Failures Striking a Balance between Hardening and Quick Restoration Firestorms The South African Advanced Fire Information System Case History: Fires in the San Diego Area References Selected Bibliography Appendix 9A: Common Types of Pole and Tower Structures Tangent Structures Guyed Structures Self-Supporting Structures Angle Structures Dead-End Structures Classification of Tornadoes

175 175 176 177 177 178 178 181 182 182 184 187 189 191 191 191 192 193 193 193 194 195 197 197 198 198 198 199 199 199 199

Contents

x

Tornado Alley Summary and Conclusions

200 201

CHAPTER 10 Effect of High Winds on Wind Turbines

203

Introduction The Impact of High Winds on Wind Farms: Case Histories Denmark, 2005 Taiwan, 2008 United Kingdom, 2011 and 2015 Blackout System Event in South Australia, September 28, 2016 Stresses from High Winds Cut-In and Cut-Out Speeds Exercise 10.1 Solution Exercise 10.2 Solution Wind Turbine Vulnerability to Hurricanes Hardening Wind Turbines Against High Winds High Wind Speed Shutdown Methods of Shutting Down Wind Turbines under High Wind Conditions Stopping the Wind Turbine by Pitch Regulation Stopping Wind Turbines with Stall Regulation Hybrid: Combination Pitch and Stall Control Stopping the Wind Turbine by Applying a Mechanical Brake High Wind Ride-Through Capability of Modern Wind Turbines Approaches to Running Above Higher Wind Conditions Ramp-Rate Control of the Pitch Angle Dynamic Control of the Pitch Angle Implementation by Wind Turbine Manufacturers Effect of High Winds on Fires in Wind Turbines Causes of Fires Cases Histories Conclusions References Selected Bibliography Appendix 10A: IEC 61400 IEC Classification of Wind Turbines

203 204 204 205 205 206 207 209 210 210 210 211 211 212 215 215 216 218 220 221 222 222 223 223 224 225 226 227 227 228 230 230 231

CHAPTER 11 Structural Hardening of Power Systems against Storms

233

Introduction Physical Hardening of the Distribution System against HIWs Physical Hardening of Distribution Line Poles Wind Performance of Poles Hardening of Distribution Poles

233 234 234 235 235

Contents

xi

Example Applications for NESC Rule 250C1 Differences between the NESC and the California GO 95 Undergrounding of Overhead Infrastructure Approaches to Hardening Strategies against Wind Storms Hardening against Floods and Storm Surges Substation Flooding Concerns Lessons Learned for Measures to Reduce the Impact of Flooding in Substations Lessons Learned from Post Substation Flood Actions Summary and Conclusions References Selected Bibliography

240 242 257 259 260 260 262 262 264 265 265

CHAPTER 12 Grid Resilience

267

Introduction Superstorm Sandy Utility Preparations for Superstorm Sandy Power Restoration The Inherent Resiliency of the Power Grid Defining System Resiliency Hardening Ride Through Rapid Recovery Adaptability Use of the Smart Grid to Increase System Resiliency Use of Social Media Appeal of Microgrids in System Resilience Performance of Solar PV Power during Superstorm Sandy Cyber and Physical Security Cybersecurity Physical Security Coordinated Attacks Summary and Conclusions References Selected Bibliography Appendix 12A: Expanded Information on Superstorm Sandy General Information on Sandy

267 268 269 270 271 271 272 273 274 274 274 275 276 284 288 288 291 292 292 293 294 294 294

About the Author

297

Index

299

CHAPTER 1

Heat Waves Introduction This chapter discusses the effect of heat waves on the energy value chain and presents lessons from previous events. A heat wave, also known as a heat storm, is an extreme weather phenomenon characterized as a prolonged period of higher-than-normal ambient temperatures that can last from a few days to a few weeks. Because heat waves are not as visible as other forms of severe weather, like high winds and ice, their effects have not been studied as much as other forms of extreme weather. Heat waves and droughts (prolonged periods of abnormally low rainfall), are separate extreme weather phenomena that can occur both independent and concurrently of one another. Each can impact certain assets in the power system on its own, but when they occur together, their cumulative impact is more severe, especially on the power generation side. The effects of droughts on power generation are covered in Chapters 2 and 3. Hence, this chapter, along with Chapters 2 and 3, cover some case studies that are related to both extreme weather events.

Effects of Heat Waves on Power Systems Heat waves affect several components of the power system. Figure 1.1 shows the main power system components that can be affected by heat waves. Elevated ambient temperatures have stressed existing electricity generation, transmission, and distribution infrastructures due to the stretching of electricity

Figure 1.1

Overview of the possible footprints of heat waves on power systems.

1

2

Heat Waves

systems’ capacity, the stressing, and even failure, of power equipment, and even widespread outages. Such power outages vary according to the duration of the failure from momentary, lasting only a few seconds, or sustained, varying from a few minutes to several days. Typically, during the second day of a heat wave, electricity demand abnormally increases during the peak summertime hours of 4:00–7:00 p.m. when large numbers of air conditioners are switched on. If a heat spell extends to three days or more, nighttime temperatures do not cool down, and the thermal mass in homes and buildings retains the heat from previous days causing air conditioners to turn on earlier and to stay on later in the day, putting more demand on and challenging electricity supplies for longer periods of time. On the power delivery system, elevated ambient temperatures and heat waves increase the summer peaks while simultaneously stressing the power delivery systems and equipment. Transmission and distribution line conductors are not as efficient at high ambient temperatures as their resistance is temperature-dependent. For every 1°C (1.8°F) rise in ambient temperature above 20°C (68°F), the resistance of copper conductors increases by about 0.38%, as the resistance increases, so does the heat loss in the conductor, which varies by the square of the resistance. The conductors of transmission lines commonly sag during hot summer days, when the demand for power rises. Transmission line conductors sagging into trees in their right-of-way have been a large factor in several large-scale blackouts, such as the August 14, 2003, northeast blackout. Investigations of that blackout, in which I participated, showed that the event was initiated by three 345-kV transmission lines supplying the Cleveland-Akron area in Ohio. The lines tripped and locked out, because they sagged and contacted overgrown trees within their rights of way. The loss of two more key 345-kV lines in northern Ohio, also due to sagging and tree contacts, shifted power flows onto a network of 138-kV lines that became heavily overloaded, and consequently, voltages began to degrade in the Akron area. Several of these 138-kV lines subsequently sagged into vegetation, distribution wires, and other underlying objects, and 16 of them tripped sequentially over a period of 30 minutes. The capacity of power transformers also declines with increased ambient temperatures due to heat waves. Figure 1.2 illustrates the effect of ambient temperature on the permissible loading of self-cooled transformers designed to operate continuously up to a 55°C rise (or 65°C) rise above ambient temperature with commercially available insulation systems. [2]. As shown in Figure 1.2, the loading of transformers has to be decreased with increasing temperatures because of thermal limits. If power components are not derated (load-reduced) to allow for more restrictive thermal limits, they may age faster or even suffer catastrophic failure. Problems have occurred with distribution transformers during heat waves. Chapter 4 covers distribution transformer failures in heat waves. On the generation side, elevated levels of ambient and air and water temperatures reduce the thermal efficiencies of thermoelectric power plants, which can result in reduced power capacity, and output; increased fuel consumption and costs to the utility and consumer; and hindered system flexibility. On the operational side, while the power system can become stressed during heat waves, utilities have learned successfully how to deal with such events. Of course, when the power system is highly stressed, the probability of operator error

Effect of High Ambient and Water Temperatures on Thermoelectric Power Generation Systems

3

Figure 1.2 Permissible load in percent of rated load at 30°C. (Data from: [2].)

increases resulting in significant outage risks. Also, the sometimes large geographical footprints of waves could place limits on the flow of electricity supply during peak demand periods between regions and neighboring utilities, as they may be experiencing the same heat waves. Heat waves have also led to high real-time power prices. Day-ahead prices for certain peak hours hit several folds in typical prices in certain regions during the 2006 and 2013 heat waves in the United States.

Effect of High Ambient and Water Temperatures on Power Generation Systems Natural gas plants, coal plants, nuclear plants, concentrated solar plants, and geothermal power plants are all affected by elevated air temperatures. Even photovoltaic (PV) systems are effected by heat waves, as the cell performance drops by 0.4%–0.5% for every 1°C (1.8F°C) rise in temperature [3]. The following section concentrates on the effect of heat waves on thermoelectric power plants.

Effect of High Ambient and Water Temperatures on Thermoelectric Power Generation Systems Increases in ambient air and water temperatures reduce the thermal efficiencies of power plants, especially the thermoelectric types. Lower thermal efficiencies in thermoelectric plants can lead to reduced capacity, increased fuel consumption,

4

Heat Waves

higher costs, and system flexibility, which has become very important today. All thermoelectric plants (e.g., coal, nuclear, and natural gas) are affected by elevated cooling water temperatures. For thermoelectric power plants, elevated ambient air and cooling water temperatures increase steam condensation temperatures and turbine backpressure, reducing power generation efficiency. Recall that in thermoelectric plants, high pressure is expanded over a turbine to produce electricity and convert it to a liquid following the turbine, from which arises the demand for cooling water. For this to happen, a vacuum is created in the condensation process that draws the steam over the turbine. Increasing the steam condensate temperatures, because of elevated temperatures in heat waves, increases the backpressure, and thus reduces the thermodynamic efficiency of the process. In other words, the smaller the temperature difference between the internal heat source and the external environment where the surplus heat is dumped, the less efficient is the process. Typically, thermoelectric plants’ net output is higher in winter than in summer due to differences in cooling water and air temperatures. The impact from increasing air and water temperatures on specific power plants is a function of the plant type and site-specific factors. For example, for each increase of 1°C (1.8°F) in air temperature, the power output of natural gas-fired combustion turbine is estimated to decrease by approximately 0.6%–0.7% [4]. The power output of a combined cycle power plant decreases by 0.3%–0.5% [5]. Nuclear plants are also affected by air temperature and the decrease in output power averages 0.5% [6]. As combined cycle plants with dry cooling are more sensitive to warmer air temperatures, the reduction in plant output is approximately 0.7%. Elevated water temperatures put power plants at risk of exceeding thermal discharge limit regulations in rivers and lakes established to protect aquatic ecosystems. These could lead to forced curtailments at once-through cooling power plants. Any thermoelectric plant that is normally cooled by drawing water from a river or lake will have limits imposed on the temperature of the returned water, typically around 30°C (86°F) and/or on the temperature differential between inlet and discharge. In a heat wave, even the inlet water may approach the limit set for discharge, and this will mean that the plant is unable to run at full power. Examples to this are shown in Chapter 3. In summary, the combination of heat waves and droughts translates into less, and warmer, water available for thermal plant cooling systems, leading to output curtailments or even shutdowns.

Case Histories The decade spanning 2001 to 2010 was characterized as the warmest decade since the beginning of meteorological records by many sources. Many countries suffered one or more heat waves during that period, inflicting infrastructure failures and economic losses. During these events, power system systems failed to deliver electricity on demand, resulting in many rolling or unintentional blackouts. The six-year period between 2011 and 2016 had several record-breaking heat waves, making it the warmest six-year period on record, according to the World

Case Histories

5

Meterological Organization (WMO). In January 2016, the WMO reported that 2015 was the warmest year on record. WMO also reported that “15 of the 16 hottest years on record have all been this century, with 2015 being significantly warmer than the record-level temperatures seen in 2014” [7]. Independent analyses from the National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA) showed that 2016 was the warmest year on record globally. According to NASA, the Earth’s 2016 surface temperatures were the warmest since modern record-keeping began in 1880. In 2015, all-time high-temperature records in Europe were shattered with two heat waves. The first heat wave stretched over several western European countries in early July, while the second major heat wave afflicted central and eastern Europe. In the United States, numerous daily record highs were recorded across the nation. The lessons learned from these events and the resulting adaption measures include a combination of legislative/regulatory and energy-specific measures.

2003 and 2006 Heat Waves: France

France was severely affected by the heat waves of 2003 and 2006, two of the worst heat waves in the country’s history. In addition to their severe social impact, these two heat waves required extensive operational changes to avoid blackouts and maintain a power supply from nuclear power plants.

2003 Heat Wave: France

Europe witnessed a severe heat wave in 2003. Record high temperatures resulted in at least 30,000 deaths, about half in France alone. The heat wave raised concerns over global warming. France recorded some of its highest temperatures in over 50 years, in both intensity and duration. The ambient temperatures were 20%–30% higher than average mean temperatures for the corresponding periods. The high temperatures came on top of a drought in preceding months. The combination of the heat wave and drought highlighted the impact of such events on energy security and, in particular, on the susceptibility of the nuclear power sector to heat waves and droughts. France has 58 nuclear reactors in 19 power plants operated by Électricité de France (EdF) with a power capacity of 63.2 GWe, supplying about 77% of the total electric generated in France, according to Réseau de Transport d’Électricité (RTE), the French transmission system operator power in the country. Thirty-seven reactors are situated near rivers and use these rivers for water for their cooling systems. Five plants, with 18 reactors are located on the coast and receive their cooling water directly from the ocean. French nuclear plants employ cooling towers to reduce their impact on rivers. In 2003, French nuclear power plants witnessed the amalgamation of high air temperature, high cooling water temperature, and low cooling water level. These three hazards occurred concurrently in some plants. EdF attempted to comply with regulations on thermal discharge temperatures, and thus, 14 of the 19 French nuclear plants, located next to inland water bodies, had either to curtail power, or shut down, which resulted in a decrease of around 4,000 MW in corresponding

6

Heat Waves

electricity-generating capacity. EdF encountered problems in ensuring the continued operation of electrical power transmission and auxiliary systems (such as compressed air and demineralized water systems). To avoid blackouts, the Autorité de Sûreté Nucléaire (ASN), the nuclear safety authority in France, exempted five power plants from thermal discharge limits and allowed discharge temperatures of up to 30°C (86°F), compared to the standard limit of 24°C (75.2°F). The French government decreed that the priority of the power generated from the French plants was for national consumption needs, yet they did not exempt them from the need to comply with international agreements for energy sales. The experience of the summer of 2003 revealed that certain baseline design values for the nuclear reactors could be reached, or even exceeded. Values of particular concern were the following: • • • •

Cooling water temperature; Level of water taken from rivers; Temperature of the air taken from outside; Temperature within the different parts of the plant.

The design of the cooling water was exceeded on certain sites. The limit can be avoided by load-shedding on certain power-consuming equipment not required for safety purposes. The main consequence of the high air temperature is a temperature increase in rooms containing safety-related equipment and, in particular, in the reactor building. In order to remedy that situation, operators resorted to the use of portable fans, air conditioners, and 50-kW, high-power cooling chillers. Due to the 2003 heat wave and drought, in total more than 30 nuclear power plant units in Europe were forced to shut down or reduce their power. Lessons Learned

EdF avoided blackouts in France by exercising several options including the following: • • • •

Purchasing energy on the wholesale power market (2,800 MW); Implementing end-use conservation (300 MW); Negotiating lower loads from industry consumers (1,700 MW); Reducing exportation to Italy. EdF’s contract with Italy was the only contract with a clause allowing interruption in the event of an emergency, and EdF was able to cut power exports by more than 50%.

In 2004, the ASN recommended actions for mitigating the magnitude of future heat waves. These included optimized cooling water monitoring, alert systems, as well as plant interior ventilation (and air conditioning). In addition, EdF installed weather warning systems with site-specific warning levels (as a function of the site-specific technical characteristics, organizational structures, and applicable regulations). This weather warning system could anticipate problems relating to heat waves and droughts based on continuous measurements of the climatic conditions observed at the specific plants. EdF also took actions to identify which plants

Case Histories

7

operated in low safety margins with respect to increased air and water temperatures. Forward-looking studies were designed to trigger appropriate actions at four predefined warning levels. Each warning level is associated with a local organizational structure and is implemented when predefined limits are met based on plant specific characteristics and applicable regulations. EdF devised and implemented a list of temporary measures for exceptional heat and low water conditions. These included measures to bring the reactor units to a safe shutdown state if certain climatic conditions persist. Other measures work to ensure that equipment such as ventilation systems, chillers, and heat exchangers is in good working condition before the summer heat. Finally, the 2003 events showed that suitable water-use agreements should be in place between the various waterway users, including power plants and the dams. Such agreements cover issues such as the following: • • • • • • •

Environmental impact; Water quality and temperature; Social impact and public health protection; Engineering feasibility; Economic and financial feasibility; Supplemental and backup water supplies; Alternatives such as the use of treated wastewater and on-site conversions at water use sites.

2006 Heat Wave: France

Another heat wave affected France in 2006; the temperatures observed were lower than those of the August 2003 heat wave, although July 2006 was the warmest month of July since 1950. The 2006 heat wave stressed the cooling systems of nuclear plants and therefore their ability to sustain their output power levels. In response, the French government published an order allowing EdF to raise river water temperatures downstream to preserve the stability of the grid and maintain power supply. That order referred only to the acceptable temperature change between the water intake and discharge, without being specific about the absolute temperatures. The French government allowed a change in temperature of 3°C (5.4°F) for those plants without cooling towers and of 0.5°C–1.5°C (0.9°C–2.7°F) plants with cooling towers. To avoid blackouts, EdF imported power during peak hours from its neighbors. Other adaption measures included end-use conservation, the purchase of 2,000 MW for an unspecified amount of time on the wholesale market, and interruption of international supply contracts that allowed for emergency measures. Lessons Learned In 2006, the French government adopted its first national adaptation strategy with a set of actions and measures. One of the cornerstones of this plan develops actions to promote energy efficiency. Accordingly, since 2006, the French government has initiated energy saving certificates (ESCs), a scheme that imposes requirements on energy suppliers for energy efficiency and the promotion of renewable energy sources.

8

Heat Waves

The 2006 heat wave also affected other European countries. In Germany, 13 coal-fired and seven nuclear power plants had to reduce their production in the last two weeks of July 2006. On average, the concurrent reductions in power amounted to about 2,000 MW, but a maximum of about 2,830 MW was simultaneously unavailable [8]. 2006 Heat Wave: North America

In 2006, a heat wave spread throughout most of the United States and Canada beginning in mid July. This heat wave was accompanied by a severe drought. The 2006 heat wave was so severe that it caused hundreds of fatalities. On July 15, 2006, the temperature reached 47°C (117°F) in Pierre, South Dakota, with many places in South Dakota reaching temperatures well into the 120s. The heat wave went through several distinct periods [9], described as follows: •



• •

From July 15 to July 22, very high temperatures spread across most of the United States and Canada. On July 17, every state except Alaska, Minnesota, and North Dakota recorded temperatures of 32°C (90°F) or greater. From July 23 to July 29, the abnormal heat was concentrated on the west coast and in southwest deserts. From July 29 to August 4, the heat wave moved eastward. From August 4 to August 27, high temperatures persisted in the south and southeast United States.

This period of heat also saw a wind storm (derecho) in St. Louis that caused widespread power outages. Impact of the 2006 Heat Wave in California

In California, which had the most severe heat-related death toll in the nation, principally in the interior region, the heat wave led to hundreds of distribution transformer failures and consequently to power outages affecting over two million electric utility customers. Chapter 4 details the impact of this heat wave on the distribution system and the resulting failure of distribution transformers. As a response to the widespread outages in California in 2006, demand response(DR) programs had an important role in the California Public Utility Commission (CPUC). We discuss DR at the end of this chapter. The CPUC authorized $262 million for DR programs for the years 2006, 2007, and 2008. Those programs included the continuation of several emergency and reliability programs, which are triggered in extreme heat wave emergencies. They also funded several new price-responsive programs, which are triggered to reduce loads in response to very high prices and temperatures that could eventually cause emergencies. In the aftermath of the 2006 heat wave, the CPUC further augmented DR programs to include programs such as autoDR, permanent load shifting (PLS), and long-term DR contracts using third-party aggregators [10]. During the 2006 heat wave, the California Independent System Operator (CAISO) reached a stage 2 emergency (which happens when operating reserves are

Case Histories

9

below or are expected to fall below 5%), allowing it to call upon interruptible customers to curtail use. The combined effect of interruptible and curtailable loads, conservation, and other utility load-reduction programs was a 4.1% reduction, more than 2,000 MW, at the peak day and hour. No involuntary load-shedding was put in play. Impact of the 2006 Heat Wave on Power Markets

Due to the heat waves across the United States, peak electrical demands in summer 2006 were much higher at all the independent system operators (ISOs) in the United States. CAISO, PJM, and the Midwest ISO (MISO) saw substantial growth in peak demand. All exceeded their historic peak demand; see Figure 1.3. The bulk U.S. power grid and wholesale power markets performed well under the stress due to unprecedented generation availability and DR employed. However, in almost every area, system operators still needed emergency actions such as warnings, appeals to the public for conservation, emergency transactions, and curtailment of interruptible large loads. There were no instances of involuntary load-shedding (blackouts) [11]. During the heat wave, prices varied by region and rose to reflect the use of more expensive generators. As an example, day-ahead prices for certain peak hours hit $350 per MWh on Long Island and were above $200 and 300 per MWh in New

Figure 1.3 Peak hourly load at all the U.S. ISOs. Peak electrical demands in the summer of 2006 at all the independent system operators exceeded historic peak due to an increase in cooling load during the heat waves of that year. (Derived from press releases and websites of the ISOs.)

10

Heat Waves

England and New York City, respectively, compared with typical prices for these areas of around $30–60 per MWh [12]. In the west, the 11-day heat wave broke demand records not only during peak hours but during evenings and weekends, stressing the distribution system and leading to distribution transformer failures, as explained in Chapter 4. Impact of the 2006 Heat in Canada

Parts of Saskatchewan, Manitoba, Ontario, and Quebec in Canada were affected by the heat wave and the drought of 2006. In mid July, Lytton, British Columbia, recorded a temperature of 42.1°C (107.8°F) and three straight days topping 41°C (105°F). Winnipeg, Manitoba, had the driest July on record and the highest average maximum temperature of any July [13]. As in the United States, nighttime minimum temperatures were also high and broke previous records. The July heat wave led to record power consumption in Ontario of 27,000 MW. Powerful thunderstorms and tornadoes affected parts of Ontario and Quebec in July and August, leading to over 625,000 residents losing power and thousands of fallen trees.

Heat Wave of 2011

The summer of 2011 saw a number of high temperatures across certain parts of the United States and Canada, from June through September. As of August 10, Dallas/ Fort Worth had recorded 40 consecutive days with high temperatures exceeding 38°C (100°F), the second-longest streak on record. (The record of 42 days was set during the 1980 United States heat wave.) In addition, the area set a new all-time hottest minimum temperature of 30°C (86°F) on July 26 and tied it twice in August. By September 13, Dallas had a total of 71 nonconsecutive days with temperatures exceeding 38°C (100°F), beating the record of 69 days set in 1980. [14] The high temperatures in August led to all-time peak load records in the Electric Reliability Council of Texas (ERCOT); see Figure 1.4. Before August 2011, ERCOT’s load record was 65,776 MW (recorded in 2010). In 2011, peak load exceeded that level in 15 days and set a new all-time peak demand record on three consecutive days (August 1–3, 2011), concluding in a new all-time peak of 68,294 MW. ERCOT likely averted another all-time peak demand record on the following day by shedding 1,500 MW of interruptible load. The prolonged August heat wave in Texas produced two periods of very high wholesale prices in ERCOT, the wholesale market operator for most of the state. Day-ahead, on-peak wholesale power prices for August 2011 rose far above the range of prices seen during the previous five Augusts; see Figure 1.5. On five days in August 2011, real-time prices hit the market cap of $3,000/MWh, and approached it on several other days. Demand Response Usage

The Texas 10-minute reserves programs for DR resources were used in the heat wave of 2011 and demonstrated reliable performance on August 4, 2011; see Figure 1.6.

Case Histories

11

Figure 1.4 ERCOT peak demand in August of 2011, where the high temperatures in August led to all-time peak load records. [Data from: U.S. Energy Information Administration (EIA).]

Figure 1.5 ERCOT August day-ahead on-peak price, north zone, August 2011. (On-peak refers to the 16-hour time block from 7:00 a.m. to 10:00 p.m., CDT on weekdays.) (Data from: EIA.)

12

Heat Waves

Figure 1.6 Demand response deployment of emergency reserves in Texas on August 4, 2011. (Data from: ERCOT.)

Heat Wave of 2012

In 2012, high water temperatures and reduced access to water caused by the drought across the United States forced a number of thermoelectric power plants to cut down production or acquire waivers to operate with cooling water above regulated temperatures. Many nuclear plants struggled with cooling water sources that approached being too warm to generate power at full levels. On August 2, 2012, unit 2 of the Millstone Power nuclear power plant in Connecticut was forced to shut down when temperatures in Long Island Sound (the source of its cooling water) reached the highest sustained levels since the facility began monitoring temperatures in 1971 [15]. Unit 3 at of the same plant (which pulls water from deeper and cooler waters in the sound) continued to operate. The Braidwood Generating nuclear power plant in Illinois received permission from the U.S. Nuclear Regulatory Commission (NRC) to continue operating after temperatures in its cooling pond rose beyond the plant’s permit limit of 37.7°C (100°F). A second power plant in the state was forced to request a variance from the U.S. Environmental Protection Agency (EPA) to pump additional water into its cooling pond in danger of heating to levels beyond those allowed by its permit. Other examples of affected power plants include the following: •

Coal-fired power plants: Powerton (coal and natural gas-fired) plant (Illinois); – Gallatin and Cumberland coal-fired plants (Tennessee). Nuclear power stations: – Vermont Yankee Nuclear Station (Vermont); – Millstone Nuclear Station (Connecticut). –



Case Histories

13

Table 1.1 Sample of High Temperature Records Set in 2015 in Europe Country

Record

France

Paris soared to 39.72°C (103.5°F) on July 1, marking the second-hottest temperature Paris has seen on any day since 1873.

Germany

A new all-time high temperature for any location or date in Germany of 42.3°C (104.5°F) was set on July 5 in the city of Kitzingen. This breaks Germany’s previous record of 42.2°C (104.4°F) set first in 1983 and tied twice in 2003

Poland

Wroclaw, the largest city in western part of Poland, set an all-time high temperature on August 8, reaching 38.9°C (102°F). The average high in earlymid August in Wroclaw was 23°C (74°F).

Spain

Madrid recorded the hottest June temperature ever of 40°C (104°F) on June 30.

Switzerland

Geneva recorded 39.7°C (103.5°F) on July 7, its highest temperature ever recorded, and the second highest temperature ever recorded in the country during any month.

2015 Heat Wave in Europe

The 2015 summer in Europe was one of the hottest on record. All-time hightemperature records were broken in many central and eastern European countries. Table 1.1 lists examples of the new recoded highs. The 2015 heat waves forced coal and nuclear plants (which use surface water for fuel processing, cooling, and emission control) to cut down production in some central and eastern European countries. The extent to which European system operators coped with the heat depended on many factors, such as the following: • • • •

The mix of power generation and the availability of solar energy; The ability to balance energy demand with energy supply; The existence and capacity of cross-border interconnections; The robustness of the transmission infrastructure.

The heat wave led to significant power outages in France, mainly due to power transformer failures. Up to 800,000 people lost power. Otherwise, nuclear stations in the country ran at a slightly lower level at times as temperatures approached 28°C (82°F). Germany experienced similar transformer failures, but no deficit in power resulted due to the abundant generation from the distributed solar PV arrays, albeit with slightly reduced efficiencies. The output of the PV arrays can be negatively impacted during heat waves as their efficiency can drop by up to 0.5% per degree Celsius of panel temperature counts. Another phenomenon that was also thought to decrease the output of the PV panels was attributed to the haze that accompanied the high-temperature days. Yet, the output of the PV panels was adequate to compensate for any derating of the thermal power plants. 2015 Heat Wave—Poland

The increase in demand due to the heat wave of 2015 stressed the Polish grid— exacerbated by the outage of its largest power plant, low operating reserves, and the absence of meaningful support from neighboring countries.

14

Heat Waves

The heat wave contributed to an increase in energy demand and a loss of load diversity, as a large number of air conditioners were operated at the same time. Adding to this increase was an unintended consequence of the existing rate structure and tariffs. The existing multitiered tariffs for households offered reduced rates between the hours of 1–3 p.m., which overlapped with the peak consumption created by the many air conditioners used during the heat wave. The power system load increased to 22 GW, and although this was less than the typical annual peak load, which occurs in wintertime (25–26 GW), it was more difficult to meet this peak demand due to lower power resources available in the summer. During the summer, the combined heat and power plants, a considerable source of power generation during the winter, are either shut down or operated at minimum load to provide domestic hot water. In addition, approximately 30% of such heat and power units were offline for maintenance and upgrades during the summer. During the second week of August, a failure occurred at the largest Polish power plant in central Poland, Belchatów, with a capacity of 858 MW, resulting in its disconnection from the power system. This occurred when some conventional power plants had to be shut down or forced to operate at a reduced load due to cooling problems caused by low intake water levels (either in rivers and lakes) and/or by high water temperatures. Belchatów came back on-line on August 13th. The operating reserve (which stood at about 200 MW) was not adequate to correct the lack of capacity available to the system. Complicating the situation even further was the fact that Poland has one of the more isolated power systems in the European Union (EU) and, as a result, could cover only 2% of its energy demand with imports at the time. The Czech Republic could not help due to the tripping of its nuclear power station in Temelin, and the Ukraine had no power surplus it could share with Poland. In the meantime, Poland had fully used the 600 MW of available import capacity from Scandinavia along the interconnector with Sweden. Furthermore, even though Germany had an energy surplus at the time (owing to the 24 GW in installed PV capacity), it could not assist due to limited cross-border connections with Poland and loop flow issues [16]. As a result of the situation created by the heat wave, Polish grid operator Polskie Sieci Elektroenergetyczne (PSE) imposed several levels of limitations of power supply for industrial consumers (with contracted capacity above 300 kW) during August. Lessons Learned

Diversifying of power generation. During heat waves, the risk to the power system is reduced when the generation profile is diversified away from the reliance only on thermal generation with heavy dependence on water for cooling. The addition of renewable energy sources, such as solar and wind, are more immune to heat waves, as was proven in the Germany and Texas heat waves of 2015. Improved usage of cross-border interconnections. Poland was unable to import enough energy from abroad to counterbalance the reduced supply from its own resources due to the heat and lack of surplus power available, or, when such surplus

Case Histories

15

was available, such as in Germany, the lack of coordination surrounding uncontrolled loop flows. Loop flows occur when the internal grid infrastructure to a country is not adequate to handle new production, and the power is diverted through neighboring countries’ grids and then back into a different part of the producing country. Such loop flows have become more common since Germany developed large amounts of wind power in its northern states along the North Sea but had limited transmission capacity to carry the generated power to industrial states. Instead the power flows through the grids of Germany’s neighbors (for example, the Czech Republic and Poland) and then back into southern Germany. Concerned about the stability of its own grid, Poland is currently planning on installing phase shifters. To the west, the Netherlands, Belgium, and France have also installed phase shifters to deal with the flows. DR. Controlled load reduction, through DR, is an effective measure that was underutilized in Poland. It is possible that DR can reduce anywhere between 4–10% of the peak energy demand in a controlled manner during heat waves. During the United States heat wave of 2006, many utilities invoked emergency DR programs, interruptible programs, and direct load control to manage their portfolios and maintain local or balancing area reliability. More operating reserves. The heat wave was forecast in advance, so PSE should have taken steps to have more operating reserves and to coordinate with neighboring system operators to improve cross-border exchanges. 2015 Heat Wave in Texas

In the last week of July and the first week of August 2015, as temperatures hovered above 40°C (above 100°F) in Texas, ERCOT set consecutive records for hourly electric demand. On Monday, August 10, 2015, temperatures hit 41.1°C (106°F) in Dallas/Fort Worth, and the grid set another all-time record of 69,783 MW. In 2015, there had only been one conservation alert, on July 30, just as the heat wave was getting started. In contrast, during an extended heat wave in 2011, conservation alerts became a matter of routine. In 2011, in fact, the power reserves were so tight that industrial operations were forced to cut back to avoid initiating rolling blackouts across the grid. In 2015, the excess power came from wind and gas turbines. Wind turbines have been going up fast in west Texas and the Texas Panhandle; at the same time, some new large natural gas plants have come on-line. According to ERCOT, the amount of generation on the grid has increased by 6% since 2011. In addition, in 2014, ERCOT introduced a new pricing system for when power reserves start to get tight, theoretically giving power plants greater economic incentive to come on-line faster, therefore giving the system even a better chance to ride through heat waves. Recent all-time highs for ERCOT (or previous all-time peak records) obtained from its website are listed as follows:

16

Heat Waves • • • • •

69,783 MW: August 10, 2015; 68,912 MW: August 6, 2015; 68,459 MW: August 5, 2015; 68,305 MW: August 3, 2011; 67,929 MW: August 2, 2011.

Preparation for Heat Waves Electric load level has a strong correlation to weather, particularly ambient temperature. In the summer, when ambient temperature is substantially above comfortable levels, electric load increases due to the high use of electricity for air conditioners. Typically, summer-peaking utilities prepare for heat waves as part of their preparing for peak summer loads. Such preparations are completed before the summer season. The preparations typically start with load forecasts, which drive a number of other activities. Annual summer load forecasts are completed by the planning groups of the utilities or the ISOs. It is important that these forecasts are weathernormalized. Weather normalization removes the effects of randomness of weather from historical trends in peak load and energy usage to reveal actual trends due to customer usage patterns and economic changes. It is also used to standardize historical and forecast peak and energy values on standard weather conditions. A number of utilities use temperatures only in the forecasts. Some use a combination of temperature, humidity, and economic factors, while others use cooling degree hours between 1:00 p.m. and 5:00 p.m. Most utilities use design weather conditions with return periods of 10 or 15 years. Peak loads exceeding such conditions are treated as contingencies, just like system contingencies. The principle is that all methods build a probability distribution of the load based on some statistical method (such as extreme value distributions, Monte Carlo methods,1 or the central tendency theorem 2) applied to historical peak day temperatures and the weather variable(s). Weather-correcting load response after each heat wave is recommended as it makes future forecasts more accurate. Forecasts, supplemented with circuit and substation peak loads from the previous summer, field inspections, and any new data not part of the forecasts, are followed by load-flow studies to determine locations with projected overloads. Potential thermal overloads, over-dutied equipment, and low voltages are identified through studies or field inspections (using thermovision cameras). New data that may not be included in the forecasts cover new load additions, load transfers, upgrades, or problem areas.

1

Monte Carlo methods (or Monte Carlo experiments) are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. Their essential idea is using randomness to solve problems that might be deterministic in principle. 2 The central limit theorem (CLT) establishes that, for the most commonly studied scenarios, when independent random variables are added, their sum tends toward a normal distribution (Gaussian distribution). The theorem is a key concept in probability theory because it implies that probabilistic and statistical methods that work for normal distributions can be applicable to many problems involving other types of distributions.

Demand Response

17

From there, substation and feeder load relief projects and contingency-switching plans are identified to address load imbalance and capacity concerns and to resolve overloads. Solutions to these potential problems can be a combination of operational measures, capital projects, and DR. Traditional solutions to loading problems include: load transfers, load balance, addition of capacitors or voltage regulators, reconductoring feeders, substation transformer increases, and new substations. Before reinforcements are put into place, investment appraisals are typically performed to ensure that the reinforcement is still required (i.e., that the network is in breach of the planning criteria) and to decide on the optimum method of addressing this breach.

Demand Response Since the heat wave of 2006, DR has gained ground as a strong alternative to the traditional generation solutions. According to the Federal Energy Regulatory Commission, DR is defined as: “Changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time, or to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when system reliability is jeopardized.” DR includes all intentional changes to consumption usage, timing, and patterns of electricity by electric utility customers in response to signals initiated by the electric utility or its proxies. DR programs reward participating customers who agree to curtail their power when called upon during periods of peak demand. DR programs include a wide range of actions that can be taken at the customer side of the meter in response to particular system conditions, such as peak demand, system congestion, system emergencies, heat waves, or high prices. DR is typically a more cost-effective alternative to adding central generation and transmission capabilities to meet the few hours of peak demand and or occasional demand spikes. Electrical generation and transmission systems are generally sized to correspond to peak demand or congestion. Hence, lowering peak demand reduces overall plant and capital cost requirements. Under conditions of tight electricity supply, such as heat waves, DR can significantly decrease the peak price and, in general, electricity price volatility. DR is similar to dynamic passive demand mechanisms to manage customer consumption of electricity in response to supply conditions, such as voltage reduction. The difference between the two is that DR mechanisms respond to explicit requests to shut off, whereas dynamic demand devices passively reduce load or even shut off when stress in response to system conditions. DR can involve both curtailing power used or by starting on-site generation. DR is a component of smart energy demand that also includes energy efficiency, home and building energy management, and electric vehicle charging. Current DR schemes are implemented with large and small commercial and residential customers, often through the use of dedicated energy-management

18

Heat Waves

control systems to shed loads in response to a signal. Services, such as lights and air conditioning, can be reduced according to a preplanned load-prioritization scheme. Depending on the configuration of generation capacity, however, DR may also be used to increase demand (load) at times of abundance production (such as high solar PV generation) and low demand. Some systems may thereby encourage energy storage to arbitrage between periods of low and high demand (or low and high prices). While initially developed to help support electric system reliability during peak load hours, DR resources currently provide an array of additional services that help support electric system reliability. Therefore, we can divide DR into three types: emergency DR, economic DR, and ancillary services DR. Emergency DR is employed in case of system emergencies. Deploying DR in these cases avoids involuntary load shedding and service interruptions during times of supply scarcity. Economic DR is employed to allow electricity customers to curtail their consumption to avoid the high price of electricity when that curtailment does not drastically inconvenience them or is worth less to them than paying the higher prices. Ancillary services DR consists of a number of specialty services that are needed to ensure the secure operation of the transmission grid and that have traditionally been provided by generators. These include spinning and nonspinning reserves, regulation, and load-following services. Smart grid emerging technologies allow customers to shift from an event-based DR to a more 24/7-based DR. Smart grid applications increase the opportunities for DR by providing real-time data to power producers and consumers. Although this granular approach increases the opportunities for DR, some customers may still be reluctant to relinquish total control of their loads to utility companies. Nevertheless, economic and environmental incentives remain the driving force behind DR. Demand Response in the United States

Although DR plays an increasingly important role in different regions of the United States, there is still great variability in how and to what extent the resource is dispatched. The variation is due in large part to the limited role to which DR is relegated in the capacity markets and sometimes the maximum number of times it is called upon and for how long. In previous heat waves, some system operators did not want to call on DR too much too soon—and thereby, risk being left without it in the case of hot days at the end of summer. In addition, legal battles in the United States over DR since 2011 have hindered the ability to use it to full capacity. In 2011, the Federal Energy Regulatory Commission (FERC) FERC, which is responsible for regulating wholesale electricity markets, issued Order 745. Order 745 regulates how DR should be compensated in wholesale electricity markets. The stated objective of this order is to “ensure that when a DR resource participating in an organized wholesale energy market administered by a regional transmission organization (RTO) or ISO has the capability to balance supply and demand as an alternative to a generation resource and when dispatch of that DR resource is cost-effective as determined by the net benefits test described in this rule, that DR resource must be compensated for the service it provides to the energy market at the market price for

References

19

energy, referred to as the locational marginal price (LMP)” [17]. With this order, FERC aimed to remove barriers to the participation of DR resources. In 2014, a District of Columbia Circuit Court of Appeals disagreed with FERC Order 745 and essentially vacated it, stating that “FERC’s new rule goes too far, encroaching on the states’ exclusive jurisdiction to regulate the retail market.” FERC appealed to the Supreme Court of the United States, and on January 25, 2016, upheld FERC’s authority to regulate DR programs in wholesale markets. Now that legal battles have been settled, DR use will probably see an expanded role in reliability and peak-shaving for heat waves; however, for DR to enter more markets, there will have to be far more automation. Other smart grid tools that can ease the stress during high demand and help mitigate supply and demand include volt/VAR optimization and distribution automation.

Conclusions When heat waves affect large areas, it is not always possible to depend solely on relief from restructured energy markets (which place limits on the flow of electricity supply during peak demand periods), limited tie lines numbers or capacities, and help from neighboring systems. Elevated ambient temperatures have stressed existing electricity generation, transmission, and distribution infrastructures. Typically, during the second day of a heat wave, the electricity demand abnormally increases during the peak summertime hours of 4:00–7:00 p.m. when large numbers of air conditioners are switched on. If a heat wave spell extends to three days or more, nighttime temperatures do not cool down, and the thermal mass in homes and buildings retains the heat from previous days, causing air conditioners to turn on earlier and to stay on later in the day, putting more demand on and challenging electricity supplies for longer periods of time. On the power delivery system, elevated ambient temperatures and heat waves increase the summer peaks, and at the same time, lead to stress that causes accelerated aging or even immediate failure of power delivery system components, such as transformers and underground cables. On the generation side, elevated levels of ambient and air and water temperatures reduce the thermal efficiencies of thermoelectric power plants, which can result in reduced power capacity and output, increased fuel consumption and cost to the utility and consumer, and hindered system flexibility. Natural gas, coal, nuclear, concentrated solar, and geothermal power plants are all affected by elevated air temperatures. They have also led to high real-time power prices. The effects on distribution transformer failures is covered in Chapter 2.

References [1]

[2]

Intergovernmental panel on climate change (IPCC), “Climate Change 2013 The Physical Science Basis,” http://www.ipcc.ch/report/ar5/wg1/, Cambridge University Press: New York, NY, 2013. Electrical and Electronics Engineers (IEEE), Standard IEEE C57.91-2011, IEEE Guide for Loading Mineral-Oil-Immersed Transformers and Step-Voltage Regulators.

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Heat Waves [3]

[4]

[5]

[6]

[7]

[8]

[9] [10] [11]

[12] [13]

[14] [16]

[16]

[17]

Pašièko, R., “Impacts of Climate Change on Renewable Energy Sources in Croatia,” Joint ICTP-IAEA Workshop on Vulnerability of Electricity Systems to Climate Change and Extreme Events, UNDP Croatia, 2011. Davcock, C., R. DesJardins, and S. Fennel, “Generation Cost Forecasting Using Online Thermodynamic Models,” Proceedings of Electric the Power, Baltimore, MD, March 30–April 1, 2004. Maulbetsch, J., and M. DiFilippo, California Energy Commission report # CEC-5002006-03, “Cost and Value of Water Use at Combined-Cycle Power Plants,” Sacramento, CA, 2006. Durmayaz, A., and O. S. Sogut. “Influence of Cooling Water Temperature on the Efficiency of a Pressurized-Water Reactor Nuclear-Power Plant,” International Journal of Energy Research, 30: 799–810, 2006. https://www.eia.gov/todayinenergy/detail.cfm?id=3010. World Meteorological Organization, “2015 Hottest Year,” press release, https://www .wmo.int/media/content/2015-hottest-year-record, 2016, Geneva, Switzerland, https:// standards.ieee.org/findstds/standard/C57.92-1981.html, 2011. Pechan, A., and K. Eisenack, “The Impact of Heat Waves on Electricity Spot Markets,” 2013, https://www.uni-oldenburg.de/fileadmin/user_upload/wire/fachgebiete/vwl/V-35713.pdf. U.S. National Weather Service Forecast Office, http://w2.weather.gov/climate/index .php?wfo=bis. California Public Utilities Commission, “DR History in California,” http://www.ora .ca.gov/general.aspx?id=1422. Federal Energy Regulatory Commission (FERC), “2006 State of the Market Report,” http://www.ferc.gov/market-oversight/reports-analyses/st-mkt-ovr/som-rpt-2006.pdf, 2006. EIA, “Northeastern Summer Electricity Market Alert,” http://www.eia.gov/special/alert/ east_coast/pdf/energy_market_alert_July_19_2013.pdf, 2006. Canada.ca, “Daily Data Report for July 2006,” http://climate.weather.gc.ca/climateData/ dailydata_e.html?timeframe=2&Prov=&StationID=10821&Year=2006&Month=7& Day=15. U.S. Energy Information Administration, EIA, “Texas Heat Wave, August 2011: Nature and Effects of an Electricity Supply Shortage,” 2011. National Geographic News, “Record Heat, Drought Pose Problems for U.S. Electric Power,” http://news.nationalgeographic.com/news/energy/2012/08/120817-record-heat -drought-pose-problems-for-electric-power-grid/, 2012. Rączka, J., and J. Maćkowiak–Pandera, “Power Deficit in the Polish Power System in August 2015—Comments of the Forum for Energy Analysis,” http://www.fae.org.pl/files/ file_add/file_add-21.pdf, 2015. United States of America Federal Energy Regulatory Commission (FERC), “DR Compensation in Organized Wholesale Energy Markets,” Docket No. RM10-17-000; Order No. 745, https://www.ferc.gov/EventCalendar/Files/20110315105757-RM10-17-000. pdf, 2011.

Appendix 1A: Defining a Heat Wave A heat wave can be characterized as a prolonged period of hot ambient temperatures that can last from a few days to a few weeks with the anticipated weather conditions of an area at a certain of time. While hot weather is a prerequisite for heat waves, it is notable that heat waves are more than just stand-alone hot days. To be a heat wave, such a period should last at least one day, but it can last several days or even

Appendix 1A: Defining a Heat Wave

21

several weeks. Urban settings can increase temperatures even more, particularly overnight, which is of concern to power equipment. The latter is referred to as the urban heat island (UHI) effect. While there is no agreed upon global definition of a heat wave, the World Meteorological Organization (WMO) defines it as “five or more consecutive days during which the daily maximum temperature surpasses the average maximum temperature by 5°C (9°F) or more.” In the United States, the U.S. National Weather Service defines a heat wave as a spell of “abnormally and uncomfortably hot and unusually humid weather” spanning two days or more. Other countries have adopted their own definitions. For example, in India, it is defined as the period where temperatures are 5°–6°C (9°F–10.8°F) or more above the normal temperature. Over the last 50 years, both the duration and frequency of heat waves have increased and the hottest days of heat waves have become even hotter. In the United States, heat waves have generally become more frequent and intense across the decades since 1960 and have been characterized by high daytime temperatures and, more importantly, high nighttime temperatures, accompanied by high humidity. The number of hot days, warm nights, and heat waves, are all expected to increase through the twenty-first century across the globe. The Intergovernmental Panel on Climate Change (IPCC) believes that heat waves are “very likely” to occur in increased frequency and intensity during this century [1]. The IPCC even postulates that “mega heat waves” affecting large areas and even continents (like those experienced in the summer of 2003 in Europe and 2010 in North America) will increase by a factor of five to 10 over the coming 40 years. As discussed in Chapter 11, heat waves can lead to outbreaks of wildfires, as they can dry vegetation, leading to an increased likeliness of ignition. The evaporation of bodies of water due to high temperatures can also be of concern to power plants, as discussed in Chapter 3.

CHAPTER 2

Effect of Droughts on Hydroelectric Power Plants

This chapter discusses the effect of droughts on hydroelectric plants, while Chapter 3 covers the vulnerability of thermoelectric plants to droughts. This chapter presents case histories of both types of plants, in which they were affected by droughts. Some of the case histories also cover heat waves, as droughts and heat waves typically happen together.

Introduction: Defining Droughts A drought can best be defined as a hydrologic condition of water shortage for a particular user in a particular location. Conditions constituting a drought in one location may not constitute a drought in a different location for users with a different water supplies and demands. In addition, there is no universal definition of when a drought begins or ends. It is a gradual phenomenon that occurs slowly over a period of time. This is in contrast to most extreme weather events, such as storms, floods, or forest fires, which occur relatively rapidly and give little time for preparation. Droughts are sometimes measured by using an index called the Palmer hydrological drought index (PHDI). PHDI is based on the balance of water supply and demand for a given climate, without including man-made changes such as new reservoirs or increased irrigation. The PHDI, and other indexes, classify drought in degrees of severity ranging from dry to exceptional. Table 2.1 depicts the categories of droughts and their potential impacts as they pertain to water availability in streams and reservoirs Drought impacts increase with the length of a drought as river levels decrease, lake and reservoirs are depleted, and water levels in groundwater basins decline. Droughts affect hydroelectric and thermoelectric power plants. Hydroelectric power plants convert the potential energy of water flowing down a steep gradient to turn turbines to generate electric power. Thermoelectric power plants use water to generate steam and as the primary coolant in their thermodynamics processes to generate electricity. When water is scarce, as it is during a drought, the operation of both types of plants is directly affected. Drought impacts can range from the need to adjust water intake or water release to derating or even shutting down the power plants.

23

24

Effect of Droughts on Hydroelectric Power Plants Table 2.1 Drought Categories and Potential Impacts Drought Category

Possible Impacts

Abnormally dry

Going into drought: Short-term dryness slowing planting, growth of crops or pastures Coming out of drought: Some lingering water deficits Pastures or crops not fully recovered

Moderate

Some damage to crops, pastures Streams, reservoirs, or wells low, some water shortages developing or imminent Voluntary water-use restrictions requested

Severe

Crop or pasture losses likely Water shortages common Water restrictions imposed

Extreme

Major crop/pasture losses Widespread water shortages or restrictions

Exceptional

Exceptional and widespread crop/pasture losses Shortages of water in reservoirs, streams, and wells creating water emergencies

Water Use by Hydroelectric Plants It is evident that precipitation is a determining factor in available hydropower generation for a given period of time. Correlation of hydroelectric power generation to changes in precipitation and river discharge is high and close to one. The variability of weather patterns imposes uncertainty in the operation of hydroelectric facilities. Hydropower operations are affected indirectly by changes in air temperatures, humidity, and wind patterns. Snowfall patterns, and associated runoff from snowpack, directly sway the water available for hydroelectric generation. For both this chapter and Chapter 3 on thermoelectric plants, it is important to note that the different plants withdraw and consume water, albeit sometimes at vastly different rates. Hence, in assessing the impacts of droughts on power generation, one has to consider the two aspects of water usage: water withdrawal and water consumption. The United States Geological Survey (USGS) defines “withdrawal” as the amount of water removed from the ground or diverted from a water source for use. The USGS defines water “consumption” as the amount of water that is evaporated, incorporated into products or crops, or otherwise removed from the immediate water environment [1]. Both water withdrawal and consumption factors impact power generation output. While Chapter 3 discusses the water withdrawals and consumption of thermoelectric plants, this chapter discusses water usage by hydroelectric plants. Hydroelectric plants themselves do not consume any measureable amounts of water in the process of generating electricity, and water flowing through the turbines and into the river is not considered consumptive because it is still immediately available for other uses. However, the increased surface area of the reservoirs for hydroelectric plants, when compared to the free flowing stream,

Classifications of Hydroelectric Plants

25

results in additional water evaporation from the surface. Reservoirs with large surface areas experience greater percentages of evaporation than smaller ones, consequently influencing the availability of water for all water uses, including hydropower. A study by the National Renewable Energy Laboratory (NREL) has found that, on average, the amount of water evaporated per kilowatt hour at hydroelectric plants reservoirs in the United States is 68L (18.0G). This is compared to 1.8L (0.47G) at thermoelectric plants [2]. With the exception of one type of hydroelectric plant—pumped hydro plants— once water passes through the turbines of a hydroelectric power plant, it cannot be reused for power generation in that hydroelectric plant but can be used in plants downstream. Therefore, such plants are dependent on a steady feed supply of water. Consequently, during droughts, when precipitation or snowpack levels are reduced, the reduced water levels can decrease to the point where electricity production is severely limited or even halted. Furthermore, because water use by municipalities often increases in times of heat waves, which frequently accompany droughts, dams may be required to release additional quantities of water, further reducing water levels available for hydroelectric generation.

Classifications of Hydroelectric Plants Hydroelectric facilities are classified according to many groupings, such as type, size (capacity), head [the vertical change in elevation, expressed in feet or meters, between the head (reservoir) water level and the tailwater, downstream, level], grid connection (single or isolated), turbine type, or classification as single or multipurpose or single or cascaded. Figure 2.1 depicts some of these classifications, including those most relevant to drought conditions, as discussed in upcoming sections. On the size classification, the U.S. Department of Energy (DOE) uses a more limited range for the sizes of hydroelectric plants. The DOE defines large hydropower plants as those facilities that have a capacity of more than 30 MW, small hydropower as facilities that have a capacity of 100 kW–30 MW, and micro hydropower plants as those with capacities up to 100 kW. Other countries have different classifications. Large hydroelectric plants are connected to the grid. Small hydroelectric plants are used to serve a small community or industrial plant. The definition of a small hydro project varies but 10 MW is generally accepted as the upper limit of what can be termed small hydro, although it may be stretched sometimes to include facilities up to 25–30 MW. Small-scale hydroelectricity production stood at over 110 GW by the end of 2014. Small hydro stations may be connected to conventional electrical distribution or used in isolated areas. A micro hydroelectric plant is a term used for hydroelectric power installations that typically produce up to 100 kW of power, and there are many of these installations around the world, particularly in developing nations. These installations can provide power to a small load such as a small community. Micro hydroelectric systems sometimes complement PV solar energy systems, because in many areas, water flow, and thus available hydro power, is highest in the winter when solar energy is at a minimum.

26

Effect of Droughts on Hydroelectric Power Plants

Figure 2.1

Typical classifications of hydroelectric plants.

In addition to the DOE official size classifications, some also use the term pico hydroelectric system to denote hydroelectric power generation of under 5 kW. Such systems are used in remote areas that require only a small amount of electricity. Even smaller turbines of 200–300W may sometimes be used to power a single home in a developing country.

Conversion of Water Potential Energy into Electric Energy To best understand the effect of droughts on hydroelectric generation, it is useful to review the principals of the generation of electricity from such plants. In conjunction with Figure 2.2, hydroelectric dams exploit the gravitational potential energy of water. Assuming a lossless passage of the water through the penstock (an intake structure that controls water flow, or an enclosed pipe that delivers water to hydro turbines), the gravitational potential energy of water is approximated by E = mgh

(2.1)

Sizing of the Penstock and the Hydroelectric Turbine

27

where m

is the mass of the water.

h

is the height from where the water is falling into the turbine of the hydroelectric plant. This is known as the “head.”

g

is the gravitational constant (9.81 m/s2).

In the MKS system, m is measured in kilograms, g in 9.81 m/s2 , h in meters, and E is in joules. Thus 1 kg, at a height of 1m would have about 10J of potential energy. Since reservoir capacities are expressed in volume (cubic meters in the MKS system), it is noted that 1 m3 is equivalent to 998 kg (~1,000 kg). Droughts affect the head of the water that provides the motive force that turns the turbines. The lower the head, the less water pressure, the less the force to turn the turbine and the less power generation. For example, the Lake Mead reservoir (see the case history later in this chapter) has lost appreciable water due to the recent droughts, leading to the derating of the Hoover Dam electricity generation.

Sizing of the Penstock and the Hydroelectric Turbine In the absence of turbines, or other restrictions, the water falling from the reservoir would emerge from the penstock at a free-flow value velocity given by (2.2), assuming all lost potential energy is converted in potential energy: vi =

2gh

(2.2)

As an example, from (2.3), a 200-m-high dam would eject water at a 62 m/s (140 mph) velocity.

Figure 2.2 Schematic of a hydroelectric dam showing the idealized effect of the height of the water (head) on the pressure of the water entering the turbine.

28

Effect of Droughts on Hydroelectric Power Plants

From (2.2), a flow rate of water F would require an area given by (2.3): A = F /vi

(2.3)

At flow rate of 1,000 m3/s, this corresponds to an opening of 16m 2 (170 square feet), or a diameter of about 4.5m (15 feet). Sizing of the Penstock

The function of the hydroelectric turbine is to extract the kinetic energy of the water. The conversion is not perfect, nor should it be. A typical 10% loss is assumed for hydroelectric dams to account for generator losses and for the fact that not all the kinetic energy can be extracted from the falling water by the turbine. The residual energy would keep the water moving, or it would stop flowing and stall the flow prohibiting the passage of additional water through from the dam. Essentially water exiting the turbine would be sapped of most, but, not all, of its energy. From this assumption, the approximate equations for the power from the dam and the velocity of the water with the turbine in place can be written. The power of water available from the dam is thus given by P = hT rFgh

(2.4)

where

ηT

represents the combined percent efficiency of the dam, usually around 90% (η ≈ 0.90). This is the combined efficiency of the turbine and generator.

ρ F

is the density of water, 1000 kg/m3.

h

is the cubic meters of water that flow through the penstock to the turbine each second, m3/s. is the height (head) in meters of the water behind the dam providing the pressure of the water that converts to the motive force.

And the velocity of the energy-sapped water is therefore given by: vo = vi 1 − h

(2.5)

where vo and vi are the output and input water velocity, respectively.

η

is the efficiency of the turbine in converting potential energy into kinetic energy.

Continuing with the same example as above, from (2.5), if 97% of the kinetic energy (η = 97%) is extracted from the water, its flow velocity is 17% of the freeflow value, or 11.5 m/s (25.7 mph). The area needed with this slightly “inefficient” conversion expands by about five times. This translates into a diameter that is about

Effects of Droughts on Different Hydroelectric Plant Types

29

Figure 2.3 Turbine shaft of one of the generators at the Third Power Plant, Grand Coulee Dam, Washington. [Source: U.S. Bureau of Reclamation (USBR).].

2.25 times larger. The resultant large area, in this case is about 80m 2 . This would explain why the penstocks and hydroelectric turbines are large. As an example, Figure 2.3 shows the rotor from the Third Power Plant of the Grand Coulee hydroelectric plant in Washington. Each of the generators of this plant is fed by an individual penstock with the largest approximately 12.2m (40 feet) in diameter. See the next section for more facts about this plant.

Effects of Droughts on Different Hydroelectric Plant Types There are basically three types of hydroelectric facilities: impoundment, diversion, and pumped storage. These three types are affected by water shortages differently; yet for all of them, electricity production can be restricted, or even halted, if the associated water levels drop too low. Impoundment-Type Hydroelectric Plants

The most common type of hydroelectric power plant is an impoundment facility. An impoundment facility uses a dam to store river water in a reservoir. Many dams

30

Effect of Droughts on Hydroelectric Power Plants

were built for other purposes, and hydropower was added later. Out of the over 80,000 dams in the United States, only about 2,000 of them produce power along with being used for other purposes, such as flood control, recreation, water supply, and irrigation. Mixed uses for water compete with the power plants during droughts. Figure 2.4 is a schematic of an impoundment dam and hydroelectric plant. The dam stores the water. The penstocks carry the water down to the turbines. The turbines are turned by the force of the water on their blades. The turbines rotate the generators to generate electricity. Figure 2.5 shows a recent picture of the Third Power Plant of the Grand Coulee dam and power plant in Washington. According to the USBR, the operator of the Grand Coulee Dam, this dam is the largest concrete structure built in North America, raising the water surface by 107m (350 feet) above the old riverbed. It is 1,596m (5,233 feet) long and 167 (550 feet) wide. The original dam was modified for the Third Power Plant by a 357-m (1,170-foot) long, 62-m (201-ft) high reservoir dam. The power facilities at Grand Coulee Dam consist of a power plant on both the left and right sides of the spillway on the downstream face of the dam [3]. The Grand Coulee is the United States’ largest hydroelectric facility with a summer capacity of about 6.8 GW. Each of the generators of the Third Power Plant is fed by an individual penstock with the largest having an area of approximately 115m 2 (1,242 square feet) or 12m (40 feet) in diameter and carrying up to 1,000 m3/s (35,000 cubic feet per second) of water. The Third Power Plant contains three generators nameplate-rated at 600 MW but able to operate up to 690 MW, and three generators rated at 805 MW. Figure 2.5 shows the new six 91-m (300-ft) 500-kV overhead transmission lines that replaced some aging old-filled cables that stretch from the Third Power Plant to a Booneville Power Administration (BPA) transmission yard. Diversion-Type Hydroelectric Plants

A diversion hydroelectric plant (see Figure 2.6) depends on diverting a portion of a river through a canal or penstock. It may not require the use of a dam. Typically, water is stored in a forebay, often located in a river canyon. The capacity to

Figure 2.4

Schematic of a large impoundment-type hydroelectric plant.

Effects of Droughts on Different Hydroelectric Plant Types

Figure 2.5 Third Power Plant, Grand Coulee Dam, Washington. (Source: USBR.)

Figure 2.6 Aerial photograph of the Thermalito Power Canal in California, a diversion type hydroelectric plant. [Source: California Department of Water Resources (DWR).]

31

32

Effect of Droughts on Hydroelectric Power Plants

generate power depends on the difference in the elevations between the forebay and the powerhouse. A run-of-the-river (ROR) plant is a good example of this type of plant. A ROR power plant may have no water storage at all or a limited amount of storage. If it does, the storage reservoir is referred to as pondage (forebay). Having no pondage would subject this type of a plant to more drought vulnerability and to seasonal river flows. A plant with pondage can regulate the water flow and can serve as a peaking power plant or base load power plant. ROR power is considered an “unfirm” source of power. It has no, or little, capacity for energy storage. The ability to generate power is diminished by a drought if the water supply to the plant cannot be maintained at a certain level, or due to competing uses of the river. Pumped-Storage Type Hydroelectric Plants

Pumped-storage hydroelectricity (PSH), also known as pumped hydroelectric energy storage (PHES), is a type of hydroelectric energy storage used by electric power systems for load balancing. The method stores energy in the form of gravitational potential energy of water from a higher elevation reservoir released to a lower elevation reservoir, passing the powerhouse; see Figure 2.7. Low-cost, off-peak electric power is used to pump the water back from the lower reservoir to the higher reservoir. During periods of high electrical demand, the stored water is released through the turbines to produce electric power. Typically, the round-trip energy efficiency of PSH varies in practice between 70% and 80%. Reversible turbine and generator assemblies act as pump and turbine assemblies. The only way to store a significant amount of energy for such plants is by having a large body of water located on a hill relatively near, but as high as possible above, to a second body of water. In some places this occurs naturally. In some situations, one or both bodies of water have been man-made. Projects in which both reservoirs are artificial, and in which no natural waterways are involved, are commonly referred to as “closed-loop” systems.

Figure 2.7 Schematic of a pumped-hydroelectric plant.

Variability of Hydroelectric Generation in the United States

33

Electricity production at pumped storage facilities is more resistant to drought because most of the water compared to other hydroelectric generation systems (due to less evaporation) at these plants can be reused.

Variability of Hydroelectric Generation in the United States The annual variability of hydropower generation in the United States is high. Figure 2.8 depicts the total capacity of hydroelectric power in the United States along with the total hydropower generation, in million megawatt hours (MWh). Notice that there was a drop of about 70 million MWh, from 2000 to 2002 due to droughts. There was also a drop from 2007 to 2009, shown in Table 2.2, for the 20 largest hydroelectric dams in the United States. Those 20 facilities (see Figure 2.9 for their locations) account for about 45% of the total U.S. hydroelectric power generated. Those two drops correspond to drought conditions witnessed in the United States during those periods. In 2015, the United States experienced its most widespread drought in over half a century. A report by NOAA showed that 55% of the contiguous United States, particularly in the Midwest, and west, suffered droughts, the largest percentage since 1956, when droughts spanned 58% of the country [4]. The two case histories following this section describe the impact of this drought on hydroelectric facilities in California and the Hoover Dam.

Figure 2.8 Comparison of hydroelectric capacity versus generation in the United States 1990– 2010. (Data from: U.S. Energy Information Administration, IEA Forms 860 and 923.)

34

Effect of Droughts on Hydroelectric Power Plants

Figure 2.9 Location of the 20 largest hydroelectric facilities in the United States responsible for about 45% of the total U.S. hydroelectric power generation.

Table 2.2 Generation Differences Due to Droughts for the 20 Largest Hydroelectric Dams in the United States Difference in Average Gen. (%) 2007–2009 vs 1990–2006

Capacity Factor 2009

Name

State

Summer Capacity (MW) 2009

Grand Coulee

WA

6,765

2%

35%

Chief Joseph

WA

2,456

–7%

45%

Robert Moses Niagara

NY

2,353

–4%

71%

John Day

OR

2,160

–13%

44%

Hoover Dam

AZ-NV

2,079

–16%

20%

The Dallas

OR

1,823

–10%

38%

Glen Canyon

AZ

1,312

–14%

32%

Rocky Reach

WA

1,254

–3%

49%

Bonneville

OR

1,093

–8%

47%

Wanapum

WA

1,044

–5%

39%

Boundary

WA

1,040

–5%

48%

McNary

OR

991

–14%

59%

Priest Rapids

WA

932

1%

52%

Wells

WA

840

–8%

51%

Lower Granite

WA

810

–18%

34%

Little Goose

WA

810

–15%

33%

Lower Monumental

WA

810

–16%

33%

Robert Moses

NY

800

2%

90%*

Oahe

SD

714

–42%

30%

Shasta

CA

714

–11%

23%

Source: DOE and the U.S. Department of Homeland Security (DHS).

Case Histories

35

Case Histories Case History: Drought Effects on Hydroelectric Generation in California

The worst droughts in California’s recorded history occurred from 2011 to 2015. These droughts reduced river flows and the levels of lakes and reservoirs. About 44% of California was classified as experiencing “exceptional drought,” the most intense drought category. All the other areas of California were classified as having abnormally “dry,” “moderate drought,” “severe drought,” or “extreme drought.” According to the California Department of Water Resources (DWR) the snowpack in the northern Sierra Nevada range were about one-fifth of normal for the hydrological year that runs from October 2013 through September 2014. The snowpack is a measurement that correlates closely to the amount of amount of water that would be available to fill reservoirs and power hydroelectric generators throughout the year. DWR also reported that for the 2014–2015 rainy season, also known as a water year, (from October1, 2014, to September 30, 2014), the precipitation in the northern Sierra, where some of California’s largest hydroelectric plants are located, was about 25% below the historical averages (1922–1988) and 60% from the wettest years (1982–1983). Figure 2.10 depicts this situation from data extracted from DWR databases [5]. Figure 2.11 shows the effect of the drought on Lake Oroville, a reservoir formed by the Oroville Dam impounding the Feather River, located in Butte County, northern California. At over 4.3 km3 (3,500,000 acre feet), it is the second-largest reservoir in California, after Shasta Lake. The lake is fed by the north fork, middle fork, west branch, and south fork of the Feather River.

Figure 2.10 Cumulative daily/monthly precipitation (inches) precipitation in northern Sierra— the location of most hydroelectric plants in California. (Data from: California DWR.)

36

Effect of Droughts on Hydroelectric Power Plants

Figure 2.11 Comparison aerial views showing Lake Oroville full of water (top image) shot July 20, 2011, and low water level (bottom image) shot September 5, 2014. (Credit: California DWR.)

Effect of Drought on California Hydroelectric Power Resources

Almost 14% of the hydroelectric generating capacity in the United States is concentrated in California. Hydroelectric generation facilities in California fall into one of two categories: facilities smaller than 30 MW and larger than 30 MW. The 30-MW and smaller facilities—small hydro—are generally considered eligible renewable energy resources, and if certified for their net MWh, can count toward renewable energy portfolio standards. Electricity generated at hydroelectric generation stations is extremely valuable for “load following” and meeting peak electricity demands, which are often the most difficult and costly forms of electricity to provide. Hydroelectric generation has varied in California, from 11% in 1992 to a high of 28% in 1995. Hydroelectric generation rises in the winter and spring months with increased runoff and drops during late summer, fall, and early winter when natural runoff is low. The extended droughts of 2012–2014 led to a reduction of about 34,000 GWh of hydroelectric generation compared to average water years, translating to approximately $1.4 billion of higher energy costs to California rate payers and an 8% increase in greenhouse gases due to the use of gas-fired replacement

Case Histories

37

generation, which is often used to assist to offset lower levels of generation from hydroelectric power generation [6]. In 2014, with the decrease in in-state hydroelectric resources, CAISO imported more power from neighboring regions as well as increased output from gas-fired generation. Much of the imported power came from hydroelectric dams located in the Pacific Northwest, which also were experiencing low water supply [7]. Figure 2.12 shows the percent of hydroelectric and gas-fired generation in California from 2005 to 2015. Electricity generation from the hydroelectric plants correlates directly with actual runoff in California rivers. The U.S. Geological Survey (USGS) defines runoff as “the result of precipitation (both rainfall and snowfall) that is in excess of the demands of evaporation from land surfaces, transpiration from vegetation, and infiltration into soils.” The water that remains available, or runoff, is the amount of water that makes its way to streams, rivers, and, possibly, to the ocean. The USGS operates a stream-gaging network that provides stream flow records and enables the compilation of annual runoff data. Comparing the data used to derive these two curves, one can find an inverse or negative correlation that is strong, with a correlation factor of –0.81. When runoff fell, generation from hydroelectric plants decreased, and more gas-fired generators were used. There was 1,628 MW less of in-state hydro power in the summer of 2014 [7]. This was compensated by more renewable generation (solar and wind) that came on-line, more gas-fired generation, and the import of more power from other northwest states. Besides less power from hydroelectric generation, the drought in 2014 caused curtailment of over 1,000 MW of thermoelectric generation due to the lack of cooling water.

Figure 2.12 Changes of hydroelectric and gas-fired generation in California from 2005 to 2015. [Data from: Energy Information Agency (EIA).]

38

Effect of Droughts on Hydroelectric Power Plants

Case History: Drought Effects on Lake Mead and the Hoover Dam

The Hoover Dam impounds Lake Mead whose water levels are managed through releases from Lake Powell, located 600 km (370 mi) up the Colorado River behind the Glen Canyon Dam. The U.S. Bureau of Reclamation (BOR), the operator of this dam, defines an elevation of 372.3m (1,221.4 ft), the top of the spillway crest at Hoover Dam, as the maximum lake storage capacity and 371.7m (1,219.6 ft) elevation as the “operationally full” level. The minimum elevation to generate power at Hoover Dam is reported by BOR to be 320m (1,050 ft), below which the reservoir is considered an “inactive pool.” Water above 320m (1,050 ft) elevation is considered “live storage” for generating power with the original turbines. A “dead pool” level is further defined at 273m (895 feet), which is the lowest water outlet at the Hoover Dam. When full, Lake Mead is the largest reservoir in the United States, but it has not reached full capacity since 1983 due to a combination of droughts and increased water demand. From 1999 to 2015 the flow of water to Lake Powell from key tributaries in the river basin has been decreasing due to drought-related issues (drops in overall precipitation, less snowpack, and earlier snow melt). This extended drought condition is the most extreme drought observed since measurements began in the 1900s. Less water in Lake Powell translates directly into less water for Lake Mead. Since 1999, the water level at Lake Mead has plunged over 40m (130 ft) to a low of 328m (1,076 ft) above sea level in May 2015. Levels below 330m (1,084 ft) have not been recorded since a period of sustained drought in 1956. See Figure 2.13.

Figure 2.13

Lake Mead surface elevation over sea level from 1980 to 2015.

Case Histories

39

Hydroelectric Generation of the Hoover Dam

The Hoover Dam plant has a nameplate capacity of about 2,080 MW. The rated plant capacity is about 3 million horsepower. It has 17 main turbines: nine on the Arizona side and eight on the Nevada side. The original turbines were replaced through an uprating program between 1986 and 1993 [8]. In 2007 the U.S. Department of Interior issued guidelines on the water usage of the Colorado River affecting Lake Powell and Lake Mead. The guidelines basically stated that at certain Lake Mead elevations, as downstream water demands are curtailed, power production would need to be concurrently reduced. With the drought conditions detailed here, Hoover Dam’s hydroelectric generation output has been significantly curtailed. In July 2014, the facility was derated down to 1,592 MW—or 77% of its capacity. Water Intake Structures for the Hoover Dam

There are four water intake, reinforced-concrete, structures for the Hoover Dam, with two on each side of the canyon; see Figure 2.14. Figure 2.15 shows the high water mark of 372m (1,220.7 ft). The diameter of these towers is 25m (82 ft) at the base, 19.3m (63.25 ft) at the top. Each tower is 120m (395 ft) high and each controls one-fourth the supply of water for the power plant turbines. Water intake is through two cylindrical gates, each 9.7m (32 ft) in diameter and 3.4m (11 ft) high. One gate is near the bottom and the other near the middle of each tower. Notice the “bathtub ring” on the exposed rock sides of Lake Mead. These bathtub rings became very prevalent in the last five years on lakes and reservoirs in California and big portions of the West due to the droughts. Enhancing the Power Pool Level of Hoover Dam

To lower the minimum power pool elevation to 290m (950 ft), five new widehead turbine runners, designed to work efficiently with less water flow, have been installed at the Hoover Dam starting in 2012 with the final one installed in 2015.

Figure 2.14 Two of the four intake structures at the Hoover Dam showing the depleted water levels due to the prolonged drought in May 2015. (Source: USBR.)

40

Effect of Droughts on Hydroelectric Power Plants

Figure 2.15 Impact of prolonged droughts on Lake Mead.

The “wide-head” is the water wheel portion of that drives the generator and that would help the generating units to operate more efficiently over a wider range of lake levels (or “head”) than the existing turbines. These turbines enable the Hoover Dam to generate power more efficiently as the water level behind the dam fluctuates between low and high elevations. Previously, a minimal level of 320m (1,050 ft) above sea level in Lake Mead served as the benchmark to guarantee power generation, but the new turbines would make it possible to revise the minimum water level to 950 ft. The dead pool level remains unchanged at 273m (895 ft).

Conclusions This chapter discusses the effect of droughts on hydroelectric plants, providing case histories of both types of plants, as they were affected by droughts. A drought can best be defined as a hydrologic condition of water shortage for a particular user in a particular location. Conditions constituting a drought in one location may not constitute a drought in a different location for users with a different water supplies and demands. Hydroelectric plants require water to generate electricity. The relation between the two is simple: Less water in a reservoir or river equals less potential for generating electricity. Correlation of hydroelectric power generation to changes in precipitation and river discharge is high, and, close to one. Hydroelectric plants themselves do not consume any measureable amount of water in the process of generating electricity, and water flowing through the turbines and into the river is not considered consumptive because it is still immediately available for other uses. A study by the National Renewable Energy Laboratory (NREL) found that, on average, the amount of water evaporated per kilowatt hour at hydroelectric plants’ reservoirs in the United States is 68L (18.0G). The variability of weather patterns imposes uncertainty in the operation of hydroelectric

Exercises

41

facilities. With the exception of one type of hydroelectric plant—pumped hydro plants—once water passes through the turbines of a hydroelectric power plant, it cannot be reused for power generation in that hydroelectric plant but can be used in plants downstream. Therefore, such plants are dependent on a steady feed supply of water. Consequently, during droughts, when precipitation or snowpack levels are reduced, the reduced water levels can decrease to the point where electricity production is severely limited or even halted. Furthermore, because water use by municipalities often increases in times of heat waves, which frequently accompany droughts, dams may be required to release additional quantities of water, further reducing water levels available for hydroelectric generation. Typically run-of-river hydroelectric plants have no pondage. That would subject this type of a plant to more drought vulnerability and to seasonal river flows. The ability to generate power is diminished by drought if the water supply to the plant cannot be maintained at a certain level or is subject to competing uses of the river. Electricity production at pumped storage facilities is more resistant to drought because most of the water, less evaporation, at these plants can be reused. In 2015, Lake Mead and California’s reservoirs and lakes were far below average levels, leading to a situation in which the “bathtub rings” on many of them were bigger than the depth of the remaining water in them. Larger bathtub rings imply lower heads. Lower heads yield less power for hydroelectric generation for impoundment-type hydroelectric plants. In California, which has been hit with droughts for five consecutive years, hydroelectric plants have operated at reduced power levels in the summer months, and for fewer hours during spring when water was being conserved and in the fall when water supplies were severely limited. The gap in hydroelectric generation was filled with gas-fired generation, other renewables (such as solar and wind), and power inputs. The supplementary chapter to this chapter is Chapter 3, which details the impact of droughts on thermoelectric generation.

Exercises Exercise 2.1

1. Calculate the theoretical hydroelectric output of a dam with the following specific normal conditions: Head = 70m. Stream with a flow = 60 m3/s. Efficiency = 80%.

ρ = density (kg/m3) (~ 1000 kg/m3 for water). 2. Calculate the output of the same dam in drought conditions that reduce the flow of the water in the stream by 20%. Solution:

From (2.4) P = hT rFgh

42

Effect of Droughts on Hydroelectric Power Plants

where

ηT

represents the combined percent efficiency of the dam, 80% in this case. This is the combined efficiency of the turbine and generator

ρ F h

is the density of water, 1,000 kg/m3. is the cubic meters of water flow in cubic meters per second. is head) in meters, providing the pressure of the water that converts to the motive force.

P = 0.8 × 60 × 70 × 1,000 × 9.81W. P ≈ 33 MW. The drought conditions would only affect the flow of water; hence, the theoretical output would then be: P = 33 × 0.8 = 26.4 MW Exercise 2.2

The potential energy stored by raising water in a pumped storage plant is given by (2.1). E = mgh Roughly how much water will need to be pumped to the top of the 366-m-high second reservoir plant to store 200 MWH (1 kWh = 3.6 MJ)? a. 2,000 m3; b. 2 million m3; c. 20 million m3.

References [1] [2] [3] [4] [5] [6]

[7] [8]

Kenny, J. F., et al., Estimated Use of Water in the United States in 2005, U.S. Geological Survey (USGS) Circular 1344, 2009. Torcellini, P., N. Long, and R. Judkoff, Consumptive Water Use for U.S. Power Production, National Renewable Energy Laboratory (NREL), NREL/TP-550-33905, 2003. http://www.usbr.gov/projects/Powerplant.jsp?fac_Name=Grand+Coulee+Powerplant https://www.ncdc.noaa.gov/sotc/drought/201506 California Department of Water Resources (DWR), Northern Sierra Precipitation 8-Station Index, http://cdec.water.ca.gov/cdecapp/precipapp/get8SIPrecipIndex.action. Pacific Institute, Impacts of California’s Ongoing Drought: Hydroelectricity Generation, March 2015. http://pacinst.org/publication/impacts-of-californias-ongoing-drought -hydroelectricity-generation. California Independent System Operator, CAISO, http://www.caiso.com/Documents/ CaliforniaISO-Challenging2014SummerButReliabilityHeldFirm.pdf. http://www.usbr.gov/projects/Powerplant.jsp?fac_Name=HooverPowerplant.

Appendix 2A: The Effects of Droughts and Heat Waves on Power Plants in the United States [9] [10]

[11] [12] [13]

[14]

[15] [16] [17]

[18]

[19]

[20]

[21] [22]

43

The Bonneville Power Administration (BPA), https://www.bpa.gov/power/pg/hydrspl .shtml. U.S. Department of Energy and Department of Homeland Security, Dams and Energy Sectors Interdependency Study, 2011. http://energy.gov/sites/prod/files/Dams-Energy% 20Interdependency%20Study.pdf, 2011. http://www.water.ca.gov/serp.cfm?q=drought+california&cx=001779225245372747843 %3Amxwnbyjgliw&cof=FORID%3A10&ie=UTF-8 http://www.reviewjournal.com/business/energy/nv-energy-backs-coal-fired-ely-energy -center-air-force-objects-solar-plant Walton, B., Circle of Blue, Low Water May Halt Hover Dam’s Power, 2010. http://www. circleofblue.org/waternews/2010/world/low-water-may-still-hoover-dam%E2%80%99s -power/, 2010. “Western Drought Steals Clean Energy Along with Fresh Water at Power Plants,” Washington Post, 2015. https://www.washingtonpost.com/national/at-hoover-dam-the -drought-is-stealing-clean-energy-along-with-fresh-water/2015/04/26/8ce2740a-e93d -11e4-9767-6276fc9b0ada_story.html, 2015. Joint Institute for Strategic Energy Analysis, Concentrating Solar Power and Water Issues in the U.S. Southwest, 2015. http://www.nrel.gov/docs/fy15osti/61376.pdf. “Heat Shuts Down a Coastal Reactor,” New York Times, 2012. http://green.blogs.nytimes .com/2012/08/13/heat-shuts-down-a-coastal-reactor/. U.S. DOE, U.S. Energy Sector Vulnerabilities to Climate Change and Extreme Weather, 2013. http://energy.gov/sites/prod/files/2013/07/f2/20130710-Energy-Sector-Vulnerabilities -Report.pdf. Krier, R., “Extreme Heat, Drought, Show Vulnerability of Nuclear Power Plants,” Inside Climate News, 2012. http://insideclimatenews.org/news/20120815/nuclear-power-plants -energy-nrc-drought-weather-heat-water?utm_source=feedburner&utm_medium=feed &utm_campaign=Feed%3A%20solveclimate%2Fblog%20%28InsideClimate%20 News%29. Pacific Northwest National Laboratory (PNNL), Climate and Energy-Water-Land System Interactions, Technical Input Report to the U.S. Department of Energy in support of the National Climate Assessment. Report No. PNNL-21185, 2012. http://www.pnnl.gov/ main/publications/external/technical_reports/PNNL-21185.pdf. Fowler, T., “More Power Plant Woes Likely If Texas Drought Drags into Winter,” Fuelfix. com, 2011. http://fuelfix.com/blog/2011/08/24/more-power-plant-woes-likely-if-texas -drought-drags-into-winter/. Bigg, M., “River Flows cut to Fight Southeast Drought,” Reuters, 2007. http://www .reuters.com/article/2007/11/19/environment-usa-drought-dc-idUSN1641201520071119. Union of Concerned Scientists, Energy and Water Demands Clash During Hot, Dry Summers, 2012. http://www.ucsusa.org/sites/default/files/legacy/assets/documents/ clean_energy/ew3/Infographic-The-Energy-Water-Collision-All-Facts.pdf.

Appendix 2A: Summaries of Recent Case Histories of the Effects of Droughts and Heat Waves on Power Plants in the United States This appendix presents, in Figure 2A.1 and Table 2A.1, examples of recent case histories of power plants (mainly hydro and thermal) that have experienced power generation curtailment (or have faced critical conditions that could have led to curtailment if conditions had continued) due to droughts or heat waves. This appendix, along with Chapters 1 and 3, should supplement this chapter. The overwhelming majority of the thermoelectric plants (nuclear of coal) that were impacted by those

44

Effect of Droughts on Hydroelectric Power Plants

Figure 2A.1 Sample of power plants that were affected by droughts and heat waves from 2006 to 2012. This figure illustrates some of the many ways in which different types of U.S. power plants have been directly impacted by drought and heat wave conditions.

conditions employed once-through or open-cycle cooling systems. The large number of once-through cooling systems indicates that the issue of power generation curtailment could become a more widespread issue should droughts and heat waves become more persistent and severe. Table 2.3 contains brief descriptions of some critical events at different types of power plants that were recently affected by droughts and/or heat waves.

Table 2A.1 Brief Explanation of the Events in Figure 2A.1 Map Reference

Year

Event and Critical Situation Caused by Drought or Heat Wave

1

2010

The Bonneville Power Administration (BPA) reported a net loss of $233 million due to below-normal precipitation and stream flows in the Columbia River basin that resulted in insufficient hydropower generation to fulfill its load obligations [10].

2

2012, 2014, and 2015

Reduced snowpack in the mountains of the Sierra Nevada limited California’s hydroelectric power generation capacity by about 8%, or 1,137 MW. In 2014 there was 1,628 MW less of in-state hydro. By 2015 the hydroelectric generation in California had fallen by 60% in four years [11]. In an average year, hydropower provides 18% of the state’s electricity needs. During the four-year period from October 2011 through September 2015, hydropower generation was at 10.5% of total electricity generation. For 2015, hydropower was far below normal, providing less than 7% of total electricity generated in-state.

3

2009

NV Energy withdrew its application through the state Public Utilities Commission to build the Ely Energy Center, a central Nevada coal-fired power that would have been one of its biggest generators. The plant would have used more than 7.1 million gallons of water per hour [12].

Appendix 2A

45

Table 2A.1 (continued) Map Reference

Year

Event and Critical Situation Caused by Drought or Heat Wave

4

2010

Water levels in Lake Mead dropped to 330.4m (1,084 ft), a level not seen since 1956. This forced the BOR, the operator of the Hoover Dam, to reduce its generating capacity by 23% [13, 14].

5

2010

The Arizona Corporation Commission (ACC) modified the certificate of approval for the proposed 340-MW Hualapai Valley Solar project to prohibit the use of groundwater at the plant. It required the plant to use effluent water from the nearby City of Kingman or to employ dry or hybrid cooling technology. The decision marked the first time the ACC prohibited the use of groundwater for a solar power plant [15].

6

2006

Power production of the North Platte Project (a series of hydroelectric plants along the North Platte River in Nebraska and Wyoming) was reduced by about 50% due to a multiyear drought.

7

2000–2008 Extended periods of drought conditions forced Nebraska Public Power District (NPPD) to modify the 1,365-MW Gerald Gentlemen Station (GSS) plant cooling system and to develop alternate methods for providing cooling water to the plant, such as a well field. The plant is the largest in the State of Nebraska.

8

2006

Extended periods of drought conditions reduced the flow in the Missouri River that led to concerns that discharge water would exceed permit limits forcing curtailment in the power generated at the Missouri River Plants.

9

2006

During a 2006 heat wave, Northern States Power (NSP) Prairie Island Nuclear Power Plant in Minnesota had to cut its power generation by more than half because the water it draws from the Mississippi River for cooling was too warm.

10

2006

Two units at Exelon’s Quad Cities Generating Station in Illinois had to reduce power generated to less than 60% due the temperature of the Mississippi River that was too high to discharge heated cooling water from the two reactors into it.

11

2012

Exelon’s Braidwood nuclear plant in Illinois needed special permission to keep operating because its cooling water pond reached 38.9°C (102°F) as a result of low rainfall and high air temperatures. It was designed to run at temperatures up to 36.7°C (98°F) [16]. In total, four coal-fired power plants and four nuclear power plants in Illinois requested permission to exceed their permitted water temperature discharge levels. The Illinois Environmental Protection Agency granted special exceptions to the eight power plants, allowing them to discharge water that was hotter than allowed by federal Clean Water Act permits [17].

12

2006

One unit at American Electric Power (AEP) D.C. Cook Nuclear Plant was shut down because the heat wave raised the air temperature inside the containment building above 48.9°C (120°F), and the temperature of the cooling water from Lake Michigan was too warm to use for cooling. The plant could only be returned to full power after five days after the heat wave had passed [18].

13

2007 and 2010

The Tennessee Valley Authority’s Browns Ferry Nuclear Plant had to reduce its power output because the temperature of the Tennessee River was too high to discharge into heated cooling water from the reactor [19]. In 2007 one of three nuclear reactors was shut down due to high river water temperature. Drought in the region and high ambient temperatures had caused an increase in the water temperatures in the river. During the prolonged heat wave in the summer of 2010, water temperatures in the river hit 32.2°C (90°F), forcing the plant to significantly cut the power output of all three of its units for nearly five consecutive weeks [17].

14

2007

Georgia Power’s Plant Hammond had to reduce its load to a minimum for several nights due to record drought that resulted in low river water levels and a heat wave. Temporary measures were put into place to mitigate thermal impacts. These measures included reducing load to a minimum each night and installing temporary mobile cooling towers to cool about one-fifth of the condenser flow rate by about 11°C (20°F).

46

Effect of Droughts on Hydroelectric Power Plants

Table 2A.1 (continued) Map Reference

Year

Event and Critical Situation Caused by Drought or Heat Wave

15

2007 and 2008

Due to extreme drought, the water level of Lake Norman in North Carolina, dropped to less than one foot above minimum allowable levels for the Duke Energy’s McGuire Nuclear Plant. The cooling water intake within less than 0.3m (1 ft) of the minimum level allowable. Since that time the intake elevation has been lowered by 1m (3 ft) to provide additional buffer for drought situations.

16

2012

Frist Energy Corp’s Perry Nuclear Station, reactor 1, in Ohio dropped production in late July to 95% of capacity because of above-average temperatures.

17

2011

An extreme heat wave and record drought in Texas forced ERCOT to declare power emergencies due to a large number of unplanned power plant outages and at least one power plant reducing its output [20].

18

2007

Severe drought in the Southeast caused the Chattahoochee River, which supports more than 10,000 MW of power generation, to drop to one-fifth of its normal flow. Overall, hydroelectric power generation in the Southeast declined by 45% [21].

19

2008

Water levels in Lake Lanier, the major source of the drinking water supply for the City of Atlanta, were significantly reduced due to the 2008 drought. This drove the governor of Georgia to consider reducing the releases from this lake. Such reductions directly impact two nuclear plants located downstream from the lake: Farley and Scholtz Power nuclear plants.

20

2007

Due to extreme drought in the Southeast region, the water level of Harris Lake dropped significantly. The water in Harris Lake was at 66.67m (218.5 ft)—just 1.1m (3.5 ft) above the limit set in the Duke Energy’s Shearon Harris Nuclear Power Plant license. Officials warned in November 2007 that the drought could force the plant to shut down.

21

2008

Entergy’s Vermont Yankee Nuclear Power Plant had to limit output four times in July because of low river flow and heat. At one point, production was reduced to 83% of capacity. The plant is on the Connecticut River, upstream of the Vernon, Vermont Hydroelectric Dam and used the reservoir pool for its cooling water. Entergy powered down the Vermont Yankee nuclear station, which went on-line in 1972, in December of 2014 due to competing lower cost natural gas-fired plants.

22

2007

Duke Energy’s Riverbend Steam Station in North Carolina had to curtail generation due to high cooling water temperature.

23

2007

Duke Energy’s 1,140-MW Allen Steam Station, also in North Carolina, had to curtail generation due to high cooling water temperature.

24

2012

Dominion Resources’ Millstone Nuclear Power Plant in Connecticut shut down one reactor because the temperature of the intake cooling water, withdrawn from the Long Island Sound reached 24.83°C (76.7°F). This was higher than the allowed 23.9°C (75 °F) technical specifications of the reactor. Water temperatures were the warmest since operations began in 1969 [16].

25

2010

Exelon’s Limerick Nuclear Power Plant in Pennsylvania had to reduce power because the temperatures of the intake cooling water, withdrawn from the Schuylkill River, was too high and did not provide sufficient cooling for full power operations [17].

26

2010

PSEG’s Hope Creek Nuclear Power Plant in New Jersey had to reduce power because the temperatures of the intake cooling water, withdrawn from the Delaware River was too high and did not provide sufficient cooling for full power operations [17].

CHAPTER 3

Effect of Droughts on Thermoelectric Power Plants Introduction Water is needed in the thermodynamic process of turning heat into work for generating electricity in thermoelectric plants (see Figure 3.1.) In these plants, fuel (e.g., coal or nuclear) is used to heat water to produce steam, which is expanded over a turbine to produce electricity. The driving force for the process is the condensation of the steam into water following the turbine, and this is where the demand for cooling water arises. It is the condensation process that creates a backpressure that draws the steam over the turbine. The steam condensation typically occurs in a heat exchanger known as the condenser. The steam is condensed by the flow of cooling water (fresh, brackish, or saline) for cooling of thermal power plants through tube bundles located within the condenser. Cooling water mass flow rates of greater than 50 times the steam mass flow rate are necessary depending on the allowable temperature rise of the cooling water. At higher condenser cooling water inlet temperatures, the steam condensate temperature is higher, and subsequently turbine backpressure is higher. The higher the turbine backpressure, the lower the power generation efficiency.

Figure 3.1

Use of water in thermoelectric power plants.

47

48

Effect of Droughts on Thermoelectric Power Plants

Droughts can lead to low levels of surface water sources (lakes and rivers) limiting the amount of water that can be withdrawn for the plant cooling needs and exposing the plant water intake structures. When water levels are low, plants might not have the option to withdraw at a higher rate, in which case the power plant is derated (its output is lowered). For a thermoelectric plant to condense the same amount of steam in the cooling process, it needs to withdraw water at higher rates, heat the withdrawn water to higher temperatures, or both. The large amounts of fresh water withdrawn by thermoelectric plants, comes at a time of declining supply, particularly in certain regions’ present and projected water shortages and droughts, as in the West and Southwest of the United States. The use of alternative power plant water-conserving cooling systems is now often proposed or even mandated by electric regulators even in areas where water is plentiful or on power plants located near large bodies of water. Alternatives to the conventional cooling approaches offer significant opportunity for water conservation, but they are costlier and require more equipment, which results in reduced plant efficiency.

Thermoelectric Plant Water Usage in the United States Data from the USGS shows that thermoelectric power plants withdrew 161 billion gallons per day in 2010; see Figure 3.2 [1]. That translates into 45.35% (38% of total freshwater) of the total water withdrawal in the nation; see Figure 3.3. In freshwater withdrawals, thermoelectric plants are second only to agriculture. According to the USGS, surface water was the source for over 99% of total water withdrawals, and 73% of those surface-water withdrawals were from lakes and rivers. On average, 19 gallons were used to produce 1 kWh (kilowatt-hour) of

Figure 3.2 Freshwater withdrawals by thermoelectric power plants in the United States, 1950– 2010. (Data from: USGS [1].)

Thermoelectric Plant Water Usage in the United States

49

Figure 3.3 Water withdrawals by thermoelectric power plants as a percentage of total water use in the United States, 1950–2010. (Data from: USGS [1].)

electricity in 2010, compared to almost 23 gallons in 2005. The 2010 thermoelectric withdrawals were 20% less than values for 2005 due to plant retirements and an increase in the use of natural gas. Factors influencing water use intensities of power plants include the age of the plant, the thermal efficiency of the plant, and the age and type of the cooling system. Figure 3.4 portrays the mix of the power generation technology changes in the United States between 2000 and 2014 according to data extracted from the EIA [2].

Coal Oil and other liquids

Figure 3.4 Mix of bulk system power generating technologies in the United States, 2000–2014. (Data from: EIA [2].)

50

Effect of Droughts on Thermoelectric Power Plants

Note that even though the percentage of the water withdrawal by thermoelectric plants in the United States for 2010 was over 45%, the water consumption by these plants was only about 3%. According to the USGS, the largest total freshwater sources of withdrawals for thermoelectric power in any state were in Texas. Illinois, Texas, Michigan, and Alabama together accounted for more than 32% of freshwater withdrawals for thermoelectric power.

Thermoelectric Cooling Technologies Four types of cooling system designs are used for thermoelectric power plants: once-through, recirculating, dry, and hybrid. The type of cooling technology used greatly influences the amount of cooling water a plant uses and determines its vulnerability to droughts. Figure 3.5 depicts the vintages and types of cooling systems used in the United States between 1950 and 2012. Once-Through Cooling (OTC) System

The majority of older thermoelectric plants in the United States typically use OTC systems, also known as open-loop cooling systems, due to their simplicity and low cost. In 2010, power plants with OTC systems accounted for 94% of total withdrawals and 47% of net power generated. OTC plants withdraw large amounts of water from surface water sources (rivers, lakes, ponds, and the ocean) or from groundwater wells and pass it through tubes of a condenser to cool the passing steam as it exits the turbine; see Figure 3.6. The condensed steam is returned back into water for use in the boiler for generating electricity once again, and the cooling water is returned to the environment at an elevated temperature. The withdrawal

Figure 3.5 from: EIA.)

Vintage of cooling systems in the United States between 1950 and 2012. (Data

Thermoelectric Cooling Technologies

51

rate of a OTC plant is relatively high, in the range of 100–200 m3/MWh (about 25,000–50,000 gallons/MWh), while water consumption remains low. Very few new power plants use OTC because of the significant water withdrawals involved and the increased difficulty in siting power plants near available water sources. In addition, elevations in the temperature of the water returned to the source can be in the range of 8°C–15°C (about 15°F–25°F) raise concerns for vegetation, algae growth, and fish. In the United States, of the 104 nuclear power reactors that were operating in 2010 (before the retirements of some plants such as the San Onofre in California), 60 used OTC (from rivers, lakes, or the sea), 35 used circulating towers, and nine units used dual systems and switched between them depending on environmental conditions. [3, 4]. Most power plants that employ OTC obtain cooling water from surface water sources use some method of primary screening to prevent large objects from being drawn through the cooling system, to avoid clogging or damage to sensitive equipment. These screens typically have mesh panels with slot sizes ranging from about 10 cm to 25 cm (3/8 inch to 1 inch) and are periodically cleaned from any debris, including aquatic organisms. Impingement can occur when organisms, such as fish, are trapped against the screen as a result of the force of the intake water and are unable to escape. Water Consumption of OTC

The higher temperature water discharged from OTC into the source causes evaporation in the receiving water body because of the increased temperature of the discharge, which may be as low as 0.5%, but could be as high of 2%–3% of the withdrawn amount.

Figure 3.6 Schematic of the flow of cooling water in the condenser of a once-through power plant cooling system.

52

Effect of Droughts on Thermoelectric Power Plants

Recirculating Systems

Power plants built after the 1960s shifted toward cooling systems that reuse water: recirculating systems (see Figure 3.7.) These are also referred to as closed-loop cooling systems. In the past, this method was necessary when access to abundant water supply was not available. Today, using this kind of cooling may be mandated by state regulators. The recirculating cooling systems are similar to OTC in that the steam is condensed in a water-cooled, shell-and-tube steam condenser. They differ from the OTC systems in that the heated water is not returned to the environment, such as a lake, river, or the ocean. Two primary technologies are used for wet recirculation cooling systems: wet cooling towers, such as the one shown in Figure 3.8, and cooling ponds. Cooling towers are of two types: natural-draft and mechanical-draft. If a cooling tower is used, then the ambient air transfers the heat from the warm water, evaporating some of it and creating a water vapor plume. The remaining cooler water is returned to the condenser for reuse in cooling steam. When a cooling pond is used, cooling relies on natural conduction/convection heat transfer from the water to the atmosphere to cool recirculating water. In both of these systems, water is kept in a closed loop. Forced draft cooling towers have a higher electrical load and higher condensing temperatures compared to OTC. Recirculating wet cooling systems with a mechanical-draft wet cooling tower significantly reduces (by a factor of 20–50 times) the amount of water withdrawn into a power plant compared to plants using OTC; however, nearly all the water withdrawn for cooling purposes is evaporated in the process. Typical values for closed-cycle wet cooling systems range from 400 to 700 gallons/MWh. [5]. The water consumption is due to evaporative losses and the replacement water used for blowdown, a process to prevent the buildup of

Figure 3.7 Schematic of the flow of cooling water in the condenser of a recirculating cooling power plant cooling system.

Thermoelectric Cooling Technologies

53

Figure 3.8 Cooling tower used in a power plant recirculating system. (Courtesy of the U.S. Department of Energy.)

minerals and sediments in the water. The water that is consumed must be continually replaced. Water withdrawals for a recirculation system are used to replace water lost to evaporation, blowdown, drift, and leakage. In 2010, the National Energy Technology Laboratory (NETL) released a study highlighting vulnerabilities in the fleet of coal plants across the United States [6]. The study found that 53% of vulnerable plants use OTC systems and that 47% use recirculating systems. The study found that most vulnerable recirculating cooling plants relied on cooling towers. Plants with recirculating cooling systems required 6% less water and produced 53% of the net power generated. Power plants with recirculating cooling systems are found in every state but were the predominant type of cooling system at power plants in the western states. Dry Cooling

A small percentage of power plants in the United States uses dry cooling. Since 1999, nearly 20 GW of new U.S. capacity has utilized dry cooling. Dry cooling systems were typically installed because local rivers and groundwater could not otherwise support the cooling demands of the plant. In contrast to the other two previous kinds of cooling systems, dry cooling systems reject the heat of condensation directly

54

Effect of Droughts on Thermoelectric Power Plants

to the atmosphere without consuming cooling water. These systems can be either direct or indirect. In direct dry cooling, typically used at gas-fired combined cycle plants, steam is ducted to an air-cooled condenser where it is condensed; see Figure 3.9. Indirect dry cooling, with limited application in the United States, utilizes a cooling water loop to condense turbine steam in a conventional surface condenser or a contact condenser. Dry cooling systems are costlier than recirculating systems. This is due to the additional equipment and systems needed for dry cooling, such as fans, drive motors, finned-tube heat exchangers, and different steel structures. Running this additional equipment requires significant amounts of electricity, which makes this system less efficient. Generation performance at a dry-cooled plant is sensitive to meteorological conditions. The condensing temperature, in the case of direct dry cooling is limited by the ambient temperature and humidity. As a result, power plant output is lower during the warm days of the year. This reduced cooling translates to an energy penalty of about 2–7% depending on the ambient temperature in the area. Despite the increased cost and lower efficiency, many areas have installed dry cooling plants because the benefit of lower dependence on water outweighs the other consequences. The efficiency penalty and costs for dry cooling made dry cooling in the past less suitable for large plants that require a lot of steam such as those powered by coal or nuclear energy, and they were typically used to support the thermal portion of combined-cycle natural gas plants (normally less than 50% of the plant’s total output). This is fast changing in the United States and elsewhere, as demand for energy and water grows and there is a great incentive to reduce the water required for energy generation. Nowhere in the world is this more evident as it is in South Africa. The local utility, Eskom, operates both the world’s largest

Figure 3.9

Schematic of a dry-type power plant cooling system.

Hybrid Cooling

55

direct-dry-cooled (Matimba Power Station) and indirect-dry-cooled (Kendal Power Station) plants. All fossil-fueled new-build Eskom power plants are dry cooled. The 4,800-MW Medupi power station will become the world’s largest direct-drycooled power plant once it is placed into operation. In the meantime, the Matimba Power Station (4,000-MW capacity) uses approximately 20 times less water than an equivalent wet-cooled power plant.

Hybrid Cooling Hybrid cooling plants employ a combination of wet and dry cooling systems (see Figure 3.10) to achieve the best features of each: the water conservation capability of dry cooling and wet cooling performance on the hottest days. Hybrid systems have the potential for more than 50% water savings compared to wet cooling towers. Some hybrid systems can also operate both cooling systems in unison to increase cooling efficiency. Industry Sponsoring Cooling System R&D

The electric power industry is conducting research into new technologies for more drought-resilient cooling methods for power plants. The Electric Power Research Institute (EPRI) is working on methods to reduce cooling tower water consumption with a supplemental dry cooling system that uses refrigerant to partially cool the steam before it reaches a specially designed cooling tower. Another idea worked on by EPRI is a dry cooling system with refrigerant that is driven by waste heat of the plant and solar energy.

Figure 3.10

Hybrid power plant cooling system.

56

Effect of Droughts on Thermoelectric Power Plants

Case Study: Phaseout of OTC in California In 2010, the California State Water Resources Control Board (SWRCB) adopted a policy requiring coastal power plants to phase out the use of OTC systems. [7] The policy affected 19 California power plants, drawing about 15 billion gallons per day from the state’s coastal and estuarine waters. Sixteen of those, totaling about 17,500 MW, are in the CAISO balancing authority area, such as the Encino plant in Figure 3.11 located in coastal town of Carlsbad. The other three are in the Los Angeles Department of Water & Power (LADWP) balancing area. The OTC policy determined that closed-cycle evaporative cooling was the best available technology and established this as a benchmark for two compliance tracks, according the SWRCB [7]: •





Track 1: Reduce the intake flow rate at each power-generating unit to a level that can be attained with a closed-cycle evaporative cooling system. A minimum of 93% reduction is required compared to the design intake flow rate. Track 2: If compliance with track 1 is not feasible, reduce the impingement mortality and entrainment for the facility as a whole to 90% of track 1 reductions, using operational or structural controls, or both. Alternatively, a plant can comply by shutting down.

The original regulatory compliance dates ranged from 2010 to 2024. In 2011, LADWP obtained a consent from the state to delay compliance for its three units until 2029. Several California generating companies contested the policy in court, but a settlement was reached in the fall of 2014, leading the compliance of some plants to be pushed back and the SWRCB agreeing to several specific implementation constraints for four facilities. The SWRCB requested the owners of each generating facility to state whether they proposed to follow track 1 or track 2 or to shut down. In initial implementation plans, no facility owner proposed track 1. Most of the owners abandoned plans to pursue track 2 and announced plant retirement plans. The policy required plant owners to submit details of their plans to comply with the new regulations. In 2013, the San Onofre Nuclear Generating Station

Figure 3.11 Example of a thermoelectric power plant in California using OTC, part of the fleet affected by California’s once-through cooling policies.

Conclusions

57

Figure 3.12 The expected progress in the compliance to California’s once-through cooling policies plan based on plant retirements and the power plant owners’ proposed dates for compliance. (Data from: California State Water Resources Control Board [7].)

(SONGS) was permanently retired. Figure 3.12 shows the expected progress in the compliance to the OTC plan based on plant retirements and the power plant owners’ proposed dates for compliance. The retirement of some power plants, especially SONGS, is responsible for the compliance occurring more quickly than what the SWRCB policy had called for. In 2014, the EPA issued its own OTC regulations that were not as stringent as those enacted in California.

Conclusions Thermoelectric power plants require a sustainable, abundant, and predictable source of water. Power plants’ use of water depends on the type of cooling that is employed. Once-through cooling has the highest dependency on water availability. Plants with recirculating cooling systems have water withdrawals of 20–50 times less than once-through cooling, but they consume all the water they withdraw, and it must be replenished. The increasing application of recirculating cooling systems paired with freshwater conservation measures over the last 60 years has reduced the water withdrawals per unit of electric power (in milliwatt hours) generated by a factor of three since 1950 to about 20,000 gallons/MWh in 2000. Dry cooling using aircooled condensers or hybrid systems using parallel dry and wet condensing loops can further reduce the water used for cooling. Thermoelectric power plants will increasingly compete with demands for freshwater from domestic, commercial, agricultural, and other sectors. Despite the inherent uncertainty of droughts, private entities, governments, and research institutions

58

Effect of Droughts on Thermoelectric Power Plants

are taking action to further understand them and to reduce their impacts on power plants. However, with the recent increase in the use of gas and the retirement of coal and nuclear plants, reductions in water withdrawals should continue in the future. Nevertheless, current and future water-related environmental regulations will continue to challenge power plant operations. Therefore, there will be increasing pressure to retire existing thermoelectric plants with once-through cooling. Case History: Drought of 2011 in Texas

Texas experienced an extreme drought in 2011 that was the worst on record. Statewide mean precipitation was 47% lower in 2011 than in 2010, representing only 40% of the long-term mean (1896–2011), the lowest annual precipitation since record-keeping began in 1896. This was accompanied with up to 100 days of temperatures higher than 38°C (100°F) resulting in historically low water power plant reservoir levels accentuated by increased reservoir evaporation (14% higher in 2011 compared to 2010). The matter was worsened by increased water use by other sectors, with 45% higher water consumption for irrigation and 32% higher for the municipal sector in 2011 than in 2010 [9]. The drought raised electricity demand by 6%. The increase in thermoelectric generation, which accounted for about 87% of the total generation mix, resulted in an increase cooling water demand by about 9%. Record peak electricity demand in early August 2011 was 4% higher than the previous record. Although electricity supplies were generally sufficient to meet the increased demand, ERCOT shed 1,500 MW of interruptible load on August 4 to avoid imposing rolling blackouts after record peak electricity demands on August 1–3 (68,300 MW).

References [1] [2]

[3] [4] [5] [6]

[7]

[8]

Maupin, M. A., et al., “Estimated Use of Water in the United States in 2010,” U.S. Geological Survey Circular 1405, NO. 1405, 2014. U.S. Energy Information Administration (EIA), Monthly Energy Review, DOE/EIA0035(2014/11). Projections: AEO2015 National Energy Modeling System, run REF2015. D021915A, 2014. Vine, G., Cooling Water Issues and Opportunities at U.S. Nuclear Power Plants, INL/ EXT-10-20208, Idaho National Laboratory (INL), Idaho Falls, ID 2010. World Nuclear Organization, “Cooling Power Plants,” 2015. http://www.world-nuclear .org/information-library/current-and-future-generation/cooling-power-plants.aspx, 2017. EPRI, “Economic Evaluation of Alternative Cooling Technologies,” Report No. 1024805, 2012. DOE/NETL, “Water Requirements for Existing and Emerging Thermoelectric Plant Technologies,” DOE/NETL-402/080108, http://www.netl.doe.gov/energy-analyses/pubs/ Water%20Benefits%20Primer_09_02_08.pdf, 2008. California State Water Resources Control Board (SWRCB), “Ocean Standards—CWA §316(B) Regulation: Cooling Water Intake Structures Once-Through Cooling Water Policy—Official Policy Documentation,” 2016. Scanlon, B. R., I. Duncan, and R. C. Reedy, “Drought and the Water–Energy Nexus in Texas,” https://www.naseo.org/Data/Sites/1/media/1748-9326_8_4_045033.pdf, 2013.

Selected Bibliography

59

Selected Bibliography Birkinshaw, K, et al., “Comparison of Alternate Cooling Technologies for California Power Plants Economic, Environmental, and Other Tradeoffs,” Technical report, California Energy Commission, Electric Power Research Institute, 2002. California State Lands Commission, “Resolution by the California State Lands Commission Regarding Once-Through Cooling in California Power Plants,” http://www.energy.ca.gov/ siting/documents/2006-04-13 SLC PROPOSED COOLING.PDF, 2006. Clayton, M., et al., “Model of Implementing Advanced Power Plant Cooling Technologies to Mitigate Water Management Challenges in Texas River Basins,” ASME 2010 International Mechanical Engineering Congress and Exposition, American Society of Mechanical Engineers, 2010. DiFilippo, M., and J. Maulbetsch, “Use of Degraded Water Sources as Cooling Water in Power Plants,” Technical Report 1005359, Electric Power Research Institute, California Energy Commission, 2003. Eaton, J., “Record Heat, Drought Pose Problems for U.S. Electric Power,” http://news .nationalgeographic.com/news/energy/2012/08/120817-record-heat-drought-poseproblems-for-electric-power-grid/, 2012. Electric Power Research Institute, “Comparison of Alternate Cooling Technologies for U.S. Power Plants: Economic, Environmental, and Other Tradeoffs”. Technical report, 2004. Kimmell, T. A., and J. Veil, “Impact of Drought on U.S. Steam Electric Power Plant Cooling Water Intakes and Related Water Resources Management Issues,” Technical report, National Energy Technology Laboratory, 2009. Lee, M., “Evaluation of Reclaimed Water for Cooling in Coal-Fired Power Plants of North Carolina”, Master’s Thesis, Duke University, 2012. Roy, S. M., et al., “A Survey of Water Use and Sustainability in the United States with a Focus on Power Generation,” Technical Report 1005474, Electric Power Research Institute, 2003. Smart, A., and A. Aspinall, “Water and the Electricity Generation Industry: Implications of Use,” Technical Report, National Water Commission of Australia, 2009.

CHAPTER 4

The California Heat Wave of 2006 and the Failure of Distribution Transformers Introduction Chapter 3 addresses the effect of heat waves on power generation, energy demand, and power markets. This chapter discusses their effect on distribution systems, and mainly distribution transformers. Throughout the United States, the period between June 15 and July 27, 2006, set new temperature records and electrical peak demand records across the nation. California saw an extraordinary magnitude and duration of high temperatures as well as humidity, creating record electric demand usage. The actual temperatures in California were three standard deviations above the weighted maximum average temperatures in the CAISO-controlled area. For example, Sacramento recorded 11 consecutive days above 37.8°C (100°F) temperatures, and Woodland Hills reached 48.3°C (119°F). Though a number of temperature records were subsequently broken in 2014 and 2015, 2006 is of particular significance from a technical point of view. In California, a heat wave over one particular weekend in July 2006 led to an elevated number of distribution transformer failures that affected roughly two million residential customers statewide. That heat wave had several unique characteristics that contributed directly to the elevated failure of distribution transformers. First, there was a peak load coincidence in all the service areas of all the three California investor-owned utilities (IOUs): Pacific Gas and Electric (PG&E), Southern California Edison (SCE), and San Diego Gas & Electric (SDG&E). This had never happened before. Second, the heat wave started on a Thursday and peaked on Saturday in southern California and on Sunday in northern California, and the heat did not start to subside until the beginning of the following week. The significance of this fact is that it suggests that residential and retail demand drove the peak loads, rather than industrial loads. It is also the reason that the distribution system and the distribution transformers saw the brunt of the effects of the heat wave. Third, this heat wave had a combination of warm daytime temperatures and warm nighttime temperatures, preventing the distribution transformers from cooling down sufficiently during the night, consequently putting stress on the equipment and ultimately causing some equipment failures.

61

62

The California Heat Wave of 2006 and the Failure of Distribution Transformers

Impact on the California Power System Distribution System Event

The 2006 heat wave mostly impacted the distribution systems. It resulted in higher than normal transformer failure rates at all the California utilities. Other transformers only tripped, and the crews were able to restore service without replacing them. Figure 4.1 shows the number of distribution transformers that failed and were replaced at PG&E, SCE, and the Los Angeles Department of Water and Power (LADWP). For reference, the annual failure rate for small distribution transformers is in the range of 0.5–1.0% per year. In IEEE standard 493-2007 (“IEEE Recommended Practice for the Design of Reliable Industrial and Commercial Power Systems”— also known as the “IEEE Gold Book” [1]), the IEEE gives a value a failure rate of 0.5–0.6% per year for transformers from 300 to 10,000 kVA based on a 1983 survey done by the IEEE. In a paper published in 1991 examining lightning-related failures on a distribution system in an area of high lightning activity [2], Parish cited an overall annual failure rate of 0.79% of distribution transformers. Within this failure rate, between 0.177% and 0.572% was linked to lightning incidents, leaving a failure rate of between 0.2% and 0.6% due to other causes. The failure rate of the distribution transformers at the California utilities during the heat wave were over half of the respective annual failure rates. At one utility, in fact, there were more distribution failures in that heat wave than would typically occur in a whole year. Case in point, Figure 4.2 shows the monthly failures of distribution transformers for one of the effected California utilities. Notice the elevated relative number of transformer failures during the heat wave of 2006 (as well as a subsequent heat wave in 2007) relative to the other months. The actual number of the failures are not shown on purpose in Figure 4.2.

Figure 4.1 Distribution transformer at the three California utilities failed during the heat wave of 2006 at very high rates in comparison to annual rates.

Transmission and Generation Systems Behaviors During the Heat Wave

Figure 4.2

63

Relative monthly transformer failures at one of the California utilities.

The percentages of distribution transformers that failed compared to the distribution transformer fleet sizes were actually minimal, as seen in Figure 4.1. However, the number of residential customers that were affected in one fashion or another was high from the tripping or failure of the transformers serving roughly two million customers statewide. (Distribution transformers in the United States are widely dispersed with each transformer serving relatively few residential customers, typically three to 12.) Because the events were unexpected, California utilities had to deal with the challenge of not having sufficient crews to deal with all the distribution transformer issues during the peak of the heat wave. The outages were concentrated on the lowest voltages of the distribution systems, where the customers are actually served. In contrast, no outages were recorded in stations serving industrial customers. The large number of outages in California prompted the CPUC and the California Energy Commission (CEC) to hold a hearing on the heat wave and to work with the California electric utilities to improve their electric service reliability. [3].

Transmission and Generation Systems Behaviors During the Heat Wave All in all, the grid performed very well. The transmission systems in California were operating at peak loads, but there were no major overloads and no congestions. Notably, the AC Pacific Intertie, which delivers cheap hydroelectric power from Oregon to California, was limited to about 4,000 MW loop flows. There were few voltage problems in northern California and a few transmission system outages, though the largest was driven by lightning strikes, not the overloads downstream caused by the heat wave. Three transmission incidents resulted in sustained outages to customers affecting about 10,000 customers, which was minimal compared to

64

The California Heat Wave of 2006 and the Failure of Distribution Transformers

the two million customers affected by the distribution transformer issues on the distribution system. On the generation side, there was a number of thermal generation outages during the period in the western part of the United States. One of the Colstrip coal power plant units (778-MW) tripped, came back a few hours later, and went out again. Six control areas in the Northwest power pool, including Canada, went into some level of emergency status, all the way up to level three in one region. The hydroelectric generation production in northern California, as well as the Northwest, were at good levels compared to other years.

Failure of Distribution Transformers During Heat Waves Under normal loading conditions, and in the absence of outside stressors (such as through-faults and lightning), the failure rate of distribution transformers is expected to increase with age. The failure rate exhibits different characteristics dependent on many variables, such as manufacturer, design, and vintage. In some cases, the failure rate increases steadily over time, while in others the failure rate may exhibit a nonlinear (even exponential) growth. In some other cases, the failure rate may exhibit an S-shaped curve, similar to other pieces of equipment. Additionally, it can be shown that for a large installed base of distribution transformers (where meaningful statistics can be collected), the high impact failure levels are caused by transformers of intermediate age (ages 25–40 years), not from old transformers (50 years of service life and older). The number of failures peaks around years 35–40. Thereafter, even though the failure rate keeps increasing every year, the number of remaining units that this rate applies to becomes smaller due to replacement for load growth or modernization of the grid. To understand the reason for distribution transformer failures, their loadings and failure modes have to be well understood. The rest of this chapter is dedicated to this. We will start with a brief discussion on the rating of the distribution transformer and then move to its loading and how it unfences its aging.

Rating Practices of Distribution Transformers in the United States

Conventional distribution transformer application practices tend to base kVA rating selection solely on the expected peak load demand. Distribution transformers in North America are routinely applied so that the peak estimated load is above the rated transformer capacity. A fixed overload factor, typically 100% to 140% of rating, is commonly used. The percent peak overload is based on the peak demand in kVA divided by the full nameplate rating of the transformer. Knowledge of Actual Loading and Failure Mechanisms of Distribution Transformers

Actual loading of distribution transformers has generally been a topic that has received relatively little attention in the past. Accurate loading estimation of

Hot Spot and Top Oil Temperatures During Heat Waves

65

distribution transformers involves a large number of variables: time of the day; day of the week; customer type (commercial, industrial, residential); transformer load factor; temperature; and voltage. Obtaining such data on an individual transformer basis has been a challenge because they have not been monitored through supervisory control and data acquisition (SCADA) systems, as is the case with critical substation transformers. Today, smart grid technologies and ground-based weather station technologies can greatly assist in determining transformer temperatures and current loading and are a great help in condition assessments needed to predict failures before they happen. Smart grid technologies can be used for the management of insulation degradation, which is necessary to manage transformer aging and hence to maintain a reasonable life expectancy for the transformer. On the other hand, failures of distribution transformers were not thoroughly investigated in the past. Large utilities have tens or even hundreds of thousands of them, and it has been simply more cost-effective to replace a failed transformer without investigating why it failed through the rigorous failure root cause analysis that larger transformer failures typically have. Without an external stimulus, and assuming normal loading conditions, certain elements in the distribution transformer, such as rubber and synthetic gaskets and seals and insulation, deteriorate over time from the manufacturing date, whether the unit is installed or kept in inventory in an equipment yard. In some cases, the deterioration that would occur due to time alone is accelerated by the stresses caused by putting the equipment in service. Hardening of gaskets and seal and paper insulation will occur at a faster rate when a transformer is operating (since the heat generated by electrical losses will accelerate the deterioration processes). Yet these are normal operating conditions. In a few situations, putting a unit in service will reduce the rate of chronological deterioration. For example, energizing a transformer creates a low level of heating (due to no-load losses) that dries some moisture in the unit. Moisture is big cause of failures in transformers. Certain types of deterioration occur only, or primarily, due to the use or operation of the distribution transformer and are proportional to the time or the cumulative level of use in service, not the chronological time. During prolonged heat waves, the distribution transformer becomes more vulnerable to failure due to the limitations on the temperatures within the transformer when the load exceeds expectations. High temperatures are responsible for insulation degradation and even failure of the transformer.

Hot Spot and Top Oil Temperatures During Heat Waves The load on a transformer cannot be increased indefinitely without causing premature aging of transformer’s insulation, which is directly influenced by the temperatures within the transformer. The most intensive aging process in a transformer appears at the point of the highest insulation temperature, known as the hot-spot winding temperature. The hot-spot winding temperature has been the principal factor in determining transformer life (aging) due to loading and is defined as the sum of the temperature of the cooling medium (oil), the average temperature rise of the copper, and the hottest-spot allowance. The value of the hot-spot temperature during a transformer loading is not only important for the thermal aging but, along

66

The California Heat Wave of 2006 and the Failure of Distribution Transformers

Figure 4.3 Examples of winding faults in transformer that failed during heat waves.

with the top oil temperature, must not exceed prescribed limits in order to avoid immediate internal transformer faults and failure of the transformer, such as those shown in Figure 4.3. If a number of dispersed transformers exceed these conditions, they will fail suddenly, which is what happened during the 2006 heat wave. A large number of distribution transformers serving residential loads saw excessive loading in the presence of high ambient temperatures and solar heating. Additionally, the nighttime temperatures were high during the heat wave of 20061 so the transformers did not cool off at night. This was the case in most of the affected areas in northern and southern California, and equipment, such as distribution transformers, was not able to cool down sufficiently during the night, putting stress on the equipment and ultimately causing some equipment failures.

1

In addition to daytime temperatures being high, the nighttime temperatures were also high. Places like Stockton, where the normal evening low is 16.7°C (62°F), the low during the heat wave was 27.8°C (82°F). Fresno recorded nighttime temperatures of 32.2°C (90°F) and above. About half of the recording stations of NOAA recorded the warmest overnight lows ever recorded. The combination of warm daytime temperatures and warm nighttime temperatures led to warm daily average temperatures. Even at the start of the heat wave, and before the temperatures started soaring, the average temperature for all the PG&E’s service area was 32.7°C (91°F). This was the hottest average temperature since 1949, the year tracking began.

Formulation of Transformer Loss of Life Based on IEEE C57.91-1995

67

Estimating Remaining Life of Transformer The absolute temperature upon which insulation aging is dependent is the sum of the load-caused temperature rise, the ambient temperature, and any solar heating. In the United States, the IEEE Guide for Loading Mineral-Oil-Immersed Transformers and Step-Voltage Regulators, IEEE Standard C57.91-1995, is used to estimate the remaining life of transformers. C57.91 has two thermal models for transformers [4]. A classical model, referred to as the Clause 7 or top oil model, has been used with good success for over 80 years. C57.91 also has a more detailed model in its Annex G. The Annex-G model, also known as the bottom oil mode, was intended to account for the more complex dynamics of the oil temperature within winding ducts and along the winding height, which is more applicable for the larger substation transformers rather than distribution transformers. The notable environmental conditions that are not properly addressed in IEEE C57.91 are air-flow, corrosion, soil resistivity, solar heating, ambient temperature variations, and load cycles. Outside the United States (e.g., in Europe, Asia, and Africa), the International Electrotechnical Commission Standard Power Transformers—Part 7: Loading Guide for Oil-Immersed Power Transformers, IEC 60076-7 is used to estimate the remaining life of transformers [5]. The two standards are similar in a number of areas, but they differ in others. The differences between the two yield an appreciable difference with regard to the transformer loss of life. The term loss of life refers to the rate of transformer lifetime loss associated with a particular loading (heat and temperature) level for the equipment. This is mainly due to the fact that loss of life according to the IEEE equals 180,000 hours, and in the IEC standard, the total loss of life is not defined, but it is usually mentioned that the transformer loss of life is 30 years.

Formulation of Transformer Loss of Life Based on IEEE C57.91-1995 Per IEEE C57.91 Clause-7, the ambient temperature and the transformer current loading are the two most critical variable inputs in the calculation of the transformer hotspot and loss of life. Table 4.1, extracted from Table 3.7 of IEEE C57.91-1995 illustrates the needed increase or decrease from rated kVA for other than average daily ambient of 30°C. Loading on the basis of ambient temperature with the loads permitted in Table 4.1 will give approximately the same life expectancy as if transformers were operated at nameplate rating and standard ambient temperatures over the same period. Table 4.1 implies that the ambient temperature characteristics significantly impact the transformer insulation life. Thus the life expectancy of a transformer installed in a desert climate is considerably shorter than a transformer installed in a coastal climate under certain operating conditions. It also implies that in the summer, or in heat waves, when transformers run at higher ambient temperatures, the insulation degrades rapidly, and the transformer life could be shortened substantially. For distribution transformers, for every 1°C ambient temperature increase (from the standard 30°C) the transformer will lose 1.5% of its loading capability. IEEE Standard C57.91-1995 estimates the per-unit loss of life in transformers under normal conditions (nameplate conditions and specified overload) by (4.1)

68

The California Heat Wave of 2006 and the Failure of Distribution Transformers Table 4.1 IEEE C57.91 1995 Transformer Cooling (Percentage)

Decrease of Load (Percentage) /°C Higher than 30°C

Decrease of Load /°C Lower than 30°C

Self-cooled

1.5

1.0

Forced-air-cooled

1.0

0.75

Forced-oil, air-water-cooled

1.0

0.75

and (4.2). This estimation is based on experimental evidence that indicated that the relation of insulation deterioration of the transformer winding paper insulation (cellulose) follows an adaption of the Arrhenius reaction rate theory. In (4.1), the reference hot spot temperature varies depending upon whether or not the transformer paper insulation is thermally upgraded and what temperature rise standard is applied. It is to be noted that the aging equations do not refer to an absolute life value, but instead to the relative aging rate. For example, the per-unit life (L) for a 65°C average winding temperature rise transformer standard transformer, with a hot spot temperature of 110°C is 1.0. 15,000

Per-Unit Life, L = 9.8 × 10−18 eTHot +273

(4.1)

From (4.1), one can then write an equation for the relative aging factor, FAA , for the transformer as in (4.2). FAA is greater than 1 when the hottest-spot temperature is greater than 110°C. This implies loss of life (from normal aging) in the transformer ⎡

Relative Aging Factor, FAA

15,000 ⎤

⎢39.16− ⎥ dL THot +273⎦ = = e⎣ dt

(4.2)

The equivalent aging of the transformer with respect to the reference temperature 110°C that will be consumed in a given time period (T) is then given in (4.3): Equivalent Aging, FEQA =

1 T

T

∫ FAA dt

(4.3)

0

It follows that the loss of life in hours can be calculated by multiplying FEQA and T (hrs) and the percentage loss of life can then be calculated as: % Loss-of-Life =

FEQA × T × 100 Normal Insulation Life

(4.4)

The application of the simple, approximate, approach to finding the transformer remainder of life for a transformer is as follows: • •

Assume an average current load and an average ambient temperature; Calculate the winding hot-spot temperature (for the given load and ambient temperature);

IEEE C57.91-1995 Clause 7 Thermal Model for Transformer Aging •

69

Calculate the IEEE C57.91-1995 loss of life in years based on the winding hot-spot temperature.

For the above equations, if the hottest spot on the distribution transformer winding is at a design rating of 110°C, then it is assumed the normal insulation life is 180,000 hours (20.5 years). Typically, the nominal life of a distribution transformer can be in excess of 30–40 years due to the fact that many transformers are operated well below nameplate capacity most of the time. Some residential distribution transformers in California are even older than 60 years. During the 2006 heat wave the failure rates showed a dependence on age, indicating that some mechanism related to aging is a contributing cause to the failures. Failure rates for young transformers, even less than 20 years old, however, were still as much as 25 times the average annual failure rate. The sudden failures of the young transformers were due to either misapplication or a temperature-related failure mechanism. The sudden failures of the distribution transformers then necessitate the need for more accurate aging estimation methods, such as those in the next section. Equations (4.1)–(4.5) show that even a slight variation between the assumed load (and hence the hot spot temperature) and the actual load can yield large differences in the aging of the transformer. If a given transformer is loaded near nameplate, a mere 6–8% error in the assumed load will either double or halve the estimated life expectancy.

IEEE C57.91-1995 Clause 7 Thermal Model for Transformer Aging Derivation of Hot Spot Temperature

This section presents the principal equations that are needed to calculate the temperatures within the transformer that drive the loss of life in a transformer to apply them to heat waves. The thermal mechanisms of a transformer are extremely complex and difficult to model. To reduce complexity, the transformer is analyzed as a lumped system, and several assumptions are made. The transformer is essentially reduced to two systems, the bulk oil and the winding, with an additional hot spot temperature located at the top of the winding. The oil temperature is presumed to be lowest at the bottom of the winding. As the oil rises upward along the winding, the oil adjacent to the winding is heated at a constant rate. Therefore, the oil temperature is assumed to increase linearly from the bottom of the winding to the top of the winding, with the highest oil temperature located at the top of the winding. At a rated load, the winding temperature distribution is assumed to be higher than the oil temperature distribution by a constant value, ∆θ w, and thus parallel to the oil temperature distribution. Due to stray flux concentration near the top of the winding of the transformer, a further increase in temperature, the hot spot temperature, is located at the top of the winding. This hot spot temperature represents the hottest temperature endured by the insulation and therefore the highest aging rate. The C57.91 Clause 7, top oil method, relates the steady-state oil temperature rises to the total losses by a power function. The steady-state winding rises are related

70

The California Heat Wave of 2006 and the Failure of Distribution Transformers

to the winding current also by a power function. The following symbols are used throughout the section and are listed here for the sake of clarity: • • • •

• • • • • • • • • • • • • • • •

HS refers to the transformer hot spot temperature; TO refers to transformer top oil temperature; WCC is the weight of the transformer core and coils (kilograms); W Tank is the weight of the transformer tank and fittings in contact with the oil (kilograms); V Fluid is the volume of oil (L) in the transformer; τ O is the oil thermal time constant (min.); τ w is the winding time constant (min.); t is the time (min.); ∆t is the calculation time step (min.), t 2 = t 1 + ∆t; ∆θ TO is the top oil rise over ambient temperature (°C); ∆qHS is the hot spot rise over the top oil temperature (°C); PNL is the no load loss (watts); PLL is the load loss (watts); P T is the total loss (watts); K is the load (per unit of the nameplate rating); R is the ratio of load loss to no-load loss at the nameplate rating; m is the winding temperature rise exponent; n is the oil temperature rise exponent; qHS is the hot spot temperature (degrees Celsius); qA is the ambient temperature (degrees Celsius).

The subscripts used are defined as follows: • • •

R indicates a rated quantity; i indicates an initial quantity; U indicates an ultimate or steady-state quantity.

The values of the above variables are dependent on the characteristics of each transformer; however, the winding thermal time constant is always in the order of minutes while the oil thermal time constant is in the order of hours. The other variables are transformer-specific; for example, for a 37.5-kVA and 65°C winding temperature rise transformer, PNL = 80, PLL = 410, P T = 490, θ TO,R = 54.60 °C, n = 1.25, and m = 0.8. Calculation Procedure

The first step in calculating thermal response is to calculate the bulk top-oil time constant.

tO,R =

Cxfr ⋅ ΔqTO,R P T ,R

(4.5)

IEEE C57.91-1995 Clause 7 Thermal Model for Transformer Aging

71

Table 4.2 Specific Heat of Some Transfer Components Material

Specific Heat (W-min/lbs-C)

Copper

0.05

Steel

0.06

Oil

14.6

The thermal capacity, Cxfr, is the combined thermal capacity y of all transformer components in contact with the bulk oil. This includes the core, windings, tank and fittings, and the oil itself. Beginning with the following specific heat for each component material, the combined thermal capacity can be calculated by combining the specific heats of the various component materials with the component weights. However, the components are not at a uniform temperature. The oil temperature varies from the bottom of the tank to the top. Examples of the specific heat for the components are given in Table 4.2. The thermal capacity, C xfr, then equals: Cxfr = 0.06 × WCC + 0.04 × WTank + 1.33 × VFluid

(4.6)

At top oil temperatures other than rated, the time constant must be corrected as follows:

tO = tO,R

⎛ ΔqTO,U ⎞ ⎛ ΔqTO,i ⎞ ⎜⎜ ⎟⎟ − ⎜⎜ ⎟⎟ ⎝ ΔqTO,R ⎠ ⎝ ΔqTO,R ⎠ 1

1

(4.7)

⎛ ΔqTO,U ⎞n ⎛ ΔqTO,i ⎞n ⎜⎜ ⎟⎟ − ⎜⎜ ⎟⎟ ⎝ ΔqTO,R ⎠ ⎝ ΔqTO,R ⎠

The next step is to calculate initial temperature based upon the assumption that the load prior to the calculation period was constant long enough for the temperatures to reach their steady-state limits. This assumption is reasonable if the load is fairly constant for a period of time prior to the overload equal to two to three times the oil thermal time constant. ΔqTO,i

⎡ ( K 2R + 1) ⎤n ⎥ = ΔqTO,R ⎢ i ⎢⎣ ( R + 1) ⎥⎦

ΔqHS,i = ΔqHS,R ⋅ Ki2m

(4.8)

(4.9)

The next step is to calculate the transient temperatures based on the oil time constant calculated above in (4.7), the user-determined winding time constant, load, losses, and initial and ultimate temperature rises. The top oil and the hot-spot rise over top oil, at time t 2 , are given by:

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The California Heat Wave of 2006 and the Failure of Distribution Transformers

ΔqTO,U

⎡ ( K 2 R + 1) ⎤n ⎥ = ΔqTO,R ⎢ U ⎢⎣ ( R + 1) ⎥⎦

(4.10)

The top oil rise at time t 2 then becomes

(

ΔqTO,2 = ΔqTO,U − ΔqTO,1

)

Δt ⎛ − ⎞ tO ⎟ ⎜ + ΔqTO,1 ⋅ 1− e ⎟ ⎜ ⎠ ⎝

(4.11)

The hot-spot rise over top oil at time t 2 is given by the following: ΔqHS,U = ΔqHS,R ⋅ KU2m

(

ΔqHS,2 = ΔqHS,U − ΔqHS,1

)

Δt ⎞ ⎛ − tW ⎟ ⎜ + ΔqHS,1 ⋅ 1− e ⎟ ⎜ ⎠ ⎝

(4.12)

(4.13)

Then the hot-spot temperature at time t is given by: qHS,2 = qA,2 + ΔqTO,2 + ΔqHS,2

(4.14)

The above calculation is repeated for each time step of the overload period, with the initial temperature rises equal to the temperature rises from the previous time step over a designated period of time to calculate the cumulative loss of life. Without the effect of the solar heating of the transformer that is presented in the next section, (4.14) is computed by summing the ambient temperature, the delta of the top-oil temperature, and the delta of the hot-spot temperature. The final hotspot temperature is then inserted into the loss-of-life equation (4.4). This iterative process is repeated 24 times for both the final hot-spot temperature and the percent loss-of-life calculation. The 24-hour cycle is then repeated 365 times or a full calendar year to attain the annual percent loss of life, if needed. Solar Heating of the Pole-Top Distribution Transformer

A very critical environmental effect that is not factored into IEEE C57.91 is the effect of solar heating on the transformer hot spot and its loss of life. The effect of the Sun shining on a fully exposed pole-top distribution transformer can be quite significant. A distribution transformer in California is exposed to 622 hours of full sun per year. Modifying the aging factor equation listed in IEEE C57.91 to account for the solar-heating factor is significant in areas that have mostly sunny and clear skies. This will be presented in this section. Accurate accounting of the effects of solar heating is complicated by the potential for potential shading of the Sun from nearby objects, changing cloud cover, and

IEEE C57.91-1995 Clause 7 Thermal Model for Transformer Aging

73

indirect solar insolation from ground reflectance. However, a conservative assessment of potential impacts can be made by assuming that there is no shading from adjacent objects (open field conditions) and assuming full sun without accounting for cloud cover. Where historical cloud cover data is available, this can be taken into account. The methodology used here follows the methodology used for the effect of solar heating on bare overhead conductors in the IEEE Standard for Calculating the Current-Temperature of Bare Overhead Conductors, IEEE 738-2006 [6]. This methodology is applied to pole-top transformers. A similar methodology can be derived for pad-mount transformers. In these calculations the following symbols are used: • • • • • • • • • • • •

N: Day of the year; Φ: Latitude, Degrees; δ S: Solar Declination, degrees; ω : ω = 15*(T – 12), degrees; T: Time, hours; D: Tank diameter, meters; H: Transformer tank height, meters; HS : Solar altitude, degrees; ID: Solar radiation, watts; α s: Absorptivity of tank surface, no units; Z S : Solar azimuth, degrees; Qsolar: Solar heat gain, watts.

The first step in this calculation is to calculate the solar declination. The solar declination is a measure of how many degrees north (positive) or south (negative) of the equator that the Sun is when viewed from the center of the Earth. This varies from approximately +23.50 degrees (north) in June to –23.50 degrees (south) in December. The solar declination is calculated as follows and is applied conservatively here for distribution transformers. ⎡ ⎛ 284 + N ⎞⎤ Solar Declination, dS = 23.4 ⋅ sin ⎢360 ⎜ ⎟⎥ ⎝ 365 ⎠⎦ ⎣

(4.15)

where N is the day of the year. Next comes the calculations of the solar altitude, H S , and solar azimuth angles, Z S . Solar altitude is the angle up from the horizon. Zero degrees’ altitude means exactly on the local horizon of the transformer, and 90 degrees is straight up from the transformer. Azimuth is the angle along the horizon, with zero degrees corresponding to north, and increasing in a clockwise fashion. Thus, 90 degrees is east, 180 degrees is south, and 270 degrees is west. Using these two angles, one can describe the apparent position of the Sun with respect to the transformer. One more coordinate is needed for this calculation, and that is the latitude where the transformer is location. The latitude specifies the north–south position of a point

74

The California Heat Wave of 2006 and the Failure of Distribution Transformers

on the Earth’s surface. Latitude is an angle that ranges from 0° at the Equator to 90° (north or south) at the poles. From the above, the solar altitude, H S , and solar azimuth, Z S , are calculated as follows: HS = arcsin ⎡⎣sin(j) ⋅ sin ( dS ) + cos(j) ⋅ cos ( dS ) ⋅ cos(w)⎤⎦

(4.16)

ZS = C + arctan(c)

(4.17)

where j

is the latitude of at the location of the transformer.

ω

is the hour angle of the Sun, ω = 15*(T – 12).

and c =

sin(w) sin(j)cos(w) − cos(j)tan ( dS )

(4.18)

The constant C is selected from Table 4.3. With the solar altitude calculated, the total direct heat flux received at sea level can be estimated by the following empirical equation [6]: ID ≈ A + B ⋅ HS + C ⋅ HS2 + D ⋅ HS3 + E ⋅ HS4 + F ⋅ HS5 + G ⋅ HS6

(4.19)

This total heat flux is then used to calculate the total heat gain from solar heating of the transformer at a given time of day. For pole-top transformers, a simple model can be used that assumes a cylindrical tank with no radiators, tubes, or fins. This is reasonable for a couple of reasons. First, the presence of radiators, tubes, or fins is generally confined to larger transformers, where the ratio of losses to surface area is higher (meaning solar insolation comprises a smaller portion of total heat input and therefore has a lower effect on oil temperatures). Second, in terms of solar insolation area, the additional radiators or fins represent only a modest increase in insolation area. The effort to include radiators or fins in the solar model will yield little in terms of accuracy but will require considerable effort. Note that angle of the solar radiation striking the tank surface is not a function of solar azimuth. It is assumed here that that tank is a cylinder with the axis

Table 4.3 Selection of the Constant C as a Function of Hour Angle, ω C Hour Angle, ω

χ≥0

χ10 mm), moderate (6–10 mm), light (1–6 mm), and very light ( 4;

K2 is a term that adjusts corona loss for rain rate RR (millimeters per hour) and is given as: K2= 10 log (RR/1.676), for RR ≤ 3.6 mm/hr; K2= 3.3 + 3.5 log (RR/3.6), for RR > 3.6 mm/hr. A

is altitude, meters.

To calculate corona loss in kilowatts per kilometer, the antilog of P (decibels) must be performed, or P=

f ⋅ 10PdB/10 60

(8.10)

The total loss for a line in kilowatts per kilometer is the summation of the loss from all the conductor bundles. Example of the Use of the BPA for Calculating Corona Losses: 230-kV Line

To illustrate the use of the BPA equation for corona losses, consider the 230-kV line used earlier, and find the corona loss for a 100-km line section. The solution follows:

n E max Ec f A

is the number of subconductors in the bundle; is the ma¡ximum surface gradient, kilovolts per centimeter; is the corona onset gradient calculated using (8.1) with m = 1; is the frequency, hertz; is the altitude, meters.

Estimating Corona Losses

165



Phase conductor diameter: 3.51 cm;



GMD =



Single conductor implies n = 1; Rated current = 1,200A; From the previous calculations, Es = 12.91 kV/cm; Rate of rain (RR) = 10 mm/hr; Line altitude = 300m; Line length = 100 km; K1 = 13 since n = 1; RR= 10 mm/hr; K2 = 3.3 + 3.5 log (RR/3.6), for RR > 3.6 mm/hr; K2 = 3.3 + 3.5 log (10/3.6) = 4.853.

• • • • • • • • •

3

Dab Dbc Dca =

3

6.5 × 6.5 × 13 = 8.19m

Equation (8.8) would then become: ⎛ E ⎞ ⎛ d ⎞ ⎛ n ⎞ A PdB = 14.2 + 65 ⋅ log ⎜ s ⎟ + 40 ⋅ log ⎜ ⎟ + K1 ⋅ log ⎜ ⎟ + K2 + 300 18.8 4 3.51 ⎠ ⎝ ⎠ ⎝ ⎝ ⎠ ⎛ 12.91 ⎞ ⎛ 3.51 ⎞ ⎛ 1 ⎞ 300 PdB = 14.2 + 65 ⋅ log ⎜ ⎟ + 40 ⋅ log ⎜ ⎟ + 13 ⋅ log ⎜ ⎟ + 4.853 + 300 ⎝ 18.8 ⎠ ⎝ 3.51 ⎠ ⎝ 4 ⎠ PdB = 1.6 The loss in kilowatts per kilometer then becomes f ⋅ 10PdB/10 60 60 ⋅ 101.6/10 =1.44 kW/km P= 60

P=

With the approximate calculations shown above, the corona loss for each phase of the 100-km section of the line is then 144 kW (or 432 kW for the three phase line). Example of the Use of the BPA for Calculating Corona Losses:345-kV line

Estimate the corona loss for the 345-kV line at sea level. Assume a rainfall rate of 10 mm/hr and an average surface gradient on the six subcontractors of 13 kV/cm. Estimate the corona losses in watts per meter with the BPA method. 1. Corona loss at sea level: Solution A = 0m; d = 3.42 cm; Rate of rain (RR) = 10 mm/hr; K1 = 13 since n = 2; K2 = 3.3 + 3.5 log (RR/3.6), for RR > 3.6 mm/hr; K2 = 3.3 + 3.5 log (10/3.6) = 4.853; Es = 13 kV/cm.

166

Transmission Line Corona Losses

Equation (8.8) would then yield for each of the six subconductors: ⎛ E ⎞ ⎛ d ⎞ ⎛ n ⎞ A PdB = 14.2 + 65 ⋅ log ⎜ s ⎟ + 40 ⋅ log ⎜ ⎟ + K1 ⋅ log ⎜ ⎟ + K2 + 300 18.8 4 3.51 ⎝ ⎠ ⎠ ⎝ ⎝ ⎠ ⎛ 13.44 ⎞ ⎛ 3.42 ⎞ ⎛ 2 ⎞ 0 PdB = 14.2 + 65 ⋅ log ⎜ = 5.21 dB ⎟ + 40 ⋅ log ⎜ ⎟ + 13 ⋅ log ⎜ ⎟ + 4.853 + 300 ⎝ 18.8 ⎠ ⎝ 3.51 ⎠ ⎝ 4 ⎠ The loss in kilowatts per kilometer then becomes f ⋅ 10PdB/10 60 60 ⋅ 105.21/10 ≈ 3.3 W/m P= 60

P=

Total for the line: P = 6 ×3.3 ≈ 20 W/m Sensitivity Analysis of Corona Loss Under Heavy Rain

Figures 8.15 and 8.16 show the corona losses under heavy rain conditions as a function of the conductor diameter and altitude above sea level, for a 10-mm/hr rainfall rate, for the 230-kV line that was studied earlier.

Figure 8.15 diameter.

Illustration of the decrease of the corona loss with an increase in phase conductor

Voltage Considerations and Corona Losses

Figure 8.16

167

Illustration of the increase of the corona loss with an increase in altitude.

To illustrate the dependence of the corona loss on the conductor size, American Electric Power (AEP) published in [12] some interesting statistics comparing resistive and corona losses for its 765-kV lines in normal weather for 1,000 MW of power. Figure 8.17 presents a summary of this data. These estimated yearly average corona losses at sea level based on normal weather consist of 20% rain, 2% snow, and 78% fair-weather conditions. Studying Figure 8.17 reveals two interesting facts. First, in the 765-kV configurations that were contrasted, the corona losses are of the same order of magnitude of the resistive losses and even exceed them in some cases. The second is that the corona losses are more heavily weighted with fair weather; thus corona losses under rain and snow would definitely be higher.

Voltage Considerations and Corona Losses Transmission Line Voltage Upgrades

Conductor corona is often the limiting factor in how high the voltage can be increased on an overhead transmission line slated for a voltage upgrade. Higher voltage yields higher surface electric fields. Higher conductor surface electric fields mean increased corona losses, audible noise, and EMI (radio noise and television interference). Appropriate criteria must therefore be established to assess the corona performance

168

Transmission Line Corona Losses

Figure 8.17 Comparison of corona and resistive losses for 765-kV lines. (Data from: [12].)

and to arrive at a maximum possible operating voltage for the existing conductor from a corona standpoint. Replacement of standard hardware with corona-free hardware may be necessary for operation at the higher field levels. The same concerns apply for line tower compaction as the surface electric field increases for the same line voltage as conductors are brought closer together. As a result, a compact 138-kV line tower design may have an electric field at the conductor surface that is more typical of a traditional 345-kV line. The increased conductor surface electric field associated with compact lines results in increased hardware and insulator corona. This implies that corona-free hardware, typically for EHV and UHV lines, may have to be specified for the HV compact lines. Voltage Reduction as a Means of Reducing Corona Losses

Voltage is the main driver of corona, so theoretically by incrementally lowering voltage, corona loss can be reduced during severe weather conditions of precipitation. A reduction in the AC voltage will lower the corona and associated losses at the expense of increasing resistance losses because the line current has to increase to keep the transfer level. However, during conditions of light load and heavy corona loss, lowering the AC line voltage may reduce corona loss more than the system losses increase. In modern control centers corona losses due to extreme weather, especially, hoarfrost, can be taken into account in optimizing the voltage level if enough data is available to forecast corona losses from the weather parameters.

Voltage Considerations and Corona Losses

169

Reduction of Corona Losses

As stated before, corona losses of transmission lines increase with voltage. One way to reduce the losses for a given line voltage is then to raise corona onset voltage. This can be done by increasing the diameter of the conductors and, to a lesser degree, by increasing the spacing between the conductors—a decision that is always weighed against economical considerations. Use of bundled, or multiple, conductors consisting of several smaller conductors of a comparatively small diameter held in place by insulating spacers will reduce the corona effects as a bundle conductor is equivalent to a single conductor of a large diameter. Three conductors are used per bundle typically on a 500-kV line; 750-kV lines have four conductors in a bundle. Six to eight conductors will probably will be required for 1,150-kV lines, and the overall diameter of the bundle may reach 1–1.5m. Corona losses, however, are only reduced by the use of bundle conductors; they cannot be completely eliminated. Corona rings, toroidal electrodes, on-station bushings, and on-transmission line insulators are often used to lower the surface gradient. Figure 8.18 illustrates the use of corona rings on station equipment and conductor bundles. Although these devices are used to prevent corona on conductors, it is possible for them to experience corona themselves due to their surface gradients. Design of these types of hardware is typically achieved using analytical methods if their corona onset characteristics are known.

Figure 8.18

Corona rings.

170

Transmission Line Corona Losses

Case Histories Measurements of Corona Losses Under Hoarfrost: Finland

Transmission line corona losses under hoarfrost conditions were tested at Tampere University of Technology, Finland, in 1996 [13]. To be able to form hoarfrost on the conductors and to control the climate parameters, the test cage was installed in the climate room, and the electric fields were calibrated against the average surface field strengths in a real 400-kV transmission line middle phase. Relatively thin hoarfrost thicknesses were used in these tests. Figure 8.19 summarizes the results of a number of tests. As can be seen from this, the corona loss with hoarfrost was two orders of magnitude higher than the corona loss for dry clean conductors even though the thickness of the hoarfrost was very thin. Other tests have shown that the corona losses were very sensitive to changes in the hoarfrost thickness. Those tests have also shown that the corona losses are highly influenced by the ambient temperature. As the temperature increased, the elevated levels of hoarfrost changed into a thinner and harder form, like small icicles, with corona losses due to the sharp edges formed. A two-conductor bundle had up to five times higher corona losses than the three-conductor bundle with the relatively thin hoarfrosts used in the tests Corona Losses due to Extreme Contamination

A newly commissioned line in an African country had very little power at the receiving end when the generators at the sending side were at full capacity. An investigation

Figure 8.19 Summary of corona losses measured with a two-conductor bundle at two different ambient temperatures under hoarfrost. (Data from: [13].)

Exercise

171

showed that this was due to very high corona losses due to the fact that the line conductors were covered with grease that led to the deposition of insect and vegetal matter along the length of the line. Such conditions, or the presence of snow or ice on the conductors, greatly reduce the corona onset gradient of the conductors and give rise to very high levels of corona losses.

Conclusions Corona is one of the major factors in transmission line design for EHV transmission lines (345- to 765-kV). It is not usually a design issue for power lines rated at 230-kV and lower. The most important factor influencing generation of corona is the electric field distribution in the vicinity of the conductor surface, and thus the calculation of the electric field gradient on the surface of HV conductors. It is theoretically possible to determine the conductor surface gradient at which onset of corona occurs, known as the corona onset gradient, and transmission lines, whether AC or DC, are designed so that their operating maximum stays below their corresponding critical corona onset levels. Though a small percentage of the total line losses generally are attributable to corona, their consequence is increased under foul-weather conditions for long transmission lines as corona loss can increase by several orders of magnitude and can become significant. Precipitation, such as snow, ice, and hoarfrost, has a significant influence on corona onset and corona performance. Other weather conditions affecting corona losses comprise a broad range of factors including ambient temperature, pressure and humidity, and wind (velocity and direction). Annual corona energy loss, which depends on the magnitude and variation of corona loss during different weather conditions occurring in a year, has an impact on the economic choice of conductors. During conditions of light load and heavy corona loss, lowering the AC line voltage may reduce corona loss more than the system losses increase. Theoretically, this approach can be used to reduce corona losses in extreme cases, such as when hoarfrost is present. Finally, accurate calculations for corona on practical transmission lines can be complicated by the nonuniformity of the conductor surface caused by conductor stranding, sag of the line, surface contaminants, and raindrops. Therefore, this chapter offers some simplified, but accurate, methods to calculate the surface electric field, corona onset voltage, and the corona losses.

Exercise Estimate the expected corona loss for the 345-kV line of Figure 8.8, but with Chukar conductors (diameter 4.07 cm). Assume the line is 1,830m, with a rainfall rate of 10 mm/hr. Estimate the corona losses in watts per meter with the BPA method. Solution

First we have to estimate the surface gradients for the six conductors. This is done using (8.2) with the following parameters.

172

Transmission Line Corona Losses

d = 4.07 cm; Rate of rain (RR) = 10 mm/hr; GMD = 1,260 cm; s = 45.72 cm. ⎛ 2 ⋅ rc ⎞ kVLL ⎜1 + ⎟ s ⎠ ⎝ Es = = ⎛ GMD ⎞ 2 3 ⋅ rc ⋅ ln ⎜ ⎟ ⎝ rc s ⎠

⎛ 4.07 ⎞ 345 ⎜1 + ⎟ 45.72 ⎠ ⎝ = 11.8 kV/cm ⎞ ⎛ 1260 3 × 4.07 × ln ⎜ ⎟ ⎝ 2.035 45.72 ⎠

With the surface gradient defined, we proceed to the calculation of the corona loss using the BPA corona loss expression, (8.8) ⎛ E ⎞ ⎛ d ⎞ ⎛ n ⎞ A PdB = 14.2 + 65 ⋅ log ⎜ s ⎟ + 40 ⋅ log ⎜ ⎟ + K1 ⋅ log ⎜ ⎟ + K2 + 300 ⎝ 4 ⎠ ⎝ 3.51 ⎠ ⎝ 18.8 ⎠ where PdB is the corona loss per line in decibels; n

is the number of subconductors in the conductor bundle;

d

is the diameter of the subconductor in cm;

Es

is the average bundle gradient in kV/cm;

K1

= 13 for n ≤ 4 and = 19 for n > 4;

K2 is a term that adjusts corona loss for rain rate RR in millimeters per hour and is given as: K2= 10 log (RR/1.676), for RR ≤ 3.6 mm/hr; K2= 3.3 + 3.5 log (RR/3.6), for RR > 3.6 mm/hr. A

is altitude in meters (m);

K1

= 13 since n = 2;

K2 = 3.3 + 3.5 log (RR/3.6), for RR > 3.6 mm/hr; K2 = 3.3 + 3.5 log (10/3.6) = 4.853; Es

= 11.8 kV/cm

A

= 1,830m.

⎛ 11.8 ⎞ ⎛ 4.07 ⎞ ⎛ 2 ⎞ 1830 PdB = 14.2 + 65⋅ log ⎜ = 10.67 ⎟ + 40 ⋅ log ⎜ ⎟ +13⋅ log ⎜ ⎟ + 4.853+ 300 ⎝ 18.8 ⎠ ⎝ 3.51 ⎠ ⎝ 4 ⎠ The loss in kilowatts per kilometer then becomes

Selected Bibliography

173

f ⋅ 10PdB/10 60 60 ⋅ 1010.67 /10 ≈12 W/m P= 60

P=

Total for the line = 12 × 6 = 96 W/m.

References Peek, F.W., Dielectric Phenomena in High-Voltage Engineering, McGraw-Hill, 1929. Mombello, E., and P. S. Maruvada, “Measurement and Analysis of Corona Losses Generated by Heavily Contaminated Conductors,” International Symposium on HighVoltage Engineering (ISH), Bangalore, India, 2001. [3] Kolcio, N., et al., “Radio-Influence and Corona-Loss Aspects of AEP 765-kV Lines,” IEEE Transactions on Power Apparatus and Systems PAS-88, No. 9, 1343, 1969. [4] Peterson, W. S., J. S Carrol, and B. Cozzens, “Corona Loss Measurements for the Design of Transmission Lines to Operate at Voltages Between 200 kV and 300 kV,” AIEE Transactions, Vol. 52. 1933, pp. 55–63. [5] Wagner, C. F. et al., “Corona Considerations on High-Voltage Lines and Design Features of Tidd 500 kV Lines,” AIEE Transactions on Power Apparatus and Systems, 1948, pp. 8–15. [6] Gary, C. H., and M. R. Moreau, L’effet Couronne en Tension Alternative, Eyrolles, Paris, 1976, pp. 379–381. [7] Trinh, N. G., and P. S. Maruvada, “A Method of Predicting the Corona Performance of Conductor Bundles Based on Cage Test Results,” IEEE Transactions on Power Apparatus and Systems, Vol. PAS-96, 1977, pp. 312–325. [8] EPRI, Transmission Line Reference Book—345 kV and Above (Second Edition), Palo Alto, California: Electric Power Research Institute, 1982. [9] Chartier, V. L., “Empirical Expressions for Calculating High Voltage Transmission Line Corona Phenomena,” First Annual Seminar Technical Program for Professional Engineers, Bonneville Power Administration (BPA), 1983. [10] Robertson, L. M., et al., “Leadville High-Altitude Extra-High-Voltage Test Project: Part II-Corona Loss Investigations,” AIEE Transactions on Power Apparatus and Systems, December, 1961, pp. 725–732. [11] Chartier, V. L., D. F. Shankle, and N. Kolcio, “The Apple Grove 750-kV Project: Statistical Analysis of Radio Influence and Corona-Loss Performance of Conductors at 775 kV,” IEEE Transactions on Power Apparatus and Systems, Vol. PAS-89, May/June 1970, pp. 867–881. [12] American Electric Power, Transmission Facts, http://web.ecs.baylor.edu/faculty/grady/_13_ EE392J_2_Spring11_AEP_Transmission_Facts.pdf. [13] Lahti, K., M. Lahtinen, and K. Nousiainen, “Transmission Line Corona Losses under Hoarfrost Conditions,” IEEE Transactions on Power Delivery, Vol. 12, No. 2, April 1997. [1] [2]

Selected Bibliography Anderson, J. G., et al., “Corona Loss Characterization of EHV Transmission Lines Based on Project EHV Research,” IEEE Transactions on Power Apparatus and Systems, Vol. PAS-85, No. 12, December 1966, pp. 1196–1212.

174

Transmission Line Corona Losses

IEEE, “A Survey of Methods for Calculating Transmission Line Conductor Surface Voltage Gradients: IEEE Corona and Field Effects Subcommittee Report,” IEEE Transactions on Power Apparatus and Systems, 1979. EPRI, AC Transmission Line Reference Book—200 kV and Above (Third Edition), Palo Alto, CA: Electric Power Research Institute, Report 1011974, 2004. Edison Electric Institute, EHV Transmission Line Reference Book, New York, 1968. Keitley, R., D. F. Oakshott, and G. C. Stringfellow, “Corona Power Loss and Radio Interference Measurements at 400 kV and 750 kV on the Leatherhead Experimental Line,” CIGRÉ Report 419, 1966. Larsson, N., and K. Ponni, “Measurements of Corona Losses due to Hoarfrost and Winter Precipitation on 400 kV Operating Lines in Finland with Special Reference to Estimation of Hoarfrost Corona Losses Based on Meteorological Data,” CIGRÉ report 409, 1964.

CHAPTER 9

Effect of High Winds on the Power Delivery System

Introduction This chapter, and Chapters 10 and 11, are related, and should be read in succession. In many regions around the globe, transmission towers and distribution poles have failed due to the reaction of high-intensity winds (HIWs) exceeding their designs. In fact, HIWs are the most common power line failures in parts of the United States, Canada, Brazil, Argentina, South Africa, New Zealand, and Australia. They have been blamed by many of the utility organizations in these countries for up to 80–90% of all weather-related failures of towers and poles. Defining HIWs

There are several different definitions for HIWs; some are based on the threshold wind speed, while others are based on the localized effects of such storms. CIGRÉ WG B2.16 [1] defines HIWs as “those having velocities exceeding 45 m/s or those likely to cause structural damage to property.” As this definition is quite encompassing, it includes several types of wind storms associated with large-scale tropical and extratropical storms (e.g., hurricanes, cyclones, and typhoons), gales, and thunderstorms. The advantage of this definition is that the threshold wind speed parameter is a precise criterion for the identification of HIWs. The other definition comes from the American Society of Civil Engineers (ASCE). ASCE limits HIWs to tornadoes, microbursts, and downbursts due to the narrow-fronted characteristic of those winds in their definition of HIW. This book uses the first definition of HIWs; thus we will refer to wind storms having velocities exceeding 45 m/s as being as HIW storms. Thus, our definition of HIW would include what some may refer to as linear winds or straight-line winds (such as derechos) as well as circular winds or spiraling winds, such as tornadoes and cyclones. The main body of this chapter focuses on case histories of the impacts of HIW on the power system, mainly the power delivery side, as these are the parts that occupy the largest footprint of power systems, and hence are most vulnerable to wind storms. Chapter 10 covers the impact of such high winds on wind turbines. The appendixes to this chapter detail the types of HIWs and their origins and characterizations, providing examples of HIWs as well as some salient case histories. Lessons learned from those storms are also presented.

175

176

Effect of High Winds on the Power Delivery System

Chapter 11 discusses structural hardening of the power system against HIWs as well as against the flooding that often accompanies HIW events such as hurricanes. Chapter 12 discusses Superstorm Sandy of 2012, which resulted in power outages in 24 states—some extended—and the lessons learned from it. Types of HIWs That Threaten the Power System Infrastructure Case History: The June 2012 Derecho in the Ohio Valley and Mid-Atlantic United States

On June 29, 2012, a derecho formed and moved across Illinois through the Ohio Valley and Mid-Atlantic states, traveling 600 miles in about 10 hours [2]. During that event, the National Weather Service received over 800 preliminary thunderstorm wind reports with peak wind gusts ranging from 130 to 160 km/hr (80–100 mph) [3]. By comparison, a category 1 hurricane is characterized by sustained wind speeds in the range of 120–150 km/hr (74–95 mph), while a tropical storm is characterized by wind speeds ranging from 63 to 118 km/hr (39–73 mph). However, hurricanes and tropical storms typically deliver the most severe wind speeds to coastal areas, and lose considerable strength as they move inland, while this derecho delivered direct, straight-line winds, to a wide swath of the Ohio Valley and the Mid-Atlantic. The morning after the event, electric utilities, cooperatives, and municipalities reported approximately 4.2 million customers without power across 11 states and the District of Columbia. Restoration efforts in many cases took seven to 10 days. New storms impacted the region during the second day of restoration, causing additional outages, and setting back restoration. Two days after the highest outage report, utilities had restored power to only 45 percent of affected customers. A series of severe thunderstorms passed through the Ohio Valley region after the derecho struck on June 29, 2012, causing new outages, and slowing restoration efforts. Appalachian Power in Virginia and West Virginia was the hardest hit utility with four additional storms following the derecho. These storms occurred on July 1, 3, 5, and 8, creating about 100,000 new outages. In addition to these subsequent storms, the region was hit with extreme temperatures that complicated restoration efforts for many utilities. Several utilities reported taking extra measures, such as distributing water and energy drinks and supplying ice to utility crews to combat the heat. Some utility workers were treated for heat-related injuries as they worked to restore power amid 38°C (100°F) temperatures between July 2 and July 6. The additional storms and the high temperatures hindered restoration efforts and lengthened the time it took to restore power to customers. The damaging winds and wind gusts experienced during this storm brought down trees in the impacted area, causing physical damage to electric power infrastructure, including transmission and distribution lines, substations, and utility poles. Utilities received little advanced warning of this storm, a factor that reduced preparation time and that may have lengthened restoration time. By contrast, utilities received warnings days in advance of Superstorm Sandy and Hurricanes Ike and Irene. The advance notices allowed utilities to stage repair crews and call center operations and arrange in advance for assistance from regions outside the expected impact areas.

Damage to Transmission and Distribution Infrastructures from Tornadoes

177

Damage to Transmission and Distribution Infrastructures from Tornadoes Most HIW line failure events include low-intensity tornadoes and downdraft winds. The front width of such storms is small when compared to typical HV line span lengths. Thus, the effects of the wind on conductors should not be significant. Accordingly, to prepare for the wind range of EF2 tornados (50–70 m/s), steel transmission towers can be reinforced at a reasonable cost. Statistics in the United States show that about 97% of observed tornadoes are of intensity EF2, or less, with 67 m/s (150 mph) gusty winds or less. Therefore, transmission towers in most places—towers designed for gusts of 50–70 m/s supplemented with additional failure containment mechanisms—are likely to sustain less damage from an EF3 tornado. Examples of Tornado Damage on the Power Grid

In May of 2010, several tornadoes struck large areas of Oklahoma, Kansas, Missouri, and Arkansas. Over 60 tornadoes, some large and multiple-vortex in nature, affected large parts of Oklahoma and adjacent parts of southern Kansas and Missouri, with the most destructive tornadoes causing severe damage in the southern suburbs of the Oklahoma City metropolitan area. The tornadoes were responsible for extensive damage to parts of the power system. Figure 9.1 illustrates the damage to a transmission tower toppled by one of the tornadoes.

Figure 9.1 Workmen are dismantling a 100-m- (300-ft-) tall transmission downed by a tornado that struck the county on May 10, 2010, Cleveland County, OK. (Source: FEMA.)

178

Effect of High Winds on the Power Delivery System

Case Histories of Some Tornado Damage in the United States

Late in the afternoon of Sunday, May 22, 2011, a catastrophic EF5-rated multiplevortex tornado struck Joplin, Missouri. This was part of a larger late-May tornado outbreak and reached a maximum width of 1.6 km (1 mile) during its path through the southern part of the city. It rapidly intensified and tracked eastward across the city. This was the third major tornado to strike Joplin since May 1971. Figure 9.2 shows the damage inflected on a substation in Joplin by 90-m/s (320-km/hr, 200mph) winds on May 22, 2011. On the afternoon of May 20, 2013, an intense EF5 tornado struck Moore, Oklahoma, and adjacent areas, with peak winds estimated at 340 km/h (210 mph), killing 24 people and causing substantial damage to transmission lines. The tornado was part of a larger weather system that had produced several other tornadoes across the Great Plains over the previous two days. Figure 9.3 is an aerial view of the damage to transmission line structures by the May 20, 2013, tornado that touched down in Moore. Failure Analysis from HIWs

Damage to overhead lines in regions exposed to HIWs depends on several factors such as the following: • • •



The frequency of occurrence and characteristics of the HIW events; The design standards to which the lines have been built; The location of overhead lines within a region and their degree of exposure to severe weather events; The age profile and extent of the overhead networks.

Figure 9.2

Substation destruction by 90-m/s (320-km/hr, 200-mph) winds. (Source: FEMA.)

Damage to Transmission and Distribution Infrastructures from Tornadoes

Figure 9.3

179

Transmission tower toppled by a tornado. (Source: FEMA.)

HIW events can be very localized, and each can be different in character, as noted earlier in the chapter. Hence, the selection of proper design for wind speeds is one of the most difficult and important tasks in the design and evaluation process. Most transmission systems in most countries were developed many years ago, based on deterministic criteria: fixed loads (e.g., using a 50-year return period) and safety factors. Where reliability concepts were applied, line and structure design were based on synoptic winds derived from statistics of extremes from annual maxima. For example, in the western United States the highest 50-year, 3-second design wind at 10m (33 ft) was set to 40 m/s (90 mph), or 27 m/s (60 mph) one-hour winds. Experience has shown though that reliance on the 50-year return period wind speed values can sometimes lead to inefficient designs for certain HIWs. To illustrate this, consider the results of a risk model developed by Schwarzkopf and Rosso [4] for the return period of tornadoes and downbursts given a certain wind speed. The results of this model that was developed for a 650-km line in Argentina are shown in Figure 9.4. Based on Figure 9.4, the downburst recorded on August 1, 1983, at the U.S. Andrews Air Force, which was recorded at 70 m/s or 252 km/h (157 mph), would have had a return period more than 7,000 years using this model. On the other hand, the derecho of 2012, with speeds up to 161 km/hr (100 mph), would have had a return period from this figure of about 50 years. Today, probabilistic approaches are becoming more popular in design structures. These are based on numerical models based on previous HIW collected data and observed failure modes of damaged transmission structures. Damage to Utility Systems from Hurricanes

Hurricanes cause damage to utility systems in two categories: damage due to the high winds and damage due to the flooding associated with the rains or storm surges. In discussing these effects, we should note that many parts of utility systems are not designed to survive major hurricanes. The utility industry is seeking ways to harden their systems so that they will incur less damage from hurricanes and thus more quickly restore their services.

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Effect of High Winds on the Power Delivery System

Figure 9.4

Statistics of downbursts and tornadoes traversing a line section in Argentina.

Damage Due to High Winds from Hurricanes

When a cyclone makes landfall, it may have a range of potential high wind gusts, with a high level of turbulence due to terrain effects. While peak wind gusts may be able to engulf a full transmission line span and support structures, the potential for impact from airborne debris from vegetation and other objects on aerial conductors is usually higher than the impact of the winds on the transmission or distribution lines themselves once wind velocities exceed 50 m/s. Thus, many utilities report that most damage to their overhead lines is due to vegetation, even entire trees and other structures, blowing over into power lines. The airborne debris results in broken poles (or their elements such as crossarms and insulators), and conductors and leaning poles. See Chapter 11 for more on this topic. Damage Due to Heavy Rains and Storm Surge

Extensive amounts of rain are associated with hurricanes, and thus, there is a high risk of flooding. Coastal regions are particularly vulnerable to damage from flooding from a tropical cyclone as compared to inland regions because cyclones typically weaken rapidly over land where they are cut off from their primary energy source, the ocean. However, heavy rains can still cause significant flooding inland. Freshwater flooding from heavy rains associated with hurricanes can produce heavy

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damage and can occur hundreds of kilometers away from a cyclone center, even when the storm does not make landfall. Storm Surge

With hurricanes, there is a risk of storm surges. When a hurricane approaches land, it blows onto shore a wall of water whose magnitude is highly dependent on the tides; this is called a storm surge.1 Storm surges, can reach several meters high above the normal levels, can flood coastal communities, the severity of which is affected by the shallowness and orientation of the water body relative to storm path. Storm surges can produce extensive coastal flooding up to 40 km (25 mi) from the coastline A storm surge tends to pick up large amounts of sand and debris and can bury, contaminate, and dislodge pad-mounted equipment and flood underground cables, vaults, and exposed manholes. When a storm surge floods coastal areas’ power systems, salt water can immerse pad-mounted and subsurface electrical equipment in the storm surge area. When the storm surge recedes, a salt residue may be left on insulators, bushings, and other components. This contamination can result in an immediate failure when the equipment is energized, or it can result in a future failure when the contamination is exposed to moisture. Typically, live-front equipment (those with exposed and easily accessible equipment energized equipment, such as busbars) performs worse when flooded compared to dead-front equipment (which does not have energized parts exposed). Submersible equipment contained in waterproof enclosures is considered resistant from flooding from hurricanes.

Wind Force on Transmission Lines’ Aerial Conductors Severe HIWs impact aerial conductors in two ways: • •

Direct wind loading applied to aerial conductor spans; Consequential airborne debris impact from vegetation or building materials.

Because of their spatial extent, direct wind loading is the most important aspect when considering design to mitigate the damaging effects of HIWs. This is influenced by the conductor diameter, the angle of incidence of the wind, and the distance between towers (span length). No allowance for debris loading is normally included on major transmission lines, even though in major wind storms of this type it is common for tree canopies from tropical forests to be stripped and impact spans of conductors. The consequential airborne debris impact from vegetation or building materials is a localized effect during extreme events and will normally result in overload and failure of conductors and the complete structural system. The magnitude of associated loading is indeterminate and therefore not a normal design consideration. To minimize this risk, vegetation must be removed from areas within proximity to aerial conductors. 1 Worldwide, approximately 90 percent of all deaths in hurricanes are drownings in either storm surge or rainfall.

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Effect of High Winds on the Power Delivery System

Selected Case Histories This section revisits some HIW storm occurrences throughout the world that resulted in major damage to transmission and distribution lines structures or led to extended major impacts on the power grid. Each case history presents a synopsis of the windinflected damage from each event, along with lessons learned, including, where applicable, corrective and preventive actions taken after the storms. Damage to power lines from wind manifest itself in two ways: direct damage to the transmission or distribution line (and their components) and collateral damage sustained by the lines from the impact of airborne vegetation carried by the wind. Pacific DC Intertie 1989, United States

Description of the Event

In February 1989, wind storms, of undocumented speeds, damaged several towers of the Pacific DC Intertie (also called Path 65)2 (see Figure 9.5) and interrupted the transmission of power from the Pacific Northwest to the Los Angeles area. Event Toll •





Eight guyed towers, one self-supporting angle, and one self-supporting tangent3 (suspension) tower were destroyed by high winds. The 2,312-kcmil conductors and static wires in those 11 spans were too extensively damaged to be reused, requiring the installation of new conductors (16 km of power conductors and 8 km of static wire). The Owens-Gorge AC transmission line, which shares some of the right of way of the DC Intertie, also sustained structural damage to six of its towers. Its phase conductors (5 km in length) on seven spans were damaged and required replacement. The damage to the Owens Gorge line was caused primarily by the falling of the DC Intertie structures and conductors [5].

Lessons Learned

From 1990 to 1992, the DC Intertie line was upgraded by reguying, moving footings, and replacing defective hardware; see Figure 9.6. These upgrades have effectively prevented any further cascade-type failures, although isolated failures have still occurred but have been quickly restored by the utility crews.

2 The DC Intertie originates near the Columbia River at the Celilo Converter Station of Bonneville Power Administration’s grid outside The Dales, Oregon and is connected to the Sylmar Converter Station north of Los Angeles. It is owned by five utility companies and managed by LADWP. The DC Intertie can transmit power in either direction, but power flows mostly from north to south. Today this line carries about 3,100 MW of power. 3 See the chapter’s appendix for a description of the different types of transmission and distribution towers and poles.

Selected Case Histories

Figure 9.5

The Pacific DC Intertie (Path 65).

Figure 9.6 Graphic representation of a tangent tower of the Pacific Intertie tower with the modified guying.

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Effect of High Winds on the Power Delivery System

Figure 9.7

Actual tangent tower and footing of the Pacific Intertie after the strengthening measures.

345-kV Line Cascade, Nebraska, 1993 Description of the Event

A fast moving windstorm was responsible for a large cascade failure in a transmission line in Nebraska on July 8 and 9, 1993. The storm traversed northern Kansas, southern Nebraska, and western Iowa, creating a swath of damage nearly 160-kmwide and 800-km-long; see Figure 9.8. In Nebraska, the storm moved at an average speed of over 20 m/s (72 km/h, 45 mph) and produced straight-line wind damage in 43 of the 60 counties it encountered. Wind speeds of 27 to 32 m/s were common during the event. Thirteen recorded gusts exceeded 35 m/s, with the highest wind gust reported at 56 m/s, lasting from 20 to 30 minutes. At least five (F0, F1) tornadoes were also spawned by this storm. Event Toll

A large cascade failure initiated by HIW occurred on the 345-kV Grand IslandMcCool-Moore transmission line [built in 1969 and owned by the Nebraska Public Power District (NPPD)], causing the failure of 406 of its structures. The line was

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185

Figure 9.8 Wind reports exceeding 25 m/s During the windstorm of July 8 and 9, 1993, and the location of the location of the Grand Island-McCool-Moore transmission line cascade.

Figure 9.9

345-kV wood poles like the 406 towers that failed.

constructed with K-frame–type structures, consisting of two wood poles with a timber head frame and interior wood cross-bracing, similar in to Figure 9.9.4 General Failure Mechanism

When a tangent structure fails and drops out of position due to wind, the weight on the two adjacent structures can rise by about 50%, and the tension on the wires increase by as much as 200%. Shield wires tend to be able to approach the doubled tension more easily than do the phase conductors. With short spans, the wires cannot

4

The line had a ruling span of 281m (920 feet) and a conductor design tension (NESC Heavy load case) of 5,800 kg (12,800 pounds). The line had two overhead shield wires and a two-conductor bundle of Drake conductors. The pole heights ranged from 21m (70 ft) to 34m (110 ft). Conductors hung from 18-unit porcelain insulator strings.

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reach the ground and tensions can exceed 200%. This doubling of tension typically pulls the adjacent structures toward the structure that triggered the cascade, the trigger structure. If the adjacent structures break under the increased tension, this action creates a force pulling more structures. This continues until there is enough slack developed in the failed section. For this line, the winds blew on numerous structures, pushing tangent structure tops away from the wind, due to the flexibility of the structures, by over 1m at the top. The 3-m-long insulator strings on the conductor system made that system quite flexible and forgiving, while the shield wires were quite rigid. At about 34-m/s (123km/h, 76-mph) wind speeds, the stresses on the poles reached exceeded 350 kg/cm 2 (5,000 psi), causing structures to break near or at the ground line. Lessons Learned •



Lack of longitudinal strength: Wires of transmission lines keep transmission structures standing, on one hand, but when their tensions increase, they could also pull them down. This line failure, and other failures like it (long cascades), are in part, the result of the thinking that prevailed in the 1960s, when this line was built, assuming that when large and strong conductors were to be used there would be no need for tower designs to accommodate broken wire designs. According to Oswald et al. [6], the wires would be too strong to break negating the need for stronger transmission structures. Transmission lines have stored mechanical energy in them. The stored energy is in the form of longitudinal energy from wire tensions and vertical energy from the weight and position of materials. For tall transmission structures, and long spans, these can be enormous energies when released due to the height of the structures and the weights of wires and structures; it is necessary to design for these characteristics. Using larger conductors would require designing for higher longitudinal and vertical forces. (Lower voltage lines tend not to have the energy to propagate a failure to such dramatic proportions). Providing structural integrity at dead-end and angle structures: Preventing longitudinal failures requires a containment system to provide a safety net against catastrophic collapse and to prevent cascades. There is value in the employment of containment-capable structures at economic intervals in all lines whose sustained outage and replacement would be costly and/or not acceptable from the system reliability point of view. Angles (corners)5 are a natural location/opportunity for a containment structure. They are ideal sources of slack to relieve the tensions, since when they collapse, considerable additional amounts of wire can be fed into the adjacent spans reducing

5 Angle or corner structures are used where transmission line conductors change direction and need to be designed to withstand the forces placed on them by the change in direction. They are like tangent structures, using suspension insulators to attach the conductors and transfer wind, weight, and line angle loads to the structure. They also have a similarity to dead-end structures, using insulators in series with the conductors to bring wind, weight, and line angle loads directly to the structure.

Selected Case Histories

Figure 9.10

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Use of dead-end and angle towers.

the wire tension on them. Dead-end structures6 are the ultimate barriers to longitudinal tension imbalance. As there are very few dead-end and angle structures in a straight (or almost straight) transmission line relative to tangent structures in most lines, both kinds are natural places to strengthen to withstand and stop a cascade event; see Figure 9.10. Anatol, Lothar, and Martin Windstorms, Europe, December 1999

Description of the Event

In December 1999, Europe was hit by three fiercely intense extratropical cyclones7: Anatol, Lothar and Martin. Anatol, hit on December 3, Lothar, struck on December 26, and Martin and Lothar on December 27. Together the three storms brought much of Europe to a halt and killed more than 160 people. Lothar and Martin caused major damage in France, southern Germany, Italy, and Switzerland. Wind speeds exceeded 42 m/s (150 km/h, 94 mph), and in some areas speeds reached 50 m/s (216 km/h, 134 mph).

6

A dead-end structure is typically used where transmission line conductors turn at a wide angle or end. Compared to a tangent structure, a dead-end structure is designed to be stronger and often is a larger structure that can resist the full unbalanced tension that would occur if all conductors were removed from one face of the structure. Typically, insulators on a dead-end structure are in series with the conductors (horizontal) to bring wind, weight, and line angle loads directly to the structure. 7 Extratropical cyclones derive their energy from the horizontal temperature contrast—warm subtropical air masses opposite cold, polar ones—that exists in the mid latitudes and is greatest during the height of winter. Extratropical cyclones arise along such thermal boundaries when various local conditions in the upper-level jet stream become unstable and the contrasting air masses begin to interact. Instead of the familiar circular structure of tropical cyclones (e.g., hurricanes), extratropical cyclones have a more complex structure and generally develop two “fronts”: one where warm air overrides cold air to the northeast of the system’s center, and one where cold air wedges beneath warm air to the southwest. Some of the highest surface winds and heaviest precipitation usually occur along these fronts. When fully developed, the system exhibits a comma shape that can extend well over 1,000 km. The swath of an extratropical cyclone’s most damaging winds, however, is typically about 150–500 kilometers wide.

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Storm Toll •

Damage in Europe where the storms passed were estimated at €10 billion (1999). France received the brunt of the Lothar and Martin windstorms; see the paths of those two storms through France in Figure 9.11. Some of the impacts of these storms on France are listed as follows: – About 3.5 million utility household losing power; – Damaging of a quarter of the French HV transmission lines where 300 HV transmission towers were toppled leading to the outage of 38 400-kV and 81 225-kV lines; – Outage of 184 substations (63-kV to 90-kV and 225-kV to 400-kV). – French state utility EdF had to acquire nearly all the available portable power generators in Europe, even bringing in some from Canada.

Lessons Learned •

New transmission design criteria adapted including the following: Modifying the mechanical strength of the towers through new bracing; – Extending the geographical areas where higher design wind values are anticipated; – Specifying higher standard wind loading for other areas. Stocking of emergency line components; Establishing reciprocal assistance agreements with other European grid operators; Upgrading weak points on the network (including clearing stretches of forest where trees could fall on power lines and upgrading the mechanical strength of some towers); Installing anticascading measures every 10 spans to limit secondary failures. –

• •





French Government Intervention

Because of the damage to overhead systems from the 1999 storms, French regulators decided to follow a new policy of undergrounding significant parts of the French system to harden against severe weather conditions. The policy dictated that one

Figure 9.11

Paths of two of the three windstorms that hit France in December 1999.

Selected Case Histories

189

quarter of all new high 63-, 150-, and 225-kV lines would be constructed underground. All new distribution networks would be built underground. Other Case Histories Microburst, France, 1996

High winds moved on a 2-km wide strip only, with wind speeds of 116–179 km/h (72–111 mph). Nineteen guyed-steel towers of the high voltage direct current (HVDC) transmission line collapsed, causing a complete failure of the RadissonDorsey Transmission System, which was carrying 2,020 MW at the time. No cascading action occurred, and no customers were affected. Cyclone Heta, New Zealand, January 2004 Description of the Event and Events Toll

Severe tropical cyclone Heta was a powerful category 5 tropical cyclone that caused catastrophic damage to the islands of Tonga, Niue, and American Samoa during late December 2003 and early January 2004. In Zealand, on January 9, 2004, three towers of a 500-kV HVDC line collapsed under extreme winds exceeding 64 m/s (230 km/h, 243 mph) with a return period of such magnitude that was estimated at 1,300 years. HIW Storm on Brazil, June 2005 Description of the Event and Event Toll

A significant number of tower failures occurred in the south and southeast geographically narrow areas of Brazil including that of eight guyed towers and one self-supporting tower of the Itaipu Dam transmission system. Lessons Learned •



Records for HIWs need to be segregated from other windstorm records and processed independently. It is important to keep the granularity of wind speed data down to time frames in seconds, as it is misleading to average the wind speed of HIW over 10 minutes.

Erwin Wind Storm, Sweden, January 2005 Brief Description

Windstorm Erwin (also known as Gudrun) hit northern Europe from Ireland to Russia on January 7–9, 2005. Floods and powerful winds hit the region. The United Kingdom was severely hit as strong winds and floods caused widespread damage; however, the Nordic region was the most affected area. In Sweden, the gust wind speed reached 42 m/s (94 mph) at the southeast coast. The most severely affected area was a corridor going east between Ängelholm and Varberg, with gust wind speeds inland of 33 m/s (74 mph). Forest damage in Sweden was the worst recorded in recent history,8 and this caused disruption to power supplies, phone lines, and 8

More than 75,000,000m3 (2.6 × 109 cu ft) of trees were blown down in southern Sweden. This resulted in Sweden at the time having the world’s largest shortage of lumber.

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railway traffic. The storm also cut power to households in Norway and hampered oil production at three offshore fields. Event Toll •

• •





Over 500,000 homes lost power in the Nordic region. (Over 400,000 households lost power in Sweden, with 10,000 homes staying without power for three weeks [7].) Five nuclear power plants in Sweden were forced to close [7]. The storm caused significant damage in Sweden, where the forest industry suffered from over 250,000 damaged trees (three to four years of lumber production). In Sweden, numerous amounts of wooden poles from 400-V to 10-kV distribution lines failed. There was also extensive damage on 40- to 50-kV lines.

Lessons Learned Since it would have been cost-prohibitive to design towers and poles to withstand a windstorm such as Erwin, several preventive measures were agreed on, listed as follows: • •

• • •

Widening of corridors for the 40 to 50 kV distribution lines; Undergrounding in rural and forest areas and undergrounding links to customer premises; Standardizing electrical equipment for quick recovery; Installing emergency backup power at critical sites; Improving forecasts and communication regarding severe weather events.

Wind Storm, Kansas, August 2006 Description of the Event and Event Toll

In August 2006, Hays, Kansas experienced a windstorm that led to collapse of a 3.2-km stretch of wood transmission and distribution poles. Nearly all poles broke at the ground line. The transmission line that failed was originally designed in 1983 to the NESC heavy loading district criteria. It consisted of 21-m (70-ft) class 2 Douglas fir poles set 2.7m (9 ft) deep. Conductors were 477-kcmil ACSR phase conductors. The average span length was 118m (388 ft). Lessons Learned •



Localized weather effects can result in winds much stronger than those recorded at nearby weather stations. Possibilities for strengthening transmission and distribution lines for high wind conditions identified included the following: – Stronger or upgraded poles; – Shorter spans (and hence, lower poles); – Smaller conductors;

Selection of Salient Lessons Learned from Several Windstorm Events

– – – –

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Storm guying; Push braces; Less pole-mounted equipment and fewer third-party attachments; Aggressive tree removal around the transmission and distribution lines.

Selection of Salient Lessons Learned from Several Windstorm Events This section summarizes and categorizes lessons learned from several windstorms around the globe. Data Collection after the Storm •











Take immediate aerial photos and videos on-site before clearing the damaged structures after a major storm event. This could facilitate the assessment of the origin of direct failures from the windstorm and indirect failures caused by flying and fallen vegetation. It would allow designers to distinguish between the primary failures and the secondary failures, including the cascade failures. Collect all meteorological data available to analyze and to understand the storm event (type, origin, location or track, intensity, duration, and correspondence with forecast). Obtain detailed information needed to support failure investigations of the components during the wind storms. Perform failure analysis (observation on-site, tests on samples, and calculations). The analysis needs to determine the root causes of failures as well as any significant contributing factors to the failures. Such analysis and information can be used to better assess the benefits (and eventually costs) of potential hardening options. Compare actual damage with the engineering and construction standards to which the facilities were built. For automatic restoration on medium voltage lines, consider using advanced reclosers with automatic sectionalizing capacities that do not depend on communications to perform their function (operating in a preprogrammed way to restore supply and isolate the fault). This way the control room personnel are not overwhelmed with SCADA signals from medium-voltage (MV) faults, but when the storm is over, they can then use SCADA on these reclosers, after the crews have repaired the faulty section and normal sectionalizing is to be reestablished.

Design Considerations •

Some existing standards for transmission line wind, ice, and snow loadings and other structural design principles for designing transmission lines are still based on deterministic principles (safety factor or allowable stress), with loads derived on an empirical basis, or based on arbitrary historical values. Where reliability concepts are applied, some line and structure some designs

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are based on synoptic winds9 derived from statistics of extremes from annual maxima; however, in many regions of the world localized HIWs pose the greatest risk for failure of transmission lines. Design wind speed can be exceeded due to local topography (ridges and slopes). If the wind load was more than normal design load, wind speed (or ice loads) need to be reviewed based on more reliable statistical data. More recent designs since around 1985 have criteria that is focused on the following main weather-related loadings: – Extreme wind; – Extreme icing; – Wind and ice combined. In general, most recent design standards are based on an assessment of the relevant probability of exceedance or occurrence of some design properties where loads and strengths are recognized as random variables, knowing that the spatial variability of wind gusts could also be significant. With statistical data, designers can associate a value of wind or ice load for any selected climatic return period or reliability level. The design wind is typically chosen to have a probability of being exceeded of 3–5% during the economic life of the overhead line asset.

Upgrading and Retrofitting Existing Transmission Structures

It can be much more economical to introduce hardening to towers before they are built. Retrofitting existing towers could be much more expensive. Reference [8] indicates that the cost premium for designing 500-kV towers (guyed-V and doublecircuit lattice-type towers) from 161–242 km/h (100–155 mph) is less than 3% (mostly due to the increase in weight of the steel of new structures). Some existing lattice structures can be modified at a low cost by merely changing internal bracing members in the body. Upgrading steel lattice towers is relatively easy, by replacing or doubling steel angles. The buckling length of primary members can be reduced by the addition of secondary members. Wood poles may be replaced with concrete poles. Other timber products such as laminated wood are used. The total structural costs of new lines are usually in the range of 15–25% of overall final line expenditures. Considering higher design wind speeds would result in an overall project cost increase of less than 1–3%. Upgrading the design of steel lattice towers in general is relatively easy, by replacing or doubling steel angles. The buckling length of primary members can be reduced by the addition of secondary members. Wood poles may be replaced with concrete poles. Other timber products such as laminated wood systems may be used. Chapter 11 concentrates on the structural hardening of distribution systems.

9 Synoptic, also known as atmospheric boundary layer (ABL), winds occur due to large-scale (~1,000km) weather systems such as the high- and low-pressure regions seen on weather maps. The vertical profile of synoptic winds follows a logarithmic profile, with a rapid increase with height near the ground and an asymptotic maximum at high levels. In contrast, downburst winds reach a maximum close to the ground (< 100m) and then reduce with height.

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Lessons Learned from Cascade Failures

The following actions are prudent to prevent cascade failures: •

Increased meshing of lines: From the system operation viewpoint, the robustness of the network can be improved by better meshing and interconnection of lines. Placing several strategic lines in the same corridor must be avoided, especially in zones prone to bad weather events. – If possible, strategic lines should not be placed in the same corridor in zones prone to severe weather events. – Strategic lines must be built far away from each other, except when the environmental requirements dominate. For system operators, identification of strategic lines is fundamental. Intensify specific maintenance programs. Poor condition of the weakest elements sensitive to primary failures must be itemized systematically. Install anticascade towers and use technology such as load control devices; it is necessary to distinguish secondary failures from primary failures.







Striking a Balance between Hardening and Quick Restoration

It is important to strike a balance between line hardening on one hand and quick system restoration on the other hand. Hardening, in addition to the physical strengthening of structures, includes preventive measures that can be taken before a storm event, such as preparedness, stocking spare parts, and developing an emergency response plan. Corrective measures after an unexpected storm event include quick restoration of power and services, emergency supplies, and rebuilding. A quick system restoration after a storm covers many areas such as the following: • •

• • •

An emergency response plan; Identification of the resources, along with the organizational structure, required for power restoration in a specified time frame; Having adequate spare material stocks in the right places; Reciprocal assistance agreements from neighboring utilities; Regular classroom and field exercises to implement the emergency plan.

Firestorms Wildfires, or firestorms, another form of extreme weather, can be categorized similarly to wind storms and are of concern to electric utilities’ infrastructures. Wildfires may affect operational considerations for some generating stations. In the western United States and Canada, recent droughts through 2016 have led to the drying of large swaths of vegetation and contributed to catastrophic, geographically large wildfires. Firestorms, which sustain their own wind system, are created during wildfires, bushfires, and forest fires. Even though the transmission lines may not be affected by the fires directly, higher temperatures can reduce the efficiency and capacity of

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power lines and other power grid components, such as transformers, and can increase the risk of disruption to transmission lines. Soot from the fires near transmission lines and substations can also reduce the electrical resistance of the air, reducing the critical flashover voltage and thus increasing the risk of transmission line flashovers as well as arcing to other lines or to nearby vegetation. Other lasting effects from wildfires that can affect the energy system include increased soil erosion, risk of landslides, and changes in water quality through increased amounts of sediment, which could affect the quality of cooling water for power plants. The South African Advanced Fire Information System

South Africa is prone to wildfires. In 2002, in one day, Eskom had 35 line faults caused by fires that resulted in the loss of power supply to Cape Town due to the loss of two of the lines, 295-km-apart. During the 2004 fire season, the South African utility (Eskom) and the Council for Scientific and Industrial Research (CSIR) in South Africa developed the Advanced Fire Information System (AFIS), an information system to combat the problem of line faults resulting from wildfires. AFIS uses satellite data to detect active fires and then sends fire alerts to Eskom users for appropriate actions by the system operator or field personnel. Initially, AFIS had a simple set of tasks [9]: • • •





Alert users to the existence of fire events around the power infrastructure; Archive fire events; Allow access to this archive for Web-based query and retrieval of fire event information; Produce a fire detection alarm when a hot spot is observed by remote sensing instruments; Process hot spot information into mobile phone text alerts and send them to registered end users’ mobile phones. Subsequently, the information is archived into a database and served over the Web as a resource.

The satellite data came from the moderate resolution imaging spectroradiometer (MODIS) flying on NASA’s Terra and Aqua satellites. The early development of AFIS was dependent on proprietary software and tools. Since then, and with collaboration with NASA, the direction has changed into open-source software and open standards. AFIS became an integral part of Eskom’s transmission-line monitoring and management system providing staff with an estimated 5,000 alert messages per month during peak fire season. Several fire-induced line insulation flashovers have been prevented by early fire detection numerous times. In one notable sequence, access to text fire alerts resulted in more than 35 cases during two fire seasons (2005 and 2006) where outages were prevented. The system was also used for analyzing, timing, and improving Eskom’s vegetation management program. In 2010, CSIR upgraded AFIS to deliver information on locations of active fires in southern and east Africa in real time. AFIA II uses data that is available within 10 minutes after the satellite passes overhead. It enabled Eskom to set up

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predefined user profiles and receive alerts whenever fires burn within 1 km of its transmission lines, providing active fire location data and burnt area estimates from satellite images. It also integrated information on wind speed and direction from 130 automated weather stations every hour. The AIFS is now being expanded from South Africa to neighboring countries through the installation of stations in the other countries such as Kenya Ghana.

Case History: Fires in the San Diego Area

Two different wildfires scorched power systems infrastructure in SDG&E’s service territory and inflicted widespread damage in 2003 and 2007. In 2007, CAISO declared an emergency when, in two days, one wildfire caused the Southwest Power link transmission system to go out of service, and another fire caused two additional HV transmission lines to trip off-line. CAISO asked SDG&E and Southern California Edison to reduce electric load by a total of 500 MW and requested voluntary energy conservation in San Diego. Over the course of the week, the fires knocked more than two dozen transmission lines out of service, and only one 230-kilovolt transmission line was left to serve San Diego. Initially about 100,000 customers were without power, but nearly all customers were back in service within a couple of weeks. Damage throughout the county to SDG&E’s electricity infrastructure was high, De Luz to Descanso and South Poway to Julian. Similarly, SDG&E losses were high, with 20% of its distribution systems destroyed, more than 3,000 poles damaged or burnt, 640 km (400 mi) of electrical lines in need of replacement, and 17 transmission lines in need of rebuilding. Figure 9.12 shows an example of the wildfires that broke off near the U.S. – Mexican border during the Harris fire in 2007 in San Diego, California. Reference [10] lists some of the measures that have been taken by SDG&E following the 2006 fire storms. These include the following: •







More aggressive vegetation management and tree trimming programs through the creation of a detailed inspection and trim program that currently covers more than half a million trees within its service territory. Use of laser scanning technology to identify and correct potential problems on the 69-kV transmission systems. System changes implemented: – Means and plans to disable automatic recloser switches during such events; – Having 80 sectionalized distribution circuits in high-risk fire areas; – Installation of 93 anemometers to assess wind conditions on power lines. Other activities: – Staging crews during red flag warnings; – Tripping power lines when winds exceed design limits or field observers report hazards; – Establishing a new customer website with weather conditions and outage information; – Deployment of a new Sun Bird heavy-lift helicopter for fire response;

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Figure 9.12 Helicopters dropping fire retardant and water during the wildfires near the U.S.Mexican border during the 2007 San Diego Harris fire. (Source: FEMA.)



– –

Replacement of wood poles with steel in high-risk fire areas as well as raising the design limit of transmission lines to 137 km/h (85 mph); Creation of a company-wide community fire safety program; Hiring seasoned firefighting professionals and meteorologists.

SDG&E also created its own weather network that includes more than 170 weather stations providing real-time weather information in 10-minute intervals for making operating decisions. In 2014, SDG&E developed the Fire Risk Mitigation Initiative (FiRM) program, which uses the lessons learned from previous programs to evaluate the performance of its 300,000 overhead poles. Based on FiRM, SDG&E initiated programs to harden pole components (such as the conductors, insulators, and splices) to withstand winds up to 40 m/s (140 km/hr, 85 mph) to significantly reduce or eliminate sources of ignition from overhead lines. In addition, SDG&E started changing wood poles to steel poles. By 2016, SDG&E had replaced over 50 km (over 31 mi.) of conductors and over 2,300 wood poles. In 2016, it aimed to replace 1,500 poles. Creating a transmission system that uses redundant facilities to deliver remotely generated power can reduce vulnerability to likely increases in wildfires. Redundancy creates more than one delivery pathway for remote generation so that if any single transmission line is out of service due to fires, then there is an alternate means to deliver the power to load centers. Separating the various pathways of looped transmission networks so that they are not vulnerable to the same wildfire events further reduces vulnerability to wildfires.

Selected Bibliography

197

References [1]

International Council of Large Electric Systems (CIGRÉ), CIGRÉ WG B2.16., “Report on Current Practices Regarding Frequencies and Magnitude of HIWs,” 2004. [2] U.S. Department of Energy (US DOE), Office of Electricity Delivery and Energy Reliability, “A Review of Power Outages and Restoration Following the June 2012 Derecho, Infrastructure Security and Energy Restoration,” 2012. [3] National Oceanic and Atmospheric Administration (NOAA), “Severe Wind Event Storms Across the Midwest and Mid-Atlantic on June 29, 2012,” http://www.erh.noaa.gov/rnk/ events/2012/Jun29_derecho/summary.php, July 2012. [4] Schwarzkopf, M. L. A., and L. C. Rosso, “Severe Storms and Tornadoes in Argentina,” Proceedings of the Conference on Severe Local Storms, 1992. [5] Schweiner, R., et al., “Transmission Line Emergency Restoration Philosophy at Los Angeles Department of Water and Power,” Transmission and Distribution Construction, International Conference on Operation and Live-Line Maintenance, 2003. [6] Oswald, B., et al., “Investigative Summary of the July 1993 Nebraska Public Power District Grand Island—Moore 345 kV transmission line failure,” Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference, Chicago, IL, 1994. [7] Carpenter, G., “Windstorm Erwin/Gudrun”, Specialty Practice Briefing, Issue 2, http:// www.guycarp.com/portal/extranet/pdf/Speciality_Briefing_170105.pdf, 2005 [8] White, H. B., “Wind Design Loads,” Transmission & Distribution World, Jan 1, 2008 Issue, 2008. [9] McFerren, G., and P. Frost, “The Southern African Advanced Fire Information System,” Proceedings of the 6th International ISCRAM Conference, Gothenburg, Sweden, May 2009. [10] San Diego Gas & Electric (SDG&E), “SDG&E’s Fire Prevention Activities,” Presentation to the California Public Utility Commission, http://docs.cpuc.ca.gov/EFILE/EXP/124035 .pdf, 2010. [11] Fujita, T. T., “Tornadoes Around the World,” Weatherwise, 1973. [12] Storm Prediction Center, “The Enhanced Fujita Scale (EF Scale),” http://www.spc.noaa .gov/efscale/, 2007.

Selected Bibliography Abi-Samra, N., “Impacts of Extreme Weather on Power Systems and Components,” EPRI Report 1017901, 2009. Abi-Samra, N., “Impacts of Extreme Weather Events on Transmission and Distribution Systems Case Histories, Lessons Learned and Best Practices,” EPRI Report 1020145, 2010. Campbell, R. J, “Weather-Related Power Outages and Electric System Resiliency,” Congressional Research Service, 2012. Consolidated Edison Company “Post Sandy Enhancement Plan,” http://www.coned.com/publicissues/PDF/post_sandy_enhancement_plan.pdf, 2013. Elsner, J. B., et al., “The Increasing Intensity of the Strongest Tropical Cyclones,” Nature 455:92–95, 2008. Emanuel, K., et al., “Hurricanes and Global Warming: Results from Downscaling IPCC AR4 Simulations,” Bulletin of the American Meteorological Society 89:347–367, 2008. EPRI, NERC, and PSERC, “Joint Technical Summit on Reliability Impacts of Extreme Weather and Climate Change,” EPRI Report 1016095, 2008. Florida Power & Light Company, “Electric Infrastructure Hardening Plan,” filed with the Florida Public Service Commission in Docket No. 130132-EI, http://www.psc.state.fl.us/ library/FILINGS/13/02408-13/02408-13.pdf, 2013.

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Effect of High Winds on the Power Delivery System Johnson, B. W., “After the Disaster: Utility Restoration Cost Recovery,” Edison Electric Institute, ht t p s : // w w w. e f i s .p s c . m o. gov/ mp s c / c o m m o n c o mp o n e nt s / v i e wdo c u m e nt . asp?DocId=4048185, 2005. Lawrence Berkeley National Laboratory (LBNL), “Microgrids at Berkeley Lab: Borrego Springs,” http://building-microgrid.lbl.gov/borrego- springs, 2014. Massachusetts Governor’s Press Office, “Governor Patrick Announces $50m for Comprehensive Climate Change Preparedness Initiatives,” http://www.mass.gov/governor/pressoffice/ press releases/2014/0114-climate-change-preparedness- investment.html, 2014. National Weather Service, National Hurricane Center, National Oceanic and Atmospheric Administration (NOAA), “Hurricane Database,” Available: http://www.nhc.noaa.gov/ Moreland Commission on Utility Storm Preparation and Response—Final Report delivered to New York Governor Andrew Cuomo, http://www.governor.ny.gov/assets/documents/ MACfinalreportjune22.pdf, 2013. U.S. Department of Energy, Infrastructure Security and Energy Restoration, Office of Electricity Delivery and Energy Reliability, “Hardening and Resiliency: U.S. Energy Industry Response to Recent Hurricane Seasons,” http://www.oe.netl.doe.gov/docs/HR-Report-final-081710. pdf, 2010.

Appendix 9A: Common Types of Pole and Tower Structures Tangent Structures

Tangent (suspension) structures are the most commonly used structures on transmission lines. They are used on straight portions of the transmission line. Tangent structures are usually characterized by suspension (vertical) insulators, which support and insulate the conductors and transfer wind and weight loads to the structure. These are designed only to handle small line angles (changes in direction) of 0 to 2 degrees. Tangent poles act as simple cantilever beams and/or slender columns in a straight line. Some standards, such as RUS Bulletin 1724E-150, the Rural Utilities Service Construction Standards, allow tangent poles only have a maximum line angle of 5 degrees. Because tangent poles are not to be located at a sharp angle turn in the line they typically resist only the forces due to wind, ice, and gravity and the forces from unbalanced tension in the conductors or other utility wires. Tangent poles typically do not have guy wires, and they do not typically have any backfill material other than the native soil. Typical tangent poles and guyed poles have setting depths based on a rule of thumb: 10% of the total pole length plus 0.6m (2 ft). That is, if the pole is 12-m(40-ft) long, approximately 2m (6 ft) is buried while 10m (34 ft) is above ground. Even though this is a rule of thumb, pole designers have used these values for embedment depth as an industry standard for tangent and guyed poles in the United States, independent of factors such as soil conditions, wind speed, pole diameter, span lengths, and guying forces. Guyed Structures

Guyed poles resist horizontal forces and resulting torques caused by wind and vertical forces from dead load, as well as both horizontal and vertical directions due to guywires. Guying forces are the biggest contributors to vertical forces in guyed

Appendix 9A: Common Types of Pole and Tower Structures

199

poles. Like tangent poles, guyed poles do not make use of backfill or concrete to transfer forces to the soil. Self-Supporting Structures

Self-supporting poles, may be located at corners of distribution lines where guy wires cannot be used, where sidewalks prevent guying, where a property owner will not allow guying, where an obstruction prevents guying, or other locations unfavorable to guying. Self-supporting poles are not common on distribution lines but are required where there is no guying option. Angle Structures

Angle or corner structures are used where transmission line conductors change direction and need to be designed to withstand the forces placed on them by the change in direction. They are like tangent structures, using suspension insulators to attach the conductors and transfer wind, weight, and line angle loads to the structure. They also have a similarity to dead-end structures, using insulators in series with the conductors to bring wind, weight, and line angle loads directly to the structure. Dead-End Structures

A dead-end structure is typically used where transmission line conductors turn at a wide angle or end. Compared to a tangent structure, a dead-end structure is designed to be stronger, and it is often larger, to resist the full unbalanced tension that would occur if all conductors were removed from one face of the structure. Typically, insulators on a dead-end structure are in series with the conductors (horizontal) to bring wind, weight, and line angle loads directly to the structure. Classification of Tornadoes

Tornadoes were initially classified per a scale derived by Fujita in 1971, referred to as the F-scale [11]. Under this system, each tornado was assigned a number between F0 and F5 for each of the following intensity indicators: maximum wind speed, path length (along the direction of propagation), and path width (perpendicular to the direction of propagation). See Table 9A.1. Guidelines in the original scheme lumped together homes, schools, mobile homes, vehicles, and trees. It is common practice to characterize tornadoes based only on wind speed alone. In 2007, the United States adopted the enhanced Fujita scale (EF-scale). It rates the intensity of tornadoes based on the damage they cause. In the EF-scale scheme, detailed descriptions are given for examples of damage to 23 types of buildings and five additional objects like trees, towers, and poles. Wind speed estimates are then provided for each structure and type of damage. The scale has the same basic design as the original Fujita scale (six categories from 0 to 5), representing increasing degrees of damage; see Table 9A.2, which summarizes data on the Storm Prediction Center website [12]. As with the F-scale, the enhanced Fujita scale remains a damage scale and only a proxy for actual wind speeds.

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Effect of High Winds on the Power Delivery System Table 9A.1

F-Scale Classification of Tornadoes

Scale

Maximum Wind Speed (m/s)

Path Length (km)

Path Width (m)

F0

Less than 33

Less than 1.6

Less than 15

F1

33–50

1.6–5.0

15–50

F2

50–70

5–16

50–160

F3

70–92

16–50

160–500

F4

92–116

50–159

500–1,600

F5

116–142

159–507

1600–5,000

Table 9A.2 Enhanced EF-Scale for Classification of Tornadoes Scale

Meters per Second

Kilometers Relative per Hour Frequency

EF0

29–37

105–137

56.88%

Minor or no damage. Confirmed tornadoes with no reported damage (i.e., those that remain in open fields) are always rated EF0.

EF1

38–49

138–177

31.07%

Moderate damage. Roofs severely stripped; mobile homes overturned or badly damaged; loss of exterior doors; windows and other glass broken.

EF2

50–60

178–217

8.80%

Considerable damage. Roofs torn off wellconstructed houses; foundations of frame homes shifted; mobile homes destroyed; large trees snapped or uprooted; light-object missiles generated; cars lifted off ground.

EF3

61–73

218–266

2.51%

Severe damage. Severe damage to large buildings; trains overturned; trees debarked; heavy cars lifted off.

EF4

74–90

267–322

0.66%

Extreme damage. Severe damage to large buildings such as shopping malls; trains overturned.

EF5

> 90

> 322

0.08%

Destruction of buildings; trucks and train cars can be thrown approximately 1.6 km (1 mile).

Damage Estimates

Tornado Alley

No state is entirely free of tornadoes; however, tornadoes occur more frequently in the central United States, between the Rocky Mountains and Appalachian Mountains in an area colloquially referred to as Tornado Alley. Tornado Alley is therefore an unofficial area of the United States where tornadoes are most frequent covering areas of northern Texas, Oklahoma, Kansas, into Nebraska. Kansas and Oklahoma rank first and second respectively in the number of tornadoes per area. In Tornado Alley, warm, humid air from the equator meets cool, dry air from Canada and the Rocky Mountains. This creates an ideal environment for tornadoes to form within developed thunderstorms and super cells; see Figure 9A.1.

Summary and Conclusions

Figure 9A.1

201

Tornado Alley in the United States where tornadoes are most frequent.

Summary and Conclusions In many regions around the globe, transmission towers and distribution poles have failed due to the reaction to HIWs exceeding their designs. They have been blamed by many of the utility organizations in the United States, Canada, Brazil, Argentina, South Africa, New Zealand, and Australia for up to 80%–90% of all weather-related failures of towers and poles. In this book, we adopt the CIGRÉ WG B2.16 definition of HIWs as “those having velocities exceeding 45 m/s.” As this definition is quite encompassing, it includes several types of windstorms associated with large-scale tropical and extratropical storms (e.g., hurricanes, cyclones, and typhoons), gales, and thunderstorms. This chapter covers several examples of HIWs as well as salient case histories with lessons learned from them. It covers in some extended detail the 1993 345-kV line cascade in Nebraska and the 1999 wind storms that hit Europe. Lessons learned from those storms are also presented covering issues such as data collection after each storm, design considerations, and measures to halt cascades. Damage from major storms has shown that no amount of reinforcement and preparation is enough to completely avoid damage. Hence, structural hardening of the distribution system (covered in Chapter 11) should focus on targeted hardening and designing for quick restoration. To ensure resiliency against major hurricanes, tornadoes, and other high-intensity windstorms, several actions need to be taken. Resiliency measures do not prevent damage; they enable electric facilities to continue

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Effect of High Winds on the Power Delivery System

operating despite damage and/or promote a rapid return to normal operations when damages and outages do occur. This chapter details some of the resiliency measures obtained from different recent major storms. This chapter also covers wildfires that can be categorized as a windstorms and that are of concern to electric utilities infrastructures. Firestorms, which sustain their own wind system, are created during wildfires, bushfires, and forest fires. This chapter discusses two wildfires that occurred in 2003 and 2007 in the San Diego California area and damaged a lot of the local utility infrastructure.

CHAPTER 10

Effect of High Winds on Wind Turbines Introduction Investment in wind energy has been increasing over the past few years, with strong development in technologies implemented in this area. Wind energy exploration began on land (now referred to as onshore) and later extended to the sea (now referred to as offshore) due to higher winds, and hence greater potential for exploitation of wind resources. Both types of wind turbines operate under the same principles and are subject to similar risks from windstorms and gusts. This chapter covers some of the impacts of high winds on both types of applications, methods to protect wind turbines against them, and measures to ride though them to preserve system stability and economic income. It also provides several case histories. High-wind conditions may be experienced by wind turbines under different scenarios: normal operation, during idle or parked time, or during a particular operation (startup or shutdown). Although it may seem as though high winds offer the perfect conditions for wind farms to produce electricity, in fact, very fast winds can cause damage to wind turbines. They can cause large vibrations and loads, creating significant forces and fatigue on turbine blades. Figure 10.1 depicts the failure rates of different wind turbine components from Germany and Denmark over a span of 13 years [1, 2]. High winds have been identified as being the cause of direct failure of rotors1 and gearboxes. Wind turbines normally operate at 3–4 m/s (cut-in wind speed) and a maximum speed (cut-out wind speed) of 25 m/s. This operational range is defined based on lifetime cost optimization criteria for turbines. The overall power production above the cut-out wind speeds is limited, and it does not compensate for the risks of operating the higher loads experienced by turbines at these wind speeds. Limiting the mechanical torque or power output in high-wind speed conditions is a very important objective for wind turbine design. Wind turbine generators must therefore be equipped with suitable safety features, passive or active, to avoid possible mechanical strains on the structure and thermal stresses on the electrical generator. Having such safety features that protect wind turbines from damage under high winds could lead to mass shutdowns in a wind farm very quickly. Several of such cases have been reported. To limit the impact of such multiple shutdowns and to attain optimized extraction of wind energy, it is necessary to keep wind turbines 1 Rotor contains the hub and the blades. The blades are connected to the hub, which transmits the rotational energy to the gearbox via the main shaft. For large turbines, the blades’ size usually is between 80m and 100m in diameter, and they rotate between 10 to 30 rpm.

203

204

Effect of High Winds on Wind Turbines

Figure 10.1 Failure/turbine/year from two large surveys of 6,000 land-based European wind turbines over 13 years. (Data from: [1].)

running at higher wind speeds, while limiting their mechanical torque. Fortunately, new developments in the wind turbine industry today allow reduced operation under high-wind conditions. These advancements are advantageous for network stability and energy production. This chapter details all of the above and provides case histories in which high winds have impacted individual turbines and wind farms.

The Impact of High Winds on Wind Farms: Case Histories It is important to understand how high winds affect wind turbines now that use of energy from the wind is increasing worldwide. Accordingly, in the following case histories, we examine situations in which high winds have led to wind turbine damage or even the nearly simultaneous shutting down of numerous wind turbines. Denmark, 2005

On January 8, 2005, wind farms in Denmark were affected by Cyclone Gudrun. Sustained wind speeds of 35 m/s (78 mph) with wind gusts of 45 m/s (103 mph) were measured in Hanstholm, Denmark—the same strength as a category 1 hurricane. At 11:45 a.m. that day most of the wind farms were operating at full power, with a planned output of 1,843 MW. At 4:30 p.m., winds picked up at the location of the wind and most of the wind turbines shut down. The output power of the farm dropped to 126 MW, a 93% drop [3]. Figure 10.2, extracted from data by Danish grid operator ELTRA, shows the wind generation before and after the storm.

The Impact of High Winds on Wind Farms: Case Histories

205

Taiwan, 2008

On September 28, 2008, Typhoon Jangmi struck Taiwan causing the failure a of large wind turbine. The tower was buckled and broken into three parts. The nacelle and shaft collapsed and were destroyed. This event marked the first time a wind turbine tower in Taiwan had to be rebuilt after collapsing in a typhoon. A structural analysis showed wind stress distribution with wind velocities of 54.3 m/s (recorded maximum wind speed from the wind turbine sensor was 54.3m/s when the tower collapsed), while the design wind speed was 70 m/s. All wind turbine bolts were completely broken into pieces and scattered on the ground. To identify the collapse mechanism, both intact bolts from nearby wind turbines and fractured bolts from the collapsed turbine were tested. These tests indicated that most bolts had insufficient strength, and a variance existed in bolt quality [4]. United Kingdom, 2011 and 2015

In December 2011, a storm with winds of up to 74 m/s (165 mph) hit Scotland. On the morning of that storm, the country’s wind turbines were generating more than 2,000 MW. By midday, output had fallen to 708 MW due the storm. This same storm was responsible for a wind turbine catching fire at a wind farm in Ardrossan, North Ayrshire (also covered under a case history later on in this chapter) [5, 6]. On November 17 and 18, 2015, dozens of wind turbines in England automatically switched off due to high winds from the named storm Barney, in which gusts of up to 38 m/s (85mph) were recorded. In Ireland, during Barney, wind energy decreased by as much as 44%, dropping from 1,385 MW (forecasted) to 777 MW (actual) [7].

Figure 10.2 Precipitous drop in wind generation during Cyclone Gudrun in Denmark, January 2005. (Data from: [3].)

206

Effect of High Winds on Wind Turbines

Figure 10.3 Sequence of events during the September 28, 2016 blackout in South Australia.

Blackout System Event in South Australia, September 28, 2016 Sequence of Events

Generation from wind has been steadily increasing in South Australia (SA). In June 2016, wind was supplying about 50% of the total load, with the other 50% supplied by natural gas and imports (about 33% and 17%, respectively) [8]. On the morning of September 28, and immediately prior to the event, the resource mix of the 1,895 MW of total electricity demand was supplied by 883 MW of wind generation (47%), 330 MW of gas generation, and 613 MW from imports via two interconnections with Victoria: Heywood (AC) and Murraylink (HVDC). The balance, about 70 MW, was being supplied by generation embedded in the distribution network, such as solar photovoltaic. Extreme winds from this storm resulted in five system faults on the transmission system.2 These faults resulted in six voltage disturbances that led to the dropping of 445 MW of wind generation. This reduction in generation, and immediate compensating increase of imports on the AC connector to Victoria, resulted in the tripping of the interconnector, due to automatic loss of synchronism protection. The HVDC connector remained connected, as designed.3 The imbalance between the resources and the load caused a rapid system frequency collapse. The under-frequency load shedding (UFLS) scheme could not act to save the system from a blackout [8]. 2

The wind speed forecasts were up to 120 km/h (33.3 m/s), which the SA transmission lines were designed to withstand. The information provided to AEMO indicated that damaged transmission lines were subjected to actual wind speeds that were much higher than forecast [8]. 3 The HVDC connector remained connected to the network during all faults and disturbances, maintained its pre-event active power level of 114 MW, and disconnected at 16:18:16 during the SA system collapse.

Stresses from High Winds

207

Figure 10.4 Performance of wind farms during the September 28, 2016 blackout in South Australia. The grouping is based on geography (i.e., where the turbines were located, not type). (Data from: [8].)

Investigations by the Australian Energy Market Operator (AEMO) found that nine of the 13 wind farms on-line before the storm did not ride through the six voltage disturbances experienced during the event. After the event, AEMO reclassified the simultaneous trip of the wind farms as a credible contingency. Figures 10.3 and 10.4 show the sequence of events and the performance of the wind farms during the event from data found in the AEMO third report on the blackout [8].

Stresses from High Winds Extreme wind conditions may be experienced by wind turbines under different conditions: normal operation, idling or parked time, or during a specific operation (e.g., startup or shutdown). Wind turbine component damage or failure can occur when extreme wind produces forces on the wind turbine above the design limit. Failure modes of wind turbines can include loss of blades and buckling of the supporting tower, with the latter being the main concern as failed blades are easier to replace. High winds may not only damage the wind turbine itself, but they could also lead to third-party risk from blade throws (when blades are torn off and hurl toward surrounding objects) and flying debris. The mode of failure of a wind turbine due to an extreme wind event cannot be generalized. The damage is a function of the turbine type and configuration, as well as the specifics of the extreme wind event and site conditions. However, in all

208

Effect of High Winds on Wind Turbines

cases, the forces and the wind turbine mechanical power, P, produced by the higher winds are dependent on their speeds, as shown in (10.1). P=

1 rCp (b, l)Avw3 2

(10.1)

where

ρ

is the air density, typically taken as 1.225 kg/m3 at sea level and at 15°C.

A

is the area swept by the blades.

vw

is the wind speed.

Cp

is the power coefficient, which is a function of the blade pitch and the tip speed ratio; see Figure 10.5.

β is the pitch angle of the wind turbine blade (the angle at which the blade surface contacts the wind). Increasing β moves the blades out of the wind, thereby reducing the effective wind area. λ is the tip speed ratio given by λ = ΩR/vw, where Ω is the turbine rotor speed, and R is the radius of the wind turbine blade. In (10.1), the factor with the largest influence on turbine power is the wind speed since the energy content of wind is proportional to the cube of the wind speed. From the turbine cut-in speed to the rated speed, a turbine’s power is proportional to the cube of the wind speed. Figure 10.6 depicts the power generated by a wind turbine for four wind speeds, Vw1, Vw2 , Vw3, and Vw4.

Figure 10.5

Cp as a function of the pitch angle β and of the tip speed ratio λ .

Stresses from High Winds

Figure 10.6

209

Wind turbine maximum power curve.

As can be seen from Figure 10.6, the power generated increases quickly with wind speeds, and so do the stresses on the different wind turbine components. The stresses due to the wind loads cause a bending of the blade in the direction of the wind and centrifugal forces that pull the blades radially outward. The centrifugal forces are proportional to blade length, the square of the turbine speed, and the blade weight. Such stresses lead to blade materials fatigue, even at moderate wind speeds and could cause failure under extreme winds. To reduce the impact the stresses, without affecting efficiency, wind turbine manufacturers build wind turbines with few blades that are long and narrow and that are pitched to an optimum angle to the wind. See Figure 10.6 for the influence of the pitch angle on the power coefficient. Manufacturers can design their wind turbines to operate safely in even extreme wind conditions and determine the expected life span of a turbine blade based on the amount of stress it can withstand before it needs to be replaced. Cut-In and Cut-Out Speeds

Wind turbines normally operate between a cut-in speed and a maximum speed, the cut-out speed (also called cut-off speed, see Figure 10.7). Below the cut-in speed, there is insufficient torque exerted by the wind on the turbine blades to make them rotate. However, as the speed increases, the wind turbine begins to rotate and generate electrical power. As the speed increases above the rated output wind speed, the forces on the turbine structure continue to rise, and, at some point, there is a risk of damage to the rotor. Not all turbines have a well-defined cut-out speed.

210

Effect of High Winds on Wind Turbines

Figure 10.7

Typical wind turbine power output versus speed.

The operational range of a wind turbine is defined based on lifetime cost optimization criteria for the turbine and its components. The cut-out speed of turbine operation becomes one of the limiting factors in wind turbine design. Operation at, or above, the cut-out speed should be limited, as it does not compensate for the higher loads experienced by the turbine.

Exercise 10.1 For a large wind turbine, assuming the same power coefficient, C p, what is the velocity of wind that can produce three times the power generated by 5-m/s wind? Solution

1 A × r × v3 2 v1 = 5 P1 =

P2 = 3P1 Then v2 = 5 × 31/3 = 7.2 m/s Therefore, for only 44% higher wind speed, we get three times the power form the wind.

Exercise 10.2 Compare the total wind energy at 15°C, at sea level (1 atm), impinging on one square meter surface of an area swept by a wind turbine, under the following wind conditions.

Wind Turbine Vulnerability to Hurricanes • • •

211

100 hours of 10-m/s wind; 50 hours of 7-m/s wind; 50 hours of 14-m/s wind;

Assume that ρ at sea level (1 atm) and 15°C is 1.225 kg/m3 Solution

A = 1m 2 100 hours of 10-m/s wind then would yield: 1 r × A × v3 2 E(W) = P(W) × t P(W) =

1 × 1.225 × 1 × 103 = 0.6125 kW 2 E(W) = 100 × 0.6125 = 61.25 kWh P(W) =



50 hours of 7-m/s and 50 hours of 14-m/s wind would yield: 1 × 1.225 × 1 × (73 ) = 0.21 kW 2 E7 (W) = 50 × 0.21 = 10.5 kWh P7 (W) =

1 × 1.225 × 1 × (143 ) = 1.68 kW 2 E14 (W) = 50 × 1.68 = 84 kWh P14 (W) =

Total = 84+1.68 = 94.5 kWh So even so the average speed is the same (10 m/s), the higher wind speeds, with velocity cubed relation, give higher energy content, even at half the time.

Wind Turbine Vulnerability to Hurricanes Wind speeds in hurricanes4 can exceed the design limits of wind turbines and lead to their failure and damage. Offshore wind turbines could be more vulnerable, as 4

NOAA’s National Hurricane Center uses the Saffir-Simpson Hurricane Wind Scale (SSHWS). This assigns hurricanes a category 1–5 rating, based on each hurricane’s intensity. A hurricane’s destructive power is in the form of extreme winds and storm surges. A category 2 hurricane, with wind speeds of 43–49 m/s (96–110 mph) and storm surges of 1.8–2.5m above normal, can cause moderate damage at landfall, while a hurricane of category 3 level, with wind speeds of 50–58 m/s (111–130 mph) and storm surges of 2.7–3.7m above normal, could cause extensive damage at landfall.

212

Effect of High Winds on Wind Turbines

hurricanes draw their fuel from the heat of the water and water evaporating from the water’s surface. In 2003, a wind farm of seven turbines in Okinawa, Japan, was destroyed by Typhoon Maemi [9], and several turbines were damaged in China by Typhoon Dujuan [10]. To illustrate the risk to a wind farm from hurricane force wind speeds, Rose et al. [11] calculated the expected number of turbine towers that could buckle in a 50-turbine NREL 5-MW turbine [12] wind farm as a function of maximum sustained (10-min mean) wind speed. In that analysis, they assumed that turbines cannot yaw during the hurricane to track the wind direction to protect the turbines. Figure 10.8, constructed from data in [11], shows the cumulative distribution function (CDF) of the expected number of turbine towers that could buckle in a single storm as a function of wind speed for a hurricane TI of 9% (where TI, the turbulence intensity, is defined as the 10-min standard deviation of wind speed divided by the 10-min mean wind speed). The dashed lines plot the fifth and 95th percentile values, and the solid curve represents the median. The vertical dashed lines show the hurricane corresponding category.

Hardening Wind Turbines Against High Winds To achieve physical hardening of wind turbines against extreme conditions, it is necessary to examine several conditions, including the following:

Figure 10.8 Cumulative distribution function (CDF) of the expected number of turbine towers buckled by a single storm as a function of wind speed. (Data from: [11].)

Hardening Wind Turbines Against High Winds • • • •

213

Extreme wind magnitude and profile (i.e., extreme shear); Extreme turbulence; Coherent gust and direction change; Extreme operating gust.

The hardening spans many different areas and components of the wind turbine, from the blades to the foundation. Details of hardening techniques are beyond the scope of this book; readers interested in learning more should consult the excellent references on this listed in the chapter’s Selected Bibliography section. However, Figure 10.9 shows a nonexhaustive list of active and passive techniques to reduce wind turbine damage due to high winds.

Figure 10.9 Nonexhaustive list of active and passive techniques to reduce wind turbine damage in high winds.

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Effect of High Winds on Wind Turbines

Offshore wind turbine risk at sea, where hurricanes draw their fuel from the heat of the water and water evaporating from the water’s surface, may be severe. Thus, offshore turbines in Europe utilize heavy concrete gravity-based structures that are placed on the seabed or monopiles that are driven many meters into the seabed to keep turbines steady in high winds and waves. Typically, wind turbines are designed based on engineering design codes and standards, such as IEC 61400, an international standard set published by the International Electrotechnical Commission; see this chapter’s appendix for more details on this standard. For northern Europe and the North Sea, where nearly all the offshore and coastal wind turbines have been built [13], these codes specify maximum sustained wind speeds with a 50-year return period of 42.5–51.4 m/s (83–100 knots), lower than high-intensity hurricanes. Several studies of extreme winds in areas prone to tropical cyclones have suggested engineering design modifications. Garciano et al. [14] proposed increasing the 50-year design reference wind speed for the Philippines from 50 m/s to 58 m/s at hub height; Clausen, et al. [15] proposed 55–75 m/s (at a 10-m height) for parts of the Philippines and southern Japan; and Ott [16] proposed a model of extreme wind speeds in the western Pacific. Such modifications can increase the cost of an onshore turbine 20%–30%. Wind turbines that have external power available to yaw can have a reduced risk of being destroyed. When winds are above the cut-out speed, the wind turbine should have its blades idling in a position creating minimal torque on the rotor. This is the only safety mechanism other than the yaw control. Installing batteries, or supercapacitors, to allow a turbine to yaw without external power, would add $30,000–$40,000 (in 2010 prices) to the price of a turbine, assuming 6h of backup power for yaw motors that draw 12 kW of power [17]. Backup power and active controls may be a low-cost way to reduce risk to the turbine. Backup power for the yaw system can be also be supplied by diesel generators. As an example, before Hurricane Irene hit, the 2-MW turbine at the University of Delaware was shut down and hooked up to a diesel generator. The shutdown turbine sustained 34-m/s (72mph) winds with its active yaw system pointing into the wind during the storm.5 Without the diesel generator the yaw system would have become inactive, and the risk to the turbine would have increased [19]. A main concern with losing wind turbines during hurricanes is the implication this would have for grid reliability; however, since there is ample warning of hurricanes, and supplemental generation reserves can be brought on-line to cover for wind plants that are shut down during the time it takes to rebuild buckled towers. The damage caused by category 3, 4, and 5 hurricanes is important for offshore wind development in the United States because every state on the Gulf of Mexico coast and nine of the 14 states on the Atlantic coast have been struck by a category 3 or higher hurricane in the last 100 years.

5

In 1999 Hurricane Irene made landfall in North Carolina with wind gusts of 38 m/s (86 miles per hour).

Methods of Shutting Down Wind Turbines under High Wind Conditions

215

Figure 10.10 Depiction of wind turbine shutdown under high winds.

High Wind Speed Shutdown At high wind speeds, typically above 25 m/s, most modern wind turbines cease power generation and shut down with the aid of a built-in safety feature. The high speed shutdown system is needed to avoid the mechanical stresses of high winds and to avoid a runaway condition if a wind turbine loses its connection to the grid. The operational range of the wind turbine (between the cut-in and cut-out speeds) is defined based on lifetime cost optimization criteria for the turbine and its components. This operating range becomes one of the limiting factors in wind turbines, needing either a robust design or an active speed-control system. The cut-out speed (also known as furling speed). Figure 10.10 depicts the typical range of operation of a wind turbine. In Figure 10.10, the wind turbine would shut down when the average wind speed reaches a certain value, the cut-out speed (e.g., 25 m/s). When the average wind speed drops below the cut-out value to a predetermined value cutback-in wind speed (lower than the shutdown speed), the wind turbine restarts. This hysteresis is needed to prevent frequent shutdowns and restarts, which contribute to fatigue-loading of the turbine. The fatigue concern would typically not be a concern when the wind speeds rarely exceed the cut-out speed but can be problematic in areas of high wind speeds dominated by short gusts of wind above the cut-out speed and high turbulence. The net result is a loss of production as the turbine switches in and out of operation.

Methods of Shutting Down Wind Turbines under High Wind Conditions Shutdown of a wind turbine may occur in one of several ways. The most common methods used by large turbines are stall or blade pitch-regulation. Automatic

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Effect of High Winds on Wind Turbines

Figure 10.11

Pitch regulation to stop wind turbines under high winds.

brake systems are also activated by wind speed sensors. These methods are further explained in the following sections. Stopping the Wind Turbine by Pitch Regulation

The main benefits of active pitch regulation (shown in Figure 10.11) over a stallregulated wind turbine are increased energy capture (albeit only few percentage points), the aerodynamic braking facility it provides, and reduced extreme loads on the turbine when shut down. Blade pitch control is a feature of nearly all large modern horizontal-axis wind turbines. The purpose of the pitch angle control might be expressed as follows [18–20]: 1. Optimizing the power output of the wind turbine below the rated wind speed to give maximum power. 2. Preventing turbine mechanical power from exceeding the design limits above rated wind speed through regulating the aerodynamic power and loads produced by the rotor. 3. Minimizing fatigue loads of the turbine’s mechanical components by ensuring that excessive loads do not result from the control action or even the reduction of certain fatigue loads. 4. With the pitch controller, it is possible to operate wind turbines at different pitch angles under normal conditions. This allows the wind turbine to have a reserve power to be called when needed. Under high wind speed conditions, the actions of the pitch control system limit the aerodynamic torque driving the generator to ensure that the mechanical components of the turbine (e.g., gearbox, generator shaft, and low-speed shaft) are not stressed due to overloads caused by wind fluctuations and turbulence. Figure 10.12 shows a family of power curves for a range of positive pitch angles for a 1,500 kW

Methods of Shutting Down Wind Turbines under High Wind Conditions

Figure 10.12

Illustration of the variations of wind turbine power output with different pitch angles.

Figure 10.13 Wind turbine output power with and without pitch control.

217

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Effect of High Winds on Wind Turbines

turbine. Figure 10.13, constructed with data from [21], shows the power curve of a pitch-controlled fixed-speed wind turbine at 15 rpm. Without the pitch control, the rotor speed and the associated power can reach unsafe limits. The pitch control system can feather (at 90° of positive pitch the blade is said to be feathered) the blades to stop the rotor during emergency shutdowns, or whenever the wind speed exceeds the maximum rated speed. Blade pitching to feather gives a highly effective means of aerodynamic braking. Blade pitch rates of 10° per second are found adequate, and this is of the same order as the pitch rate needed for power control [18]. To halt a three-bladed wind turbine, all three blades must move into the feathering position together to distribute and balance the loads on all structural parts during the procedure. All three pitch axes must move out of the wind at the same time. Several open-loop control schemes are available for the pitch actuator feathering drive, lest the pitch axis position feedback signal is lost. Closed-loop, self-sensing, and pitch control systems are also available. For pitch-regulated wind turbines, the blades need not be as strong as those required by stall-regulated turbines, which reduces blade costs [22]. Stopping Wind Turbines with Stall Regulation

Stall regulation (shown in Figure 10.14) offers the simplest means of controlling the maximum power generated by a wind turbine against high winds. Stall regulation control must be part of the design of the wind turbine. The principle of the operation of stall regulation is increasing the angle of attack to decrease the lift-to-drag ratio; see Figure 10.15. Stall regulation can be passive or active. Passive schemes do not require or have any assist from pitch control. The blades of passive stall power–controlled wind turbines have a fixed angle and are slightly twisted along their longitudinal axis. The rotor airfoil profile is aerodynamically designed so that when the wind speed exceeds a safe limit, the angle of attack of the airfoil to the wind stream is increased. This would stop the lift force on the blade causing the wind turbine to stall. This ensures that the blade stalls gradually. (See Figure 10.15.) The advantage of stall control in wind turbines is that it avoids the introduction of moving parts into the rotor and it simply accomplished

Figure 10.14

Stall regulation as a method to stop wind turbines under high winds.

Methods of Shutting Down Wind Turbines under High Wind Conditions

Figure 10.15

219

Variation of the lift/drag ratio of a stall-regulated wind turbine.

the aerodynamic design of the rotor airfoil. It also avoids stall-induced vibrations. A large number of installed wind turbines are stall-controlled. Wind turbines normally experience a drop in their electrical power output levels at high wind speeds. See Figure 10.16.

Figure 10.16

Comparison between pitch and stall regulation for wind turbines.

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Effect of High Winds on Wind Turbines

Some turbines larger than 1-MW rated capacity are equipped with active stall power–control mechanisms. In this case they use pitchable blades resembling the pitch-controlled machines. In high winds, the control system pitches the blades in the opposite direction of the logic of pitch-regulated turbines (decreasing the angle of attack to reduce the lift and the rotational speed of the blades), thus increasing the angle of attack leading to a stall condition. An advantage of active stall control is that the power output can be controlled to avoid overshooting the generator’s rated power at the start of wind gusts and the wind turbine is able to deliver its rated power at high wind speeds. See Figure 10.16. In high winds, for the turbine to stall, the rotor speed must be restrained. In a fixed-speed turbine,6 the rotor speed is restrained by the generator if the torque stays below the pull-out torque. In a variable-speed turbine, the speed is varied so that the generator torque matches the aerodynamic torque generated by the wind turbine. At that point the rotor could be slowed down. The load torque has to exceed the wind torque for the rotor to stall. Disadvantages of Stall Regulation

Stall regulation has several disadvantages, such as the following: •





Lower aerodynamic efficiency: To achieve stall regulation at reasonable wind speeds in fixed-speed wind turbines, turbines must be operated close to stall. This could result in lower aerodynamic efficiency. This could be mitigated in a variable-speed turbine, keeping the speed below rated speed to maintain peak power coefficient. Higher risk of fatigue: The stalled blade could exhibit low vibration damping. Low variation in the presence of low damping could lead to large vibration displacement amplitudes that could lead to large bending moments and stresses, causing fatigue damage. Higher cost design of the wind turbine blades: When parked in high and turbulent winds the stall-regulated, fixed-pitch stationary blade could be subjected to large aerodynamic loads that cannot be alleviated by adjusting (feathering) the blade pitch angle; thus blades must be designed to ride through these, at the expense of a cost penalty.

Hybrid: Combination Pitch and Stall Control

On constant-speed turbines, the blade pitch setting is adjusted slowly to provide maximum power output. When the rated wind speed is reached, the blades are adjusted to a more negative pitch setting, tripping aerodynamic stall. At higher wind speeds, the pitch angle is adjusted continuously to maintain the maximum power specified. 6

Wind turbines are classified by their mechanical power control and by their speed control. Beyond mechanical power regulation, turbines are further divided into type 1 (fixed-speed) and type 2 (limited variable speed).

Methods of Shutting Down Wind Turbines under High Wind Conditions

221

For variable-speed turbines, when the rated wind speed is reached, the blades are adjusted to a more positive pitch setting, thereby reducing the aerodynamic forces and maintaining the requested power levels. Stopping the Wind Turbine by Applying a Mechanical Brake

Mechanical brakes control overspeed during high-wind shutdowns for the majority of wind turbines. Aerodynamic braking, in pitch-regulated wind turbines, is used to decelerate the rotor initially, so the mechanical brake torque does not have to be high. The mechanical brake can be actuated when an overspeed resulting from the failure of the aerodynamic system is detected. It can also be actuated simultaneously with the aerodynamic brake. The most severe emergency braking case would arise following a grid loss during generation in winds above rated speeds. A wind turbine mechanical brake typically consists of a steel brake disc acted on by calipers. The brakes can be mounted on the rotor or low-speed shaft or on the generator high-speed shaft (or in some cases on both shafts). The most cost-effective position is on the high-speed shaft between the gearbox and the generator; see Figure 10.17. Mounting on the generator’s high-speed shaft results in a braking torque in inverse proportion to the shaft speeds. The heat generated

Figure 10.17

Wind turbine mechanical brakes.

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Effect of High Winds on Wind Turbines

by the braking must be designed with enough mass to dissipate the heat and stay below design values.

High Wind Ride-Through Capability of Modern Wind Turbines As wind power penetration increases and wind farms grow in size, following the common approach to shutting down wind turbines at a certain cut-out wind speed (to protect the wind turbine structure from excessive loading) yields economic losses and undesirable effects for the grid. In addition, frequent shutdowns and restarts can contribute to fatigue-loading of turbines. Furthermore, it makes prediction of the energy output at high wind speeds difficult. Small errors in wind-speed prediction could lead to excessive errors in power prediction. Therefore, there is keen interest among grid operators to attain some kind of ride-through capability for high winds to ensure reliable energy production in high-wind situations. Equipping wind turbines with control logic that would extend their operating range and that would gradually reduce power output instead of shutting down completely at high winds could lead to a more stable power output and a better economic performance. It would be particularly helpful for larger wind farms where commitment to a certain level of energy production is often required. One added benefit of a ride-through capability for high winds is related to spinning reserve. If an increase in wind speed can cause all the turbines in a large wind farm to shut down suddenly within a few minutes of each other, the network would have to cope with this energy deficit by providing more spinning reserve. For example, if instead of shutting down suddenly at 25 m/s, ramping the power output down smoothly from full power to zero between, say, 24 and 35 m/s would result in a much lower probability of a large sudden shortfall at a wind farm. This would translate into lower spinning reserve requirements.

Approaches to Running Above Higher Wind Conditions Wind turbines operate at speeds above the cut-out speed by derating their output power during times of high wind speed. This is achieved through a range of control methods, from pitch control of blades to generator-torque control. Some systems use blade pitch-control systems to achieve a smooth ramp-down of power when winds reach a predetermined, maximum speed and threaten to overload a turbine. Control above the maximum wind speed is achieved by varying the pitch to reduce the blade speed (i.e., operating in a nonoptimal configuration that still generates some power but does not constitute stalling). For double-conversion systems, advanced system controls combining blade speed and torque controls can be used. Reduced output is achieved by slowing rotational speed, which reduces the output power of the generator, allowing the blade speed to be controlled to a manageable value.

Approaches to Running Above Higher Wind Conditions

223

Ramp-Rate Control of the Pitch Angle

The reduction of the output power would follow a linear ramp, as is shown in Figure 10.18. The power reference could be selected based on the average measured wind speed or pitch angle. Derating is achieved by pitching the blades out of the wind as soon as the rated power output is reached and by limiting rotational speed in proportion to the increase in wind speed and turbulence intensity. Such an approach can negate some of the downsides of the sharp cut-out without significant increase in wind turbine loads. The gradual derating eliminates abrupt cut-outs and eliminates the hysteresis effect shown in Figure 10.18, as operation of the wind turbine would be continuous, albeit at reduced levels, as the wind speed increases and decreases beyond the cut-out speed. Such a gradual reduction of wind turbine power reference in high wind speed is known as a soft cut-out strategy. The wind turbine extreme loads for soft cut-out typically increase by 5% [23] and can easily be accommodated in the design of new turbines. As the systems are primarily based on the control portion of the turbine, it would appear that the function could be retrofitted to existing wind turbines. Dynamic Control of the Pitch Angle

Another approach suggested by Jelavic et al. [24] uses a method that relies on an active control algorithm that keeps the turbine loads in the design envelope, even when wind speed is higher than cut-out value. This approach relies on the wind turbine state estimation and worst-case wind speed prediction and chooses the one that produces the maximal loads under the design constraints. If the predicted loads exceed the design envelope loads, the wind turbine power (i.e., rotor speed) reference is reduced in order to achieve lower wind turbine loads. By changing the rotor speed reference, both tip speed ratio λ and pitch angle ß are changed, which establishes a new operating point with lower loads and lower energy output. As the design parameters may not be linear, this results in a nonlinear power output of the wind turbine, as shown in Figure 10.19.

Figure 10.18 High wind ride through with ramp control of output power for pitch-regluated wind turbines.

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Effect of High Winds on Wind Turbines

Figure 10.19 High wind ride-through with dynamic control of output power for pitch-regulated wind turbines.

Implementation by Wind Turbine Manufacturers

A number of manufactures have introduced ride-through capability for their wind turbines and offer them as options. Two examples are discussed as follows. ENERCON Storm Control

ENERCON [25] equips its wind turbines with a control system that ramps down speed using pitch-angle control to vary blade speed. When storm control is activated, the rated speed is linearly reduced starting at a predetermined wind speed. Beginning at another turbine-specific wind speed, the limitation of the turbine’s rated speed also reduces active power. With this scheme, the operational range of the wind turbine can be expanded. An example provided by ENERCON in [25] shows that when their storm control system is activated, the example wind turbine would only shut down if a 10-minute average of the wind speed exceeds 34 m/s. This is in contrast to the situation that occurs when the storm control system is not active, that is, the wind turbine would shut down if either a 3-minute or 15-second average exceed 25 m/s or 30 m/s, respectively (see Figure 10.20).

Figure 10.20

Depiction of the ENERCON Storm Control System. (Data from: [25].)

Effect of High Winds on Fires in Wind Turbines

225

Figure 10.21 Performance improvement of wind turbines with Siemens high-wind ride through. (Data from: [26].)

Siemens High-Wind Ride Through

The Siemens [26] wind turbine control for high winds gradually reduces power output instead of shutting down completely. This approach relies on pitching the blades out of the wind as soon as the rated power output is reached and limiting rotational speed in proportion to the increase in wind speed and turbulence intensity. Figure 10.21 [26] depicts the performance of a wind turbine with and without the high wind ride-through control. It is to be noted that normal shutdown occurs at 25 m/s and restarts after the wind speed drops down to 20/s.

Effect of High Winds on Fires in Wind Turbines Another concern created by high winds is wind turbine fires. Instances of fires in wind turbines are increasing. Fire is the second-leading cause of catastrophic accidents in wind turbines (after blade failure) and accounts for up to 30% of the reported turbine accidents of any year since the 1980s [27]. In over 90% of wind turbine fires reported, a total loss of the wind turbine, or at least, a severe structural failure of the major components (blades, nacelle, mechanical, or electrical components) has been reported [28]. Researchers from Imperial College London, the University of Edinburgh, and SP Technical Research Institute of Sweden carried out a global assessment of the world’s wind farms, which in total contain an estimated

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Effect of High Winds on Wind Turbines

200,000 turbines [29]. The team estimated that 10 times more fires are happening than are being reported. Instead of an average of 11.7 fires each year, which is what is reported publicly, the researchers estimate that more than 117 separate fires are breaking out in turbines annually. This is still less than 0.1%. Fire accidents are much less frequent in wind turbines than in facilities of other energy sectors such as oil and gas, which globally experience thousands of fire accidents per year. Nevertheless, fires in wind turbines are a serious matter and of great concern to wind farm owners and operators. Causes of Fires

Fires are typically started by other factors other than high winds. Per Uadiale et al. [27], the main causes of fire ignition in wind turbines are lightning strokes, electrical malfunction, and mechanical malfunctions. The fire concern in wind turbines is due to the presence of large amounts of highly flammable material, such as the hydraulic oil and lubricants, contained within the nacelle of the wind turbine. These are close to potential electrical or mechanical ignition sources. Once a fire is ignited in a wind turbine, it can rapidly escalate due to the wind that supplies the oxygen. As soon as ignition occurs in a turbine nacelle, the chances of externally fighting the ensuing fire are slim to none due to the remote location of the wind farm and height of the nacelle above ground (see Figure 10.22). Instances of reports about fires on wind farms are increasing.

Figure 10.22 Depiction of a fire in the nacelle of a wind turbine.

Conclusions

227

Cases Histories Nissan Factory, Sunderland, United Kingdom, 2005

In December, one of the turbines in the Nissan factory wind farm, just installed in August of that year, was engulfed in a fire that led to its total loss. This led to the disruption of traffic on a nearby highway due to debris hazards as well as the 55-m wind turbine falling onto the road. Firefighters were not able to save the turbine due to its height and the burning debris falling to the ground, but they were able to prevent secondary ignitions on the ground. The same turbine caught fire shortly after it was restarted due to a loose bolt that had jammed a rotating mechanism that overheated the turbine [30, 31]. Ardrossan, Ayrshire, United Kingdom, 2011

On December 8, 2011, a nonoperational wind turbine caught fire during a heavy storm, with 67-m/s (150-mph) winds in North Ayshire due to a direct lightning stroke. The wind turbine was completely burnt out. Burning debris and burning debris were scattered across far distances due to the strong wind [32]. Gross Eilstorf, Germany, 2012

The Gross Eilstorf wind farm project in Lower Saxony, Germany, began operation in 2011/2012 and has a 51-MW capacity with a total of 17 wind turbines. On March 30, 2012, one of the newly installed 3-MW wind turbines caught fire, leading to the destruction of the nacelle and one of the blades. The cause of the fire was identified to be a loose connection in the electrical system [33].

Conclusions High wind conditions may be experienced by wind turbines under normal operation, when they are idling when parked, or during a specific operation (startup of or shutdown). They can cause large vibrations and loads, creating significant forces and fatigue. There have been several reported cases of wind turbine damage worldwide. There also have been reports of multiple turbines in wind farms affected by a wind storm shutting down together. The shutdown of multiple turbines is especially significant for energy systems that are heavily dependent on wind energy, a situation that is increasing globally. The shutdown of multiple turbines has been reported to be a significant contributing factor to blackout in South Australia in September 2016, where wind energy was supplying close to 50% of the load at the time. Although this chapter does not detail physical hardening of wind turbines against extreme winds, it summarizes some of the control aspects that can assist in the hardening of wind turbines against high winds. In addition, the chapter describes some active and passive techniques to reduce wind turbine damage, both when wind turbines are operational or when they are shut down as a safety measure against impending storms.

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The chapter also covers some emerging techniques to extend the operating range of wind turbines and to reduce power output gradually instead of shutting down completely during high winds. These techniques could lead to a more stable grid and improved economic performance of wind farms. Some manufactures are actually including options on their wind turbines that deliver this desired ridethrough capability. The chapter concludes with a discussion of wind turbine fires, the second-leading cause of catastrophic accidents in wind turbines (after blade failure), accounting for up to 30% of reported turbine accidents. In conclusion, it is worth noting that researchers have determined that only a fraction of the damage to wind turbines is being reported, which makes the subjects covered in this chapter even more relevant due to the ever-increasing use of wind power. As turbine size and wind farm size have increased over the years, the financial risk associated with their damage and loss of production due to high winds also increases. A single turbine may cost several million dollars. Moreover, a single offshore wind farm can cost more than one billion dollars. With such high capital costs, project owners, wind farm operators, and insurance companies want to ensure that projects have the best possible chances of withstanding extreme environmental conditions.

References [1]

Feng, Y., and P. Tavner, “Introduction to Wind Turbines and Their Reliability and Availability,” presented at the European Wind Energy Conference, April 20–23, Warsaw, Poland, 2010. [2] Tavner, P., et al., “Reliability of Different Wind Turbine Concepts with Relevance to Offshore Application,” presented at the European Wind Energy Conference, March 3– April 3, Brussels, Belgium, 2008. [3] Alegrýa, I., et al., “Connection Requirements for Wind Farms: A Survey on Technical Requirements and Regulation,” Renewable and Sustainable Energy Reviews, Vol. 11, No. 8, October 2007, pp. 1858–1872. [4] Chou, J., and, W.-T, Tu, “Lessons Learned from a Collapsed Wind Turbine Tower in Taiwan,” Engineering Failure Analysis, Vol. 18, No. 1, http://www.engineering.nottingham.ac.uk/icccbe/proceedings/pdf/pf135.pdf, 2011 [5] Diamond, K., “Extreme Weather Impacts on Offshore Wind Turbines: Lessons Learned,” Natural Resources and Environment, Vol. 27, No. 2, fall 2012. [6] Jackson, B., “165-mph Storm Wrecks A Wind Turbine,” The Sun, https://www.thesun. co.uk/archives/news/958881/165mph-storm-wrecks-a-wind-turbine/, 2011. [7] http://irishenergyblog.blogspot.com/2015_11_01_archive.html, 2015. [8] AEMO, the Australian Energy Market Operator, “Black System South Australia 28 September 2016,” http://aemo.com.au/-/media/Files/Electricity/NEM/Security_and_ Reliability/Reports/Integrated-Third-Report-SA-Black-System-28-September-2016.pdf, October 2016. [9] Takahara, K., et al., “Damages of Wind Turbine on Miyakojima Island by Typhoon Maemi in 2003,” http://windeng.t.u-tokyo.ac.jp/ishihara/paper/2005-5.pdf, Japan, 2004. [10] Clausen, N., et al., “Wind Farms in Regions Exposed to Tropical Cyclones,” https://www. researchgate.net/publication/228491415_Wind_farms_in_regions_exposed_to_tropical_ cyclones, Hamburg: Germanischer Lloyd WindEnergie GmbH; 2007. [11] Rose, S., et al., “Quantifying the Hurricane Risk to Offshore Wind Turbines,” Proc Natl Acad Sci U S A, 2012 Feb 28; 109(9): 3247–3252. Published online 2012 Feb 13. doi: 10.1073/pnas.1111769109, 2012.

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[12] Jonkman, J., et al.,“Definition of A 5-MW Reference Wind Turbine for Off-Shore System Development,” http://www.nrel.gov/docs/fy09osti/38060.pdf, 2009. [13] Argyriadis, K., “Recommendations for Design of Offshore Wind Turbines (RECOFF), Section 2.1: External Conditions,” http://cordis.europa.eu/project/rcn/54147_en.html, 2004. [14] Garciano, L., and T. Koike, “New Reference Wind Speed for Wind Turbines in TyphoonProne Areas in The Philippines,” J Struct Eng., 2010;136:463–467, 2010. [15] Clausen, N.-E., et al., “Design of Wind Turbines in An Area with Tropical Cyclones,” Athens: European Wind Energy Conference and Exhibition, 2006, pp. 1–10. [16] Ott, S., “Extreme Winds in The Western North Pacific,” Riso-R-1544(EN) Riso National Laboratory, Roskilde, Denmark, 2006, pp. 1–39 [17] Aabakken, J., Power Technologies Energy Data Book (fourth edition), Golden, CO: National Renewable Energy Laboratory; 2006. [18] Burton, T., et al., Wind Energy Handbook (second edition), John Wiley & Sons, Chichester, United Kingdom, 2011. [19] Mahan, S., “Hurricane Irene and Its Impact on Wind Farms,” http://blog.cleanenergy. org/2011/09/06/hurricane-irene-and-its-impact-on-wind-farms/, 2011. [20] DNV/Risø, Guidelines for Design of Wind Turbines (second edition), Denmark: Jydsk Centraltrykkeri, 2002. [21] NREL, “Fixed-Speed and Variable-Slip Wind Turbines Providing Spinning Reserves to The Grid,” http://www.nrel.gov/docs/fy13osti/56817.pdf, July 2013. [22] Markou, H., and T. J. Larsen, “Control Strategies for Operation of Pitch Regulated Turbines Above Cut-Out Wind Speeds,” in European Wind Energy Conference and Exhibition EWEC 2009, Vol. 6, 2009. [23] Bossanyi, E., and J. King, “Improving Wind Farm Output Predictability by Means of a Soft Cut-Out Strategy,” in European Wind Energy Conference and Exhibition EWEA, 2012. [24] Jelavic, M., et al., “Wind Turbine Control Beyond the Cut-Out Wind Speed,” https://bib. irb.hr/datoteka/619383.EWEA13_clanak.pdf, 2014. [25] ENERCON, http://www.enercon.de/en/technology/wec-features/, 2017. [26] Olson, J., and P. Botha, “Performance Upgrades of Operational Wind Turbines,” http:// www.windenergy.org.nz/store/doc/2014NZWEC_PaulBotha_JonOlson.pdf, 2013. [27] Uadiale, S., et al., 2014, “Overview of Problems and Solutions in Fire Protection Engineering of Wind Turbines,” Fire Safety Science Vol. 11, 2014, pp. 983–995. [28] “Summary of Wind Turbine Accident Data to 31 December 2012,” Caithness Windfarm Information Forum, 2013. [29] “Fires Are Major Cause of Wind Farm Failure, According to New Research,” Imperial College News, http://www3.imperial.ac.uk/newsandeventspggrp/imperialcollege/newssummary/news_17-7-2014-8-56-10, July 2014. [30] Windaction, “Wind Turbine on Fire,” http://www.windaction.org/posts/813-wind-turbineon-fire-1#.WGauemffPmF. [31] BBC News, “Human Error Caused Turbine Blaze,” http://news.bbc.co.uk/2/hi/uk_news/ england/wear/4759926.stm, 2006. [32] BBC News, “Wind Turbine Fire at Ardrossan Wind Farm,” http://www.bbc.co.uk/news/ uk-16115139, 2011. [33] Williamson, K., “Vestas Identifies Cause for V112 Wind Turbine Fire,” http://www. renewableenergyfocus.com/view/25458/vestas-identifies-cause-for-v112-wind-turbinefire/, 2012. [34] IEC standards, http://www.iec.ch/dyn/www/f?p=103:22:0::::FSP_ORG_ID:1282. [35] The American National Standards Institute ANSI, http://webstore.ansi.org/energy/windturbine/default.aspx?source=blog.

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[36] International Standard—IEC 61400-1, Wind Turbines—Part 1: Design Requirements. Third Edition 2005-8—IEC ref # IEC 61400-1:2005 (E).

Selected Bibliography Eggleston, D. M. and F. S. Stoddard, Wind Turbine Engineering Design, New York: Van Nostrand Rheinhold, 1987. Harrison, R., E. Hau, and H. Snel, Large Wind Turbines, Design and Economics, John Wiley & Sons Ltd., Chichester, United Kingdom, 2000. Hau, E., Wind Turbines: Fundamentals, Technologies, Application, Economics (second edition), Heidelberg: Springer, 2006. Leite, O., “Review of Design Procedures for Monopile Offshore Wind Structures,” masters dissertation, https://sigarra.up.pt/feup/pt/pub_geral.show_file?pi_gdoc_id=408683, 2015. Suryanarayanan, S., and A. Dixit, “Control of Large Wind Turbines: Review and Suggested Approach to Multivariable Design,” Proc. of the American Control Conference, 2005. Senjyu, T., et al., “Output Power Control of Wind Turbine Generador by Pitch Angle Control Using Minimum Variance Control,” Electrical Engineering in Japan, Vol. 154, No. 2, 2006. Lupu, L., et al., “Pitch and Torque Control Strategy for Variable Speed Wind Turbines,” in 2006 European Wind Energy Conference Proceedings, Athens, Greece, 2006.

Appendix 10A: IEC 61400 The IEC 61400 is an international standard set published by the International Electrotechnical Commission on design requirements for wind turbines [34]. The series covers most aspects of wind turbine life from site conditions before construction to testing after assembly, as seen in the following list. • • • • • • • • • • • • • •

• •

IEC 61400-1, design requirements; IEC 61400-2, small wind turbines; IEC 61400-3, design requirements for offshore wind turbines; IEC 61400-4, gears for wind turbines; IEC 61400-5, wind turbine rotor blades; IEC 61400-11, acoustic noise measurement techniques; IEC 61400-12-1, power performance measurements; IEC 61400-13, measurement of mechanical loads; IEC 61400-14, declaration of sound power level and tonality; IEC 61400-21, measurement of power quality characteristics; IEC 61400-22, conformity testing and certification of wind turbines; IEC 61400-23, TR Full scale structural blade testing; IEC 61400-24, TR lightning protection; IEC 61400-25 (1-6), communications for monitoring and control of wind power plants—overall description of principles and models; IEC 61400-26, time-based availability for wind turbine generating systems; IEC 61400-27, electrical simulation models for wind power generation.

Appendix 10A: IEC 61400

231

Figure 10A.1 Examples of existing standards for the design phase of an offshore wind turbine.

IEC 61400 replaced the various national standards and forms a basis for global certification. In the United States, wind turbine design standards include IEC 61400 along with other ISO and ANSI standards. The U.S. National Renewable Energy Laboratory participates in IEC standards’ development work and tests equipment according to these standards [35]. Figure 10A.1 shows the applicability of some of the existing standards for the design phase of an offshore wind turbine. IEC Classification of Wind Turbines

IEC classifies wind turbines into three classes. Table 10A.1 shows the differences between the three classes [36]. The “reference wind speed” Vref is five times the annual mean wind speed, and the 50-year wind gust, is referred to as Ve50 [36]. Extreme wind conditions are characterized by their “return time,” A 50-year gust is one with a magnitude that is expected to occur at a specific location on average only once every 50 years. As defined in the IEC 61400-1, Ve50 is the maximum gust over a 50-year return period for a 3-second averaging time. This implies that for a turbine that is operating, the control system of the wind turbine is assumed to be able to pitch the blades in a feathered position, resulting in minimal rotor torque. If the wind turbine is shut down or parked at the wrong angle to the wind due to a turbine-related fault, then the turbine may have to withstand even greater loads. However, since the

232

Effect of High Winds on Wind Turbines Table 10A.1 IEC Wind Classes Class 1 High Wind

Class 2 Medium Wind

Class 3 Low Wind

Reference wind speed, Vref

50 m/s

42.5 m/s

37.5 m/s

Annual average wind speed (maximum), Vave

10 m/s

8.5 m/s

7.5 m/s

50-year return gust, Ve50

70 m/s

59.5 m/s

52.5 m/s

one-year return gust

52.5 m/s

44.6 m/s

39.4 m/s

probability of extreme gusts occurring while the wind turbine has a fault is small, the required withstand is not increased further from the level it should withstand when it is generating power. In addition to the above, IEC defines several transient events turbines must be designed to withstand. These include the following: •





Extreme operating gust (EOG): A decrease in speed, followed by a steep rise, a steep drop, and a rise back to the original value. The gust amplitude and duration vary with the return period. Extreme coherent gust (ECG): This is a sustained change in wind speed, again following a cosine-shaped curve with the amplitude and duration depending on the return period. Extreme wind shear (EWS): A transient variation in the horizontal and vertical wind gradient across the rotor. The gradient first increases and then falls back to the initial level, following a cosine-shaped curve.

These transient events are deterministic gusts intended to represent the extreme turbulent variations that would be expected to occur at the specified return period.

C H A P T E R 11

Structural Hardening of Power Systems against Storms

Introduction HIWs like those caused by hurricanes can cause extensive damage to the power infrastructure. Some hurricanes, like hurricane Wilma, which hit Florida and other states, have toppled more than 10 thousand distribution poles and hundreds of transmission structures. Some hurricanes like Rita, Katrina, and Sandy, in addition to their wind-inflected damage, caused major flooding, rendering substations and other equipment unusable for prolonged periods of time. Such damage to the infrastructure has caused outages affecting millions of people. In the aftermath of such severe hurricanes over the last 20 years, regulatory bodies have mandated that their utilities either adopt or investigate hardening options for their systems, based on detailed storm hardening plans. Such plans include detailed descriptions of the construction standards, policies, and procedures that the utilities use to enhance the reliability of overhead and underground electrical transmission and distribution facilities. Due to the much larger size of distribution systems compared to transmission systems, this chapter concentrates on hardening of the former. It discusses issues pertaining to the hardening of distribution poles. These include retrofitting poles inplace, replacing them, and developing a means to lessen the wind forces on them. It discusses vegetation management practices as contact with airborne vegetation has been found to be the major contributor source of outages in the storms. It covers the topic of undergrounding, which seems to be come up after every major storm, and presents its benefits as well as its potential disadvantages. In addition, the chapter summarizes the requirements of the NESC, which specifies the minimum requirements for these—even though several utilities choose to use even more stringent designs and approaches—and provides lessons learned from many utilities based on post-storm forensic analysis done by the utilities or myself. Only through forensic analysis of the performance of various designs and construction methods can rational decisions be made regarding whether present designs are adequate from a HIW perspective. This chapter also covers flooding due to such storms, along with lessons learned for measures to reduce the impact of flooding in substations, as restoring flooded substations from fresh or salt water due to the storm surges could be lengthy. This chapter also provides a list of recommendations developed based on previous storms, to act as a starting point for further investigation into system hardening 233

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Structural Hardening of Power Systems against Storms

to make an electric system less susceptible to damage during major storms. Subsequently, Chapter 12 delineates overall resiliency measures for power systems against major storms learned from recent major storms.

Physical Hardening of the Distribution System against HIWs Due to the relative size and breadth of distribution systems compared to the transmission systems, they take the brunt of damage from HIWs. In the United States, there are over 6.5 million miles of distribution lines,1 compared to just shy of 200 thousand miles of transmission lines operating over 200 kV. A recent survey by the Edison Electric Institute (EEI) showed that in 2013, its members spent $20.8 billion on distribution systems, a 3.5% increase over 2012 spending. The bulk of the increase in the capital expenditures went to storm hardening and improved system reliability, including undergrounding infrastructure. In consideration of the relative size of the distribution system plant, this section concentrates on distribution pole hardening against HIW. On the scope of hardening, it is cost-prohibitive to completely harden against major HIWs. Hence, utilities start with a targeted hardening approach of their distribution systems, which, when combined with a solid plan for quick restoration, can be effective in minimizing the impacts of HIW. Physical Hardening of Distribution Line Poles

Poles are the crucial structural elements in support of overhead distribution power lines (and various other public utilities), which carry voltages from 4.6 to 33 kV. The standard utility pole in the United States is about 12-m (40-ft) -long and is buried about 2m (6 ft) in the ground. However, poles can reach heights of 37m (120 ft) or more to satisfy clearance requirements. They are typically spaced (span length) about 38m (125 ft) apart in urban areas, or about 91m (300 ft) in rural areas. Jointuse poles are usually owned by one utility, typically the electric utility, which leases space on these for other utilities to place their attachments. In the United States, the NESC [1], published by IEEE2 sets the standards for the construction and maintenance of utility poles and their equipment. The NESC specifies best practices for the safety of the electric supply and communication utility systems at both public and private utilities. The code is a collaborative work and is frequently revised with significant input from the businesses and industries it serves. It contains minimum safety requirements for distribution lines and for distribution poles of any material. Most utility poles in the United States are made of wood with some type of preservative (against insects, rot, and fungi). Other materials that are increasingly being

1

Distribution substations connect to the transmission system and lower the transmission voltage to medium voltage. This medium-voltage power is carried on primary distribution lines, and after distribution transformers again lower the voltage, secondary distribution lines carry the power to customers who are connected to the secondary lines. The poles supporting distribution lines, meters measuring usage, and related support systems are also considered to be part of the distribution system. 2 Not to be confused with the National Electrical Code published by the National Fire Protection Association (NFPA).

Physical Hardening of the Distribution System against HIWs

235

used for utility pole materials include steel, concrete, and fiber-reinforced composite (FRC). Wood poles are also the oldest, with some as old as 80. Southern yellow pine is the most widely used species in the United States. (Other species in use include Douglas fir and jack pine.) This chapter focuses on the hardening of wood poles. Wind Performance of Poles

Wind force on a pole is due to the following three components (see Figure 11.1): 1) wind blowing on the pole itself, 2) wind blowing on the conductors (phase and ground wires), and 3) wind blowing on the pole-mounted utility equipment (e.g., transformers, fuses, and reclosers) and third-party equipment (for the other utilities). As shown in Figure 11.1, the three wind different forces listed above exert bending movements on the pole, the sum of which could create a resultant moment that that could bend the pole until it failed, typically at the ground line. Since the wind pressure on an object is proportional to the square of wind velocity, as the wind picks up speed the impact would increase nonlinearly on the pole. Typically, utilities limit the actual loadings to 20–50%, depending on the application of the pole, with the lower value for poles at highway and river crossings of the maximum calculated loading for an assumed maximum design wind speed. Hardening of Distribution Poles

A discussion on hardening poles should start by covering the codes that govern the minimum construction and strength requirements that utilities need to follow

Figure 11.1

Wind forces on a distribution pole.

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Structural Hardening of Power Systems against Storms

[2]. This, however, should be prefaced by the fact that historical experiences in areas that have been affected by HIWs have forced utilities to develop construction practices that often exceed the minimum strength and clearance requirements of existing codes. Utilities upgrade poles and structures with stronger materials. Certain pole and line design configurations are less susceptible than others to damage from trees and falling limbs. In the United States, the NESC specifies the loading criteria, such as those from wind and ice, and the strengths for power line structures. It specifies the horizontal and vertical loading from various combinations of ice and wind on poles, wires (conductors), transformers, and other components, with the most conservative ones covering the effect of ice on top of wind loading. Structures meeting NESC requirements can be considered safe but may not be hardened enough to sustain HIW gusts; it is also possible that they may not be economical. The NESC defines three different grades of safety requirements depending on installation: grade B, grade C, and grade N. Grade B has the most stringent requirements, and N has the least. Grade B includes poles located on limited-access highways (such as interstates), railroad tracks, and navigable waterways requiring waterway crossing permits. Grade C pole construction has been the most used construction standard at some of the utilities that were hit hard by Superstorm Sandy; however, some used wood cross-arm design stronger than what is required by NESC for grade C construction and used a grade B rated cross-arm designs. The NESC has three basic structural loading conditions that may apply to the different components of an overhead line. These are: district loading (Rule 250B), extreme wind (Rule 250C), and extreme ice with concurrent wind (Rule 250D). Rule 250B has been around since 1916 and is based on loading maps modified based on data from the U.S. Weather Bureau; see Figure 11.2. The loading district boundaries have been modified several times, including a revision to move the

Figure 11.2 NESC General loading map of the United States with respect to loading of overhead lines.

Physical Hardening of the Distribution System against HIWs

Figure 11.3

237

GO 95 Districts in California.

boundaries to align with certain state borders. California defines its own windloading conditions in General Order No. 95 (GO 95) specifications. See Figure 11.3 for the GO 95 districts in California. Rule 250C, added in the 1970s, accounts for a high wind loading conditions (without other weather conditions such as icing). It is based on a 2% annual probability or a 50-year return period. Rule 250C utilizes a series of maps produced by the American Society of Civil Engineers (ASCE) to illustrate the appropriate basic wind speed. Most of the continental United States has a 40-m/s (90-mph) basic wind speed with varying speeds along coastlines. When pole and tower structures exceed 18.3m (60 ft) above ground or water level, NESC requires that they be designed to withstand the extreme wind load calculated by (11.1). The wind pressures calculated by this equation would be applied to the entire structure and supported facilities without ice. In the following equation, units are provided in both the metric and imperial systems. Extreme Wind Load = k × V 2 × kz × GRF × I × Cf × A

(11.1)

where Wind load is in newtons (pounds) k

is the constant, wind velocity-pressure numerical coefficient, reflecting the mass density of air for the standard atmosphere [i.e., temperature

238

Structural Hardening of Power Systems against Storms

of 15°C (59°F)] and sea level pressure of 760 mm (29.92 in) of mercury. A value of 0.613 is typically used for k, except where sufficient climatic data is available to justify the selection of a different value of this factor for a design application. V

is the basic wind speed, a 3-s gust wind speed in meters per second at 10m (miles per hour at 33 ft) above ground.

kz

is the constant, velocity pressure exposure coefficient, as defined in NECS’s Rule 250C1, Table 250-2 V: basic wind speed of 3-s gust wind speed in meters per second at 10m (miles per hour at 33 ft) aboveground (NECS’s Figure 250-2).

GRF is the gust response factor, as defined in NESC 2017 Rule 250C2. I

is the importance factor, 1.0 for utility structures and their supported facilities.

Cf

is the force coefficient (shape factor) as specified in NESC 2017 rules 251A2 and 252B

A

is the projected wind area, in square meters.

One key parameter in (11.1), Cf, the force coefficient, differs if it is used for conductors or for the structures (towers and poles). •







For conductors or cables without ice covering, Cf is assumed to be equal to 1.0 as their projected area is assumed to be that of a smooth cylinder. For cylindrical structures and components, those having straight or tapered cylindrical structures, or structures composed of numerous narrow flat panels that combine to form a total cross-section that is circular or elliptical, Cf is equal to 1.0. For flat, nonlattice structures, those having structures or components in a square or rectangular shape, Cf is equal to 1.6. For latticed structures, square or rectangular latticed structures, or components, Cf is equal to 3.2 on the sum of the projected areas of the members of the front face if structural members are flat surfaced or 2.0 if structural surfaces are cylindrical.

See this chapter’s appendix for an application example of (11.1). Per NESC 2017, if no portion of a structure or its supported facilities exceeds 18m (60 ft) above ground or water level, the provisions of the above rule are not required. In the United States, several distribution lines, though under this threshold, use the more conservative NESC requirement reserved for the higher structures. The third NESC loading condition is the extreme ice with concurrent wind case, as defined by Rule 250D. This load case was added in 2007. NESC specifies that when the structure or its supported facilities exceeds 18m (60 ft) above ground or water level, the structure and its supported facilities should be designed to withstand loads associated with the uniform ice thickness and concurrent wind speed, as specified by NESC Figure 250-3, and the wind pressures for the concurrent wind

Physical Hardening of the Distribution System against HIWs

239

speed should be as indicated in Table 250-4. It also applies when a structure or its supported facilities exceeds 18.3m (60 ft) above the ground. The final NESC wind-loading calculations use two different rules. Both rules require that the load be multiplied by a load factor (see Table 11.1) and multiplying the ultimate pole strength by a strength factor (see Table 11.1). The load factor, sometimes referred to as the overload factor, is a safety factor that results in added strength. The NESC load factors increase the applied storm load on the pole based on the required construction grade. When an overload factor is reduced, the usable strength of the pole increases accordingly. For example, if a grade C pole with load is reduced by 50%, the pole can be subject to twice as much force without violating the new load factor. Since the wind force on a pole is proportional to the square of wind speed [see (11.1)], this means that the new rated wind speed is equal to the old rated wind speed times the square root of the allowed wind force increase. The application of the NESC strength factors decreases the efficient strength of the pole. The load and strength factors may be combined into a single overloadmultiplying factor that will used to multiply the load. NESC allows for the deterioration of wood structure strength, resulting in a specified strength for initial installation and a separate specified strength for at replacement. Engineered materials like concrete are assumed to not lose strength over time and therefore have a single specified strength. For wood, the NESC references the ANSI O5.1 for dimensions, tolerances, grades of materials, and the like. While the NESC specifies loads for analysis, the American National Standards Institute O5.1 establishes the capacity of the poles, as described in the following section.

Table 11.1 Load Factors for Structures (Towers and Poles) and Other Components to Be Used with the Strength Factors of Table 11.2. Grade C Grade B

At Crossings

Elsewhere

Rule 250B loads (combined ice and wind 1.50 district loading) Vertical loads

1.9

1.9

Transverse loads Wind wire tension

2.50 1.65

2.20 1.30

1.75 1.30

Longitudinal loads In general At dead-end

1.10 1.65

No requirement 1.30

No requirement 1.30

Rule 250C loads (extreme wind) Wind loads All other loads

1.00 1.00

0.87 1.00

0.87 1.00

1.00

1.00

1.00

Rule 250D loads (Extreme ice with concurrent wind) Source: NESC 2017, Table 253-1.

240

Structural Hardening of Power Systems against Storms Table 11.2 Strength Factors for Structures, and Other Components to Be Used with Load Factors of Table 11.1. Strength factors for use with loads of Rule 250B (combined ice and wind district loading) Metal and prestressed-concrete structures, cross-arms, and braces

1.0

1.0

Wood and reinforced-concrete structures, cross-arms, and braces

0.65

0.85

Fiber-reinforced polymer structures, cross-arms, and braces

1.0

1.0

Support hardware

1.0

1.0

Guy wire

0.9

0.9

Guy anchor and foundation

1.0

1.0

Strength factors for use with loads of Rules 250C (extreme wind) and 250D (extreme ice with concurrent wind loadings) Metal and prestressed-concrete structures, cross-arms, and braces

1.0

1.0

Wood and reinforced-concrete structures, cross-arms, and braces

0.75

0.75

Fiber-reinforced polymer structures, cross-arms, and braces

1.0

1.0

Support hardware

0.8

0.8

Guy wire

0.9

0.9

Guy anchor and foundation

1.0

1.0

1

Source: NESC 2017 Table 261-1. 1 Wooden cross-arms decay more rapidly than poles. Today’s cross-arms are expected to last much longer than those produced in the 1960s, 1970s, or 1980s due to new technologies in pressure treatment. There are typically higher numbers of cross-arm failures in comparison to pole failures. Some utilities have initiated a cross-arm replacement program to enhance storm resiliency. The use of fiberglass or composite cross-arms instead of wood cross-arms should be evaluated for circuits on limited-access rights of way. The fiberglass or composite cross-arms will keep their strength through their entire life, beyond that of the pole. The expected lifespan for a composite or fiberglass cross-arm is 60 years. Doing this will limit the number of cross-arm related failures in areas that are difficult to access, and these cross-arms should rarely have to be replaced before the pole.

Example Applications for NESC Rule 250C1

As an illustration of the application of NESC Rule 250 C for structures above 25m, consider the transmission tower in Figure 11.4. From (11.1), assuming wire wind pressure of 40 m/s, we can calculate the loads on both the phase conductors and the ground wires. Extreme Wind Load in newtons = k × V 2 (m/s) × kz × GRF × I × Cf × A ( m2 ) Wind Pressure on the Phase Conductors

For the phase conductors, h = 24m kz, the velocity pressure exposure coefficient, as defined in NECS’s Rule 250C1 and Table 250-2 (for the basic wind speed, 3-s gust wind speed in meters per seconds at 10m above ground) is equal to 1.20. GRF, the wire gust response factor, is determined using the height of the wire at the structure, h = 24m, wind design wind span of 400m, and NESC Table 250-3, is equal to 0.69.

Physical Hardening of the Distribution System against HIWs

Figure 11.4

241

Example tower for application of NESC Rule 250C.

I, the importance factor, is equal to 1.0 for utility structures and their supported facilities. Cf, the force coefficient (shape factor), as specified in NESC 2017 Rules 251A2 and 252B, is equal to 1.0. Extreme Wind Load in newtons = k × V 2 (m/s) × kz × GRF × I × Cf × A ( m2 ) Extreme Wind Load in newtons = 0.613 × 402 × 1.2 × 0.69 × 1 × 1 Extreme Wind Load in newtons ≈ 800 newtons/m2

Wind Pressure on the Ground Wires

For the ground wires, h = 32m Kz = 1.3; GRF = 0.65; I = 1.0; Cf = 1.0. Extreme Wind Load in newtons = k × V 2 (m/s) × kz × GRF × I × Cf × A ( m2 ) Extreme Wind Load in newtons = 0.613 × 402 × 1.3 × 0.68 × 1 × 1 Extreme Wind Load in newtons ≈ 870 newtons/m2

242

Structural Hardening of Power Systems against Storms

Wind Pressure on the Structure •



• •

The kz for the structure is based on the total structure height, h, 32m; therefore, from NESC Table 250-2, is equal to 1.20. The structure gust response factor, GRF, is also determined using the total structure height, 32m. Using NESC Table 250-3, is equal to 0.89. I is equal to 1.0. Cf for the structure is equal to 3.2.

Extreme Wind Load in newtons = k × V 2 (m/s) × kz × GRF × I × Cf × A ( m2 ) Extreme Wind Load in newtons = 0.613 × 402 × 1.2 × 0.89 × 1 × 3.2 Extreme Wind Load in newtons ≈ 3,350 newtons/m2

Differences between the NESC and the California GO 95

There are differences between the NESC and the California GO 95 in defining the various factors that must be applied to the pole-loading analysis to determine sufficient strength for the applied load. While the NESC uses load factors and strength factors, as explained above, GO 95 uses a single factor called the safety factor. The GO 95 safety factor augments the storm load on the pole. In either case, the standards specify that the applied load must be less than the efficient strength of pole for the load to meet the standard safety requirements. Tables 11.3 and Table 11.4 summarize the strength/load factor loading requirements for the NESC and the safety factors for GO 95, respectively. These are also illustrated in equations (11.2)–(11.5). For the NESC requirements, the guiding equations are For Grade B Storm Load × 2.5 < Pole Strength × 0.65 For Grade C Storm Load × 1.75 < Pole Strength × 0.85

Table 11.3 Summary of NESC Loading Requirements NESC Construction Grade

Load Factor

Strength Factor

Load Factor/ Strength Factor

B

2.5

0.65

3.85

C

1.75

0.85

2.06

(11.2)

(11.3)

Physical Hardening of the Distribution System against HIWs

243

Table 11.4 Summary of California GO 95 Loading Requirements GO 95 Construction Grade

Safety Factor

A

4

B

3

C

3

For California, GO 95 Grade A Storm Load × 4 < Pole Strength Grade B and C Storm Load × 3 < Pole Strength

(11.4)

(11.5)

Wood Pole Classes

It is the strength of the pole that determines if the pole can withstand the environment loading for the necessary level of reliability (grade of construction). Wood pole standards for construction and strength are described in ANSI Standard O5.1-2015 where the permitted stress level of various wood species must be determined by multiplying the designated fiber strength by the factors shown on Table 261-1 of the NESC. This standard uses the Imperial measuring system (British system), so it uses feet, pounds, and inches. Poles are classified by the ability to withstand load, as shown in Figure 11.5 and in Table 11.5. Wood poles are classified by their size and strength into pole classes (class 4, class, 3, class2, class1, class H1, class H2), with increasing pole diameter with decreasing class number. The pole’s bending strength is a function of the pole’s circumference. Small increases in the circumference of the pole yield nonlinearly higher bending strengths. The strength of a pole with a circular cross-section, at a specific location, can be approximated by the cube of the circumference at this location. The bending strength of the pole, as defined by the class of the pole, determines its load carrying capacity. Classification numbers have a requirement for the load the pole must be able to withstand 2 feet from the top of the pole. A pole’s height and class are typically abbreviated as h-c, where h is the height in feet, and c is the classification. This a 40-5, which is a 40-ft-long class-5 pole. Pole classes are defined so that poles of different wood species are equal in load-carrying capacity (ANSI 05.1 2015, Annex B). A pole of a species of wood with lower fiber strength would require larger dimensions to be considered the same class pole. The design process typically corresponds to picking the class of pole based on the required grade of construction, loading district, and the equipment/spans that the pole must carry.

244

Structural Hardening of Power Systems against Storms

Figure 11.5

ANSI 05.1 definition of bending pole bending load.

Wood poles are specified by their length, top circumference, and bottom circumference (measured 6 feet from the butt end). Lengths vary in 5-foot (1.5-m) increments from 25 to 110 ft (7.6–33.5m) and circumferences in 2-inch (5-cm) increments such as 15 and 17 inches (38 and 43 cm). Each class of pole has a minimum tip circumference. A class-1 pole, for example has a 27-inch (69-cm) minimum top circumference (greater top circumferences are also available). Increasing the pole class could be the most practical way to meet hardening criteria. Concrete poles have different classifications than wood poles. While wood poles use a numbering system, concrete poles use an alpha designation. For example, a class-2 wood pole, with a 3,700-lb. tip load may be considered equivalent to a classH concrete pole. Laminated wood poles are sometimes used as self-supporting poles where wood poles are not strong enough to withstand the loads.

Table 11.5

Excerpts from ANSI 051/2015 Annex B

Pole Class ANSI O5.1 2015

Horizontal Load (lbs.)

H5

10,000

H4

8,700

H3

7,500

H2

6,400

H1

5,400

Physical Hardening of the Distribution System against HIWs

245

Replacing Wood Poles with Steel (and other) poles

Following the extensive damage from hurricanes in the early 2000s, regulatory bodies in Florida, Texas, and other states asked their utilities to investigate and adopt hardening options for their systems. The same edict came from the regulators of regulators in the northeastern states affected by Superstorm Sandy. Based on these, several utilities moved away from wood to steel or concrete poles, among other materials [3]. Steel has an excellent strength-to-weight ratio and can be used for very strong structures. Beyond reliability and load capacity, steel poles offer several other benefits such as increased longevity and lower life-cycle costs. Figure 11.6 illustrates the difference in design methodologies between the wood poles and steel poles for several poles tested by EPRI and others in the 1990s. The vertical line in the middle of Figure 11.6 represents design loading criteria for pole selection. This line corresponds to the mean rapture strength of the wood poles (which is the basis for wood pole design) and represents the minimum strength of steel poles, which was the basis for steel pole design in the tests performed. The strength of the steel poles tested exceeded the minimum required strength determined by the loading requirement, illustrated by the vertical line in Figure 11.6. Even though in theory wood poles can have equivalent strength to steel, they cannot match their consistency; therefore, wood poles require higher strength factors as specified by the NESC. Wood poles also can experience loss of strength due to aging and can be weakened by natural causes (such as infestation), leading to their failures, which are sometimes sudden. Steel is a yielding material subject to different modes of failure. Whereas wood poles often completely break, steel poles tend to bend, leaving line conductors more intact. This feature also helps to prevent cascades. Steel towers have lower BIL than wood poles and are difficult to climb and susceptible to corrosion.

Figure 11.6

Comparison between wood and pole strengths.

246

Structural Hardening of Power Systems against Storms

Case History

As an example, one project at a major utility in the United States rebuilt an existing 16-km distribution line, where the existing wood poles for the whole line were removed, and in their place, taller steel poles were erected over existing trees, thus minimizing power outages due to falling branches during storms or high winds. Figure 11.7 depicts a replacement of a wood pole with a steel pole of the same height. In addition to steel, there are other options for distribution poles. These are shown in Table 11.6. In-Place Hardening Wood Poles

There are several ways to increase the strength of an existing pole without replacing it. Some of the most effective actions are simple and straightforward, such as adding structural reinforcement or bracing to existing distribution lines, such as in Figures 11.8 and 11.9. An extended-length steel brace can be driven below the ground line and extends above any third-party attachments. This can restore poles to their original strength and sometimes increase the strength of the pole by one or two pole classes. Typically, this could cost one-third or less of the cost of pole replacement, and a typical successful program can save a utility millions of dollars in replacement costs. Other pole-enforcement techniques examples include adding guy wires; see Figure 11.10. Adding transverse guys to existing poles transfers some the wind stress from wind forces from the pole to the guy wires (Figure 11.10). This is a very

Figure 11.7

A replacement of an H-frame wood pole with a steel one.

Physical Hardening of the Distribution System against HIWs Table 11.6

247

Alternative to Wood Pole Materials

Pole Material

Notes

Cast concrete

• Formed by pouring concrete into a form (typically rectangular) • Prestressed steel strands typically included to increase the strength • Less expensive than spun concrete

Spun concrete

• Formed by pouring concrete into a form (typically circular) with a hollow interior • Manufactured in a circular mold spun at a high speed to compress the concrete against the inner wall of the mold • Weighs less than cast concrete • Being round, it is less affected by wind

Steel/concrete hybrid

• Round steel pole mounted on a concrete foundation • Not as susceptible to corrosion as steel only poles • Like a steel tower, it has lower BIL than wood and is difficult to climb

Lattice

• High strength-to-weight characteristics and wind characteristics • High cost • Requires a foundation • Available in both steel and composite materials (but could be twice as wide as an equivalent wood pole due to mechanical considerations)

Composite

• Use becoming more common in areas subject to woodpecker and insect damage • Made by injecting an epoxy resin into a matrix of reinforcing such carbon fiber • High strength-to-weight ratio; no susceptibility to corrosion; and high BIL • More impact-resistant • Resistant to rot or decay • Free of toxic preservatives • Nonconductive • Resistant to woodpecker or insect damage • Virtually maintenance-free

Figure 11.8

Bracing of distribution pole partially damaged by storm.

248

Structural Hardening of Power Systems against Storms

Figure 11.9

Another bracing technique of distribution pole partially damaged by storm.

cost-effective option; however, proper field conditions need to be present to allow for such installations. Using Shorter Spans, Smaller Conductors, and Fewer Pole-Mounted Equipment and Attachments for Hardening Shorter Spans

The distance between poles (span) depends on several factors. In the design of a new distribution line, road intersections, among other things, dictate the location

Figure 11.10 Application of guy wires to existing distribution poles can increase their hardening.

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of some poles. After these are defined, other poles are filled in based on maximum allowable spans of the wire. On a long straight segment of distribution line, the span is dictated by the wires based on the ground and other clearances, not the strength of the pole. Wind blowing on the conductors generates forces (directly proportional to the span length) that are transferred to the poles at each end of the span. Half of the forces are transferred to each pole at the two sides of the span. Thus, reducing the span length would reduce the forces on the poles. Shorter spans, when practical, directly result in a more resilient distribution lines against high winds. This also allows for the use standard construction practices and materials. However, in some cases, span length required to meet extreme wind criteria results in many closespaced poles, which is not always possible and creates a negative visual impact. Smaller Conductors

As shown in the case history on the cascade of the transmission line in the 1980s, oversized conductors can cause toppling of structures. A large percentage of wind force on a pole is due to wind blowing on conductors. Therefore, conductors with smaller diameters reduce wind loading on poles. If ampacity calculations allow, it is worth considering the use of conductors with smaller diameters—strong, conductors to increase extreme wind rating without requiring exceedingly short spans or very strong poles. Using smaller conductors, though, has some drawbacks for ice loading, and hence, every case needs to be evaluated on its own merits. Pole-Mounted Equipment: Utility and Third-Party

Wind forces on pole-mounted equipment (such as transformers, fuses, and reclosers) or third party attachments can make the poles more vulnerable to high winds, as they transmit transverse wind forces. Their weights also add to the vertical on the poles. Thus they must be considered in the hardening analysis. As a result, attachments can significantly impact the maximum allowed span length. Using threephase transformers rather than three single-phase ones, or using a pad-mounted transformer rather than pole-mounted ones, can add more robustness to poles [5]. The presence of multiple attachments on distribution poles leads to greater vulnerability of the poles in extreme weather. Telephone and cable TV cables, and associated equipment, for example, are installed in multiples on many distribution poles. There are two types of forces that result from the attachments. One is a horizontal force on the pole due to wind pushing on the attachment wires. The other is an axial downward force on the pole at the attachment point due to the weight of the attachment wires. The multiple attachments create a higher risk of pole overloading, thus making a pole more vulnerable to failure. Attachments are also another aerial element that may be impacted by falling trees or limbs, creating more stress on the pole. Fewer attachments translates into a higher extreme wind rating that lessens the probability of failure during a hurricane. Removing thirdparty attachments can be an effective way to increase extreme wind ratings from an engineering perspective. Another option is to move equipment on a pole to a nearby stronger pole or one with a higher allowable wind rating. See Figures 11.11 and 11.12 for examples of pole-mounted utility equipment and third-party attachments.

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Figure 11.11

Example of pole-mounted utility equipment and third-party attachments.

Taking Advantage of Dead-End Structures

One mitigation measure used for electrical distribution lines is the use of dead-end structures. When a power line breaks, the unbalanced forces can break the pole and even cause a cascade. A dead-end structure has guy wires to prevent it from bending under normal loading and to support it when a line breaks. Dead-end

Figure 11.12

Example of pole-mounted utility equipment and third-party attachments.

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structures are intended to provide protection against a cascade for extreme ice and wind events. There are two types of dead-end structures, single-sided dead-end and double dead-end structures. A single-sided dead-end structure is the last pole on the line. If poles break near the single-sided dead-end structure (see Figure 11.13), the guy wires on the dead-end structure assist in keeping the dead-end structure upright. For a long line, a double dead-end structure may be inserted along the line to add strength, as well as to prevent cascading along the entire length of the line, also through the guy wires. Vegetation Management

Even if every pole and tower were upgraded to concrete or steel, we would still experience storm-related outages. The reason is that flying debris (such as roofs and road signs) and vegetation (such as falling trees and tree limbs) damaging poles—not the strong winds themselves. Thus, changing pole designs to meet extreme wind standards may unnecessarily increase costs without really improving the overall resiliency of the network. Per EPRI, power outages and other power disturbances cost the U.S. economy nearly $120 billion every year, and a large portion of this can be directly attributed to power outages triggered by overgrown vegetation on the right of way (ROW). The 2008 Edison Electric Institute Reliability Report said that 67% of electric outage minutes were weather-related. Inadequate level of vegetation management (tree trimming), and failure to manage tree growth in transmission ROWs of 345-kV and 138-kV lines were some the primary causes of the major 2003 Northeast blackout, one of the largest in U.S. history. Several large outages after HIW storms have been due to power lines being damaged, or even toppled, by high winds or airborne vegetation, including full trees. Following the 2003 blackout, the Commission designated the North American Electric Reliability Corporation (NERC) as the Electric Reliability Organization (ERO), with the responsibility to develop and enforce standards to ensure the reliability of the bulk power system,

Figure 11.13

Single-ended dead-end tower.

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including the reliability standard that addresses vegetation management covering tree trimming on rights-of-way, FAC-003-2, as contact with vegetation was identified as the initiating event of the 2003 blackout. Power lines operated above 200,000 volts (200 kV) and some transmission lines between 100 kV-200 kV are subject to FAC-003-2. FAC-003-2 requires that trees and other vegetation growing in or adjacent to the power line right-of-way be trimmed to prevent power outages caused by tree contact with a transmission line. This standard requires that trees and other vegetation growing in or adjacent to the power line ROW be trimmed to prevent power outages caused by tree contact with a transmission line but gives each utility the leverage of developing and implementing its own tree trimming or vegetation management plan. Nevertheless, the plans must conform to the requirements of the state or local authorities and any applicable ROW or easement agreement with property owners. Vegetation management for lower voltage distribution lines, such as the one shown in Figure 11.14, are controlled by the utility regulatory commissions within each state. These are typically the lines running in residential neighborhoods on wood or metal poles and usually operated at voltages between 4 kV and 36 kV. Most, but not, all tree trimming or vegetation management activities that directly affect homeowners involve local distribution, not transmission, and are, therefore, exclusively subject to state and local requirements and oversight. Scope of Vegetation Management

Vegetation management includes clearing vegetation and widening corridors to avoid trees (or branches) falling on power conductors and supports. Utility vegetation management actions typically include the expansion of existing ROWs, clearance of overhang in urban areas, and removal of dead or dying trees, or hazard trees; see

Figure 11.14 Trees and other vegetation growing in or adjacent to the power line ROW need to be trimmed to prevent power outages.

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Figure 11.15. During hurricanes, and other HIW storms, most vegetation damage is from falling trees located outside of the utility ROW. In many cases, transmission easement rights explicitly allow for the removal of hazard trees [6]. Active vegetation management methods include both mechanical and chemical or herbicide methods. Mechanical methods are most common. However, cutting and mowing vegetation have the undesired effect of causing vegetation to grow back thicker and fuller, thus requiring repeated applications. NESC Requirements for Vegetation Management

The NESC has been adopted by most public/state utility commissions and is used to provide direction and standards for electric utility companies. Rule 218 of the NESC has been interpreted as a set of guidelines that utilities use for defining their vegetation management activities and goals. Yet, Rule 218 has historically generated a large industry discussion regarding what it really requires. As an example, the use of the word “should” versus “shall” points to its application as a general guideline, not a mandate; see the following example from the 2017 NESC: “218. Vegetation management, A. General: Vegetation management should be performed around supply and communication lines as experience has shown to be necessary. Vegetation that may damage ungrounded supply conductors should be pruned or removed…” More importantly, Rule 218 does not specifically define and specify the clearances to be maintained between energized conductors and the surrounding vegetation. It was hoped that the 2017 version would be clarify such uncertainties, but it did not. Costs of Vegetation Management Vegetation management represents some of the highest recurring maintenance cost at utilities, and its deferral tends to be costlier overall. Vegetation management varies

Figure 11.15

Illustration of the danger posed by hazard trees outside the ROW.

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widely between utilities and even between their service areas based on vegetation density and growth rate. Vegetation management frequently competes for budget dollars and often faces strong public opposition—at least until major storm-related outages occur and a large number of utility customers are left without power, sometimes for several days. The vegetation management cycle for distribution ranges from five to 60 years and for transmission ranges from one to 10 years. Distribution vegetation management costs range from about $1,000 to $10,000 per kilometer and for transmission from about $200 to $7,000 per kilometer. In the United States, regularly scheduled transmission vegetation management is required under current standards set by NERC and the ISOS of the U.S. grids. The cost per kilometer of transmission vegetation patrol varies widely, from $10 to $50, with lower costs typically associated with aerial patrols and higher costs with foot patrols. Distribution vegetation patrol also differs widely from $1 per mile to almost $20 per kilometer. Today drones are being considered for replacing foot and aerial patrols at a much lower cost and more benefits. In June 2016, the U.S. Federal Aviation Administration (FAA) issued a final rule to allow increased commercial operation of drones [7]. However, the new FAA rules stipulated that drones may only be used in daylight and must be maintained an altitude of at most 120m (about 400 feet) above ground level. In addition, they need to be within visual line of sight of either the operator or an observer. While prior drone regulations limited commercial drone operation to FAA-licensed pilots, the new regulations specify that the pilots be at least 16 years old and possess a remote pilot airman certificate. While the FAA takes a cautious approach to the use of drones, it has included the option to apply for waivers. Utilities currently conduct most maintenance operations by visual inspection, but the new rule on the use of drones for utility applications begins to pave the way toward more cost-effective drone-based maintenance and vegetation surveys along the ROWs; see Figure 11.16. Lessons Learned on Vegetation Management Let’s review some important findings collected from different wind and winter storms with respect to vegetation management: •





Distribution pole failures during HIW storms were principally caused by fallen trees (secondary failures) and not due to the impact of the wind on the power delivery system directly (primary failures); see Figure 11.17. This is due to the risk from airborne debris and from trees outside the ROW, which can exceed the risk of trees within the ROW by factors sometimes exceeding a 3-to-1 ratio. To reduce the amount of tree-related damage that occurs during hurricanes, vegetation patrol programs should not only look for clearance violations, as these are not very effective in reducing HIW damage. Patrols must look for trees both inside and outside of the ROW that are likely to fall into structures or lines when subjected to high winds. Tree issues addressed by traditional utility vegetation management do not typically result in substantial hurricane benefits. Typical vegetation management is focused on maintaining a specified clearance between vegetation and

Physical Hardening of the Distribution System against HIWs

Figure 11.16

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Use of drones for vegetation management.









energized conductors in the ROW. During hurricanes, tree-related damage is typically due to entire trees falling over into lines and structures. Experience from past storms indicates that increased focus on hazard and danger tree removal is effective in reducing damage during wind storms. Effectiveness is increased if utilities have the ability, at a minimum, to condemn dead and diseased trees that can fall into the utility lines. For distribution systems, a direct correlation exists between the proximity of trees to distribution lines and the vulnerability of the lines to severe wind and winter storms, with tree-related failures increasing exponentially when wind speeds are more than 100 km/h (around 60 mph). Line-outage frequency is correlated with the number of trees-per-kilometer edge of the line and is less dependent on variables such as line and tree heights and clearance between the trees and line. Targeted vegetation management actions have been proven to be effective, especially in areas that have seen power reliability issues in the past. Several utilities routinely perform targeted reliability improvements that include a combination of vegetation management, along with selective undergrounding (see the section on undergrounding later in this chapter) along with other system enhancements. Revisiting in-place vegetation management programs periodically is vital to minimizing the effects of wind and winter storms on power lines. The use of

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Figure 11.17 Power lines throughout Louisiana become entangled in trees from Hurricane Gustav’s powerful winds and rain. (Source: FEMA.)







the results of storm damage (and subsequent restoration) is critical to modifying the necessary vegetation management programs and steps. This also allows a critical review of clearance standards and trim specifications. Several pole replacements in distribution systems are due to pole tops being rendered unusable when a tree hits the line, putting excessive force on the pole top pin insulator and mounting hardware. This results in splitting the pole tops and having to replace the whole poles. The problem occurs when the mounting bolts are oriented such that they are parallel to the phase wires. Coordinating with property owners and local officials for planting and replacing vegetation outside the ROW that have shorter heights, are slower growing, and have a longer lifecycle is important in reducing tree-related outages during storms. Applying analytics can improve vegetation management. Analytics can assist in tracking vegetation management practices in different regions and tree species at various times to maximize the return on investment, as measured in system reliability. The ability to track all these metrics on a geographic

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information system (GIS) with a vegetation management database and work history, coupled with a data-mining engine to develop business intelligence, has benefited utilities in tacking this major cause of storm-related outages. The smart grid (advanced distributed sensors, communications, and data networks) has enhanced condition-based maintenance and enabled intelligent vegetation management. A new concept is emerging in vegetation management—integrated vegetation management (IVM). IVM is defined as the practice of promoting desirable, stable, low-growing plant communities that will resist invasion by tall-growing tree species through cost-effective control methods [8]. These methods can include a combination of chemical, biological, cultural, mechanical, and/or manual treatments. An October 2016 memorandum of understanding (MOU) between the U.S. Environmental Protection Agency (EPA), the Edison Electric Institute (EEI), the U.S. Department of Agriculture (Forest Service), and the U.S. Department of the Interior (Bureau of Land Management, Fish and Wildlife Service, and National Park Service) helped establish sound IVM practices as the standard for utility ROW management.

Undergrounding of Overhead Infrastructure Undergrounding Distribution Lines

The conversion of overhead electric power distribution facilities to underground has been a topic of discussion for many years in the quest to harden against severe weather events, such as wind storms and hurricanes [9]. Underground equipment will typically not fail due to wind-related hurricane damage, and such damage will be minimal if flooding is not involved. However, underground systems are not immune flooding and storm surges, which can cause equipment failures and outages. Conversion of overhead electric distribution systems to underground is costly; the cost of converting existing overhead electric distribution lines and equipment to underground averages $500,00—50,000 per kilometer in addition to the cost of converting the services to individual homes and business. The costs for undergrounding residential main-trunk feeders’ range from $10,000 to $15,000 per residential customer affected and $20,000–40,000 per commercial customer affected. Such additional costs would require that electricity rates increase. Selected and targeted undergrounding can be an effective hardening investment strategy. It may be most cost-effective to use undergrounding for portions of a circuit that are harder to access rather than undergrounding main trunk lines. Selective undergrounding solves the problem that tree damage in remote areas of a feeder can prevent energizing the entire feeder. After a storm, selective undergrounding allows restoration crews to concentrate on the three-phase lines along roadways where large blocks of customers would be restored quickly. Potential Benefits of Undergrounding Electric Facilities • •

Lower storm damage and restoration cost; Fewer outages during normal weather and momentary interruptions;

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Structural Hardening of Power Systems against Storms • • •

Reduced live-wire contact; Lower vegetation management costs; Improved aesthetics.

Potential Disadvantages of Undergrounding Electric Facilities •



• • • •

Greater vulnerability to flooding and storm surges, and damage during poststorm cleanup. Figure 11.18, from FEMA shows a utility repairman restoring service to an area disrupted by Hurricane Sandy. Longer duration interruptions and more customers impacted per outage. For underground facilities, after flooding, once the water recedes, troubleshooting and restoration may take longer than with overhead distribution systems. Higher maintenance and operating costs. Stranded asset costs for existing overhead facilities. Increased exposure to dig-ins. Reduced flexibility for both operations and system expansion.

Undergrounding Transmission Lines

New underground transmission is approximately 10 times as costly as overhead [4]. New transmission is already required to be built to NESC extreme wind criteria; therefore, the benefit in moving from an extreme-wind-rated overhead transmission design to underground is not great, unless the difference is less than 5%. From the technical side, using underground cables rather than overhead lines adds high phase-to-ground capacitance and can, thus, be a source of high voltages, especially

Figure 11.18

A utility repairman restoring service to an area disrupted by Hurricane Sandy.

Approaches to Hardening Strategies against Wind Storms

259

during off-peak conditions, unless counteracted by other means, such as shunt reactors and static var generators. Though undergrounding of existing overhead infrastructure is not economically feasible, some utilities have considered targeted undergrounding projects, especially for lines serving critical infrastructure and selected backbone circuits.

Approaches to Hardening Strategies against Wind Storms While hardening objectives (reducing damage and shortening restoration time) are common among utility companies, hardening needs differ. Utilities seek to harden their systems while holding costs at justifiable levels to their regulators. As Superstorm Sandy has shown, no amount of reinforcement and preparation is able to completely avoid damage. Accordingly, structural hardening of the distribution system should focus on two objectives: (1) hardening of circuits that feed critical loads and load centers and (2) designing for quick restoration. To achieve this, hardening efforts should start with the hardening of substations, feeders, and circuits that serve critical infrastructures. These include those that serve facilities such as hospitals, fire and police departments, and water treatment plants. After feeders serving critical facilities and essential services are hardened, an analytical approach should be used to prioritize the remaining feeders. An evolving hardening strategic concept revolves around designing the system for quick restoration as the primary objective [2]. This more pragmatic approach admits upfront that no amount of reinforcement and preparation will completely avoid damage from certain events, whether they are category 4 hurricanes or F5 tornadoes. Economic steps can be taken to make key elements of the system, particularly the societally critical circuits, faster to repair and restore when downed. Examples of such measures supporting this strategy include the following: •





• •

Limiting the number of individual circuits per pole line. A pole like the one shown in Figure 11.12 makes more residents prone to outages if it is damaged Adding more ground-level manual switches that do not require lift trucks top to operate. Reexamining feeder and loop topologies to reduce the number of customers impacted by a single point of damage, taking, for example, the following measures. – Splitting up some of the larger reclosure loops; – Relocating switching and overhead equipment; – Placing lateral fusing to reduce cascading outages; – Designing circuit configuration to limit the number of customers affected by a line outage through adding automated, remotely controlled switches or manual switches to targeted circuits to provide more flexibility to isolate damage areas and restore customers by switching to alternate supplies. Reducing feeder segment size. Adding isolation devices on open-wire feeders and improving auto-loop designs that allow the feeding of power from multiple points along the feeder circuit.

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Hardening of critical poles. Critical poles include poles with capacitor banks, autotransformers, reclosers, voltage regulators, and automated switches. Damage to critical poles impedes restoration and is difficult or expensive to repair.

Hardening against Floods and Storm Surges For the grid, flooding could be one of the worst types of extreme weather events covered in this book because of the long-term damage that floodwater can do to power substations and to underground electrical systems. Floods can be most broadly grouped into flash floods, river floods, and storm surges, with the main difference being the onset of the flooding. Storms, tropical cyclones, and other maritime extreme weather can also produce deadly storm surges, as in the case of Superstorm Sandy in 2012, Hurricane Katrina in 2005, Cyclone Sidr in November 2007, and Cyclone Nargis in May 2008. Flash floods and storm surges are usually the most damaging with heavy downpours or seawater surges that can lead to gushes of water that turn dry flood plains into raging torrents in minutes. With flash floods and storm surges, there is often little warning that flooding will occur, and infrastructures in the water’s path can be destroyed quickly and roads can become impassable. Flooding can cause severe damage to substation equipment and may lead to interruptions in service continuity and widespread outages. Superstorm Sandy involved both fresh water and saltwater, from the storm surge, flooding. During Superstorm Sandy, flooding of the underground power infrastructure in New York City led to extensive power disruptions. Substation Flooding Concerns

Flooding affects many aspects of the power system, but is a major concern to substations; see Figure 11.19. Flooding becomes a problem for substations when the amount of water reaching the drainage network exceeds its capacity [10]. Flooding can cause severe damage to substation equipment and may lead to interruptions in service continuity and widespread outages. Large amounts of water, rust, and mud left trapped behind a flood in a substation can make repair of the equipment a sizable and lengthy restoration task. Restoring a flooded substation takes much longer than restoring a downed power line that was damaged by ice or wind. Utility restoration crews must deal with the large amounts of water, rust, and mud left trapped in the structure. Switchgear, relay panels, transformer fans, pumps, and control kiosks are among the pieces of substation equipment most susceptible to flooding. The problem with the cables can become even more acute when flooding is from saltwater. Saltwater flooding creates additional challenges to the infrastructure. Prolonged saltwater exposure can damage cables, motors, metal fasteners, and electronic parts and can cause short circuits. Clean-up from saltwater flooding is lengthy and labor-intensive and involves inspecting all the affected areas, evaluating damage, and cleaning and repairing damaged equipment. Repairing or replacing some equipment is not always easy as a lot of the equipment is aged (some more than 50 years old) and obsolete. Once the water is pumped out, more

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Figure 11.19 Flooded substation and transmission lines by a flooded river in North Carolina. (Source: FEMA.)

slow-moving work begins: inspections, drying with fans or blowers, and cleaning to make sure that the saltwater that entered the structure is removed. Flooding also presents some unique problems for urban secondary network systems. In addition, transmission and subtransmission systems can be affected by flooding in terms of compromising tower integrity or in the case of fast moving water. Hardening Substations against Floods

For existing substations, there are limited measures available for hardening against floods. One entails installing, when possible, permanent barriers, typically a continuous wall 1–1.25m (~ 3 ft) high made of concrete blocks at the side or sides of the substation most vulnerable to flooding. When permanent barriers are not possible, relocatable (nonpermanent) barriers can also been used. These can be made of many materials, including steel, concrete (like that used in traffic and security barricades), or water-filled plastic. For new substations, industry standard substation site design is to avoid significant impacts from flooding at the 100-year flood elevation, plus a third of a meter (1 ft). This methodology is feasible for most substations (i.e., inland or noncritical) but should be modified for critical substations and/or coastal substations, which may have unique risks. After identifying critical substations, different levels of flood mitigation can be employed for those whose locations have been finalized. One solution is raising the critical equipment (or for smaller substations, raising

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the whole substation) by several meters. Some of the most vulnerable components in the substation are the control wiring in the lower cubicles of the control house, which may contain essential protection and control schemes. Water damage to those components during severe flooding could result in the outage of the substation or a large percentage of it. For this reason, some utilities that design for the possibility of floods have required special designs for the control panels on equipment support structures. The control panels are mounted 1–4m above ground level, making access ladders necessary. In addition, some utilities have used special control cables with humidity-protective layers able to withstand long-term water immersion. For distribution substation applications, a proven approach has been to combine the costeffectiveness of modular equipment solutions with the storm hardening concept of elevated substations. At medium voltage levels, many modular substation designs are available that can be installed on elevated foundations, platforms, or stilts. Elevating an entire conventional transmission substation is very challenging, if possible, due to the amount of space required for increased electrical clearances at higher voltages. Elevating substations with indoor gas-insulated switchgear can be done. As far as flooding from hurricanes is considered, some substations along the Gulf of Mexico have been elevated as much as 7–8m (~25 ft) based on flooding predictions for a category 3 storm. The costs for elevating substations to category 4 or 5 storm surges are prohibitive, and utilities in such cases typically invest in spare equipment to address such flooding risks. Lessons Learned for Measures to Reduce the Impact of Flooding in Substations

If a major storm such as a hurricane is imminent, then certain preparatory steps can help diminish the risk of power interruptions in substations due to flooding and to enhance personnel safety. Depending on the size of the substations and the risk of flooding, certain measures can help diminish the risk of power interruptions in substations due to flooding, such as the following: •





• • •



Ensuring that all substation drawings and prints are stored in a location that will remain dry; Cleaning the grounds in and around the substation from debris and materials so that water runs off freely; Consolidating load on the minimum number of energized transformers (to minimize damage from through faults) during the event; Removing relays that are not in use; Waterproofing equipment as much as possible when practical; Sealing and waterproofing (as much as possible) items such as tap changes and motors for motor-operated switches; Hardening lead-acid cells (e.g., sealing and plugging their vents).

Lessons Learned from Post Substation Flood Actions

Although many substation elements can be flooded, here we discuss restoration measures for only two elements: circuit breakers and transformers.

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Circuit Breakers

When equipment is flooded, the damage inflicted on the power circuit breakers can be the most severe, since circuit breakers operate at very high speeds and with great precision, making them sensitive to contamination and improper lubrication. This applies to metal-clad switchgear as well as outdoor circuit breakers for HV systems. Repairing flood-damaged breaker mechanisms can be a challenge. Metalclad switchgear breakers typically use a motor-driven, spring-charged mechanism and air-magnetic or vacuum arc interruption. Outdoors, HV breakers use hydraulic, pneumatic, or solenoid mechanisms and air, oil, or SF6 interruption media. The following are some actions that should be taken for the restoration of breakers after they are flooded: •



• • • • •









Disassembly of the mechanism, removal of the residue, brushing away of the rust, and removal and replacement of mud-contaminated lubricants; Thorough inspection and cleaning of all bearings, pins, cylinders, O-rings, latches, triggers, air control valves, and compressors (total disassembly and replacement of all the soft seals and replacement of any damaged ones); Testing of all control wiring, without exception; Replacement of all the gaskets and pressure-relief safety valves; Replacement of trip coils; Cleaning of motors and replace bearings; Replacement of all molded-case, low-voltage breakers (due to the vulnerability of the insulation to water damage; Repair of medium-voltage oil circuit breakers if repair costs do not exceed 50% of the cost of new ones (if so, replace); Replacement of chutes of air-magnetic breakers, since it may be impossible to clean them thoroughly; Checking SF6-insulated switchgear for water ingress, even though it is typically immune to flood damage; Performance of power factor and travel timing tests for all breakers above 34 kV.

Transformers

The following actions should be taken for the restoration of transformers subjected to flooding: •

• • •

Clean, drain, flush, and lubricate gearbox and gear trains for transformer load tap changers and clean or replace motor bearings; Check and replace voltage-regulating relays as needed; Clean and test all electrical wiring and connectors in auxiliary control cabinets; Clean motors and replace bearings in forced-air cooling fans. In addition to the above, a detailed visual inspection, winding integrity, and oil tests need to be completed before the transformer is returned to service.

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Summary and Conclusions Electric utilities affected by previous storms have invested heavily in storm preparedness planning, pole inspection programs, vegetation management, and voluntary collaboration in regional mutual assistance groups. They have acquired fleets of mobile substations and stocked spare transformers and equipment necessary for rebuilding after major storm. System hardening and resiliency cover the activities needed to make a system less susceptible to damage during major storms to decrease the number of customers who could experience power interruptions or lack of essential services during major storms. While the objective of hardening may be common among utility companies, the hardening needs of the different utilities differ. As Superstorm Sandy has shown, no amount of reinforcement and preparation is able to completely avoid damage; thus, structural hardening of the distribution system should focus on two objectives: hardening of circuits that feed critical loads and load centers and design for quick restoration. Cost effective hardening approaches should start with the hardening of substations, feeders, and circuits that serve critical infrastructures such as hospitals. After feeders serving critical facilities and essential services are hardened, an analytical approach should be used to prioritize the remaining feeders. The most common hardening practices that utilities have been implementing include replacing wooden utility poles with poles made of steel, concrete, or a composite material; upgrading transmission towers from aluminum to galvanizedsteel lattice or concrete; and installing guy wires, and other structural supports. The NESC does not require the majority of distribution structures are to be able to withstand hurricane-force winds. However, it is worth considering the possibility of using designs above minimum code standards to reduce damage during extreme wind conditions. Even after taking pole-hardening measures, it is still possible to experience storm-related outages. The reason is that flying debris (such as roofs and road signs) and vegetation (such as falling trees and tree limbs) are the primary causes of distribution-pole damage during a storm, not strong winds themselves. In highwind situations, the risk of airborne debris coming from trees outside the ROW can exceed the risk from trees within the ROW by a factor of 3 or 4 to 1. Thus, changing pole designs to meet extreme wind standards, without paying close attention to vegetation management, may unnecessarily increase costs without really improving the overall resiliency of the network. The undergrounding of distribution systems does work nicely in certain situations, such as at intersections of major highways. Underground equipment does not typically fail due to wind-related hurricane damage, and damage to it is minimal if flooding is not involved. Nevertheless, burying cables is not the best answer in all cases. During the hurricane season of 2005, flooding of underground facilities delayed restoration. The other concern during major storms is flooding. Flooding affects many aspects of the power system, but it is of particular concern to substations in flood zones or coastal areas prone to storm surges. Flooding can cause severe damage to substation equipment and may lead to interruptions in service continuity and widespread outages. Large amounts of water, rust, and mud left trapped behind a

Selected Bibliography

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flood in a substation can make repair of the equipment a sizable and lengthy restoration task. Fortunately, the lessons learned from utilities that have recovered from floods can be invaluable. The best advice is to plan for the risk of flooding and to put necessary plans and measures into action—before the last minute. In conclusion, certain preventive measures and preparatory steps can help diminish major storms’ impacts and reduce restoration times. To devise steps to diminish the impact of extreme weather impacts, it is necessary to understand the risks and to adjust system design, asset management, and operating practices accordingly.

References [1]

The Institute of Electrical and Electronics Engineers (IEEE), “2017 National Electrical Safety Code (NESC) C2-2017,” April 2016. [2] Abi-Samra, N., et al., “Hardening the System,” Transmission & Distribution World Magazine, February 2013, pp. 30–34. Also, http://tdworld.com/vegetationmanagement/hardening -power-grid-20130201/, 2013. [3] Abi-Samra, N., “Impacts of Extreme Weather on Power Systems and Components,” EPRI Report 1017901, 2009. [4] Abi-Samra, N., “Impacts of Extreme Weather Events on Transmission and Distribution Systems Case Histories, Lessons Learned and Best Practices,” EPRI Report 1020145, 2010. [5] Abi-Samra, N., et al., “Sample Effects of Extreme Weather on Power Systems and Components, Part I: Sample Effects on Distribution Systems,” Proceedings of the Power and Energy Society General Meeting 2010, July 2010. [6] Abi-Samra, N., “Utility Vegetation Management Optimizes Reliability,” Electric Light & Power Magazine. Also available on line, http://www.elp.com/articles/powergrid_ international/print/volume-19/issue-1/features/utility-vegetation-management-optimizes -reliability.html, 2013. [7] “How the FAA’s First-Ever Commercial Drone Rules Could Affect Power Companies,” Power Magazine, http://www.powermag.com/how-the-faas-first-ever-rules-could-affect -drone-operating-power-companies/, 2016. [8] Kenneth, L., for Edison Electric Institute, “Out of Sight, Out of Mind 2012: An Updated Study on the Undergrounding of Overhead Power Lines,” http://www.eei.org/ourissues /electricitydistribution/Documents/UndergroundReport.pdf, 2013. [9] United States Environmental Protection Agency (EPA), “Integrated Vg Management (IVM) Practices around Utility Rights-of-Way,” https://www.epa.gov/pesp/integrated-vegetation -management-ivm-practices-around-utility-rights-way, 2016. [10] Abi-Samra, N., and W. Henry, “Before and After a Flood,” IEEE Power and Energy Magazine, Vol. 9, No. 2, 2011.

Selected Bibliography Abi-Samra, N., “Extreme Weather Effects on the Energy Infrastructure,” http://www.cctc2013. ca/Papers/CCTC2013%20EXT1-3%20Abi-Samra.pdf, 2013. American Society of Civil Engineers. “Overview of Electricity Infrastructure. Failure to Act: The Economic Impact of Current Investment Trends in Electricity Infrastructure,” 2012. American Petroleum Institute, “Hurricanes and the Oil and Natural Gas Industry Preparations,” http://www.api. org/news-and-media/hurricane-information/hurricanepreparation.

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Blake, E. S., et al., “Tropical Cyclone Report: Hurricane Sandy,” National Hurricane Center, 2013. EPRI Underground Transmission Systems Reference Book—2006 Edition, Palo Alto, CA: EPRI, 2006. Federal Energy Regulatory Commission (FERC) and North American Electric Reliability Corporation (NERC), “Report on Transmission Facility Outages During the Northeast Snowstorm of October 29–30, 2011: Causes and Recommendations,” http://www.ferc .gov/legal/staff-reports/05-31-2012-ne-outage-report.pdf, 2012. Florida Power & Light Company. “FPL Announces Plan to Accelerate Strengthening of Florida’s Electric Grid during Annual Storm Drill,” press release, 2013. Hines, P., J. Apt, and S. Talukdar, “Trends in the History of Large Blackouts in the United States,” Proc. 2008 IEEE Power Energy Soc. General Meeting, July 2008, pp. 1–8. Henry, R., “National Science Board Workshop, Task Force on Hurricane Science and Engineering,” Institute for Human and Machine Cognition Pensacola, Florida, April 2006. NERC, “High-Impact, Low-Frequency Event Risk to the North American Bulk Power System,” a Jointly Commissioned Summary Report of the North American Electric Reliability Corporation and the U.S. Department of Energy’s November 2009 Workshop. Liu, Y., and C. Singh, “A Methodology for Evaluation of Hurricane Impact on Composite Power System Reliability,” IEEE Trans. Power Syst., Vol. 26, No. 1, 2011, pp. 145–152. Office of Electricity Delivery and Energy Reliability, U.S. Department of Energy, “Hardening and Resiliency: U.S. Energy Industry Response to Recent Hurricane Seasons,” http://www .oe.netl.doe.gov/docs/HR-Report-final-081710.pdf, 2010.

CHAP TE R 12

Grid Resilience Introduction “Grid resilience” is defined in Presidential Policy Direction 21 (PPD-21) [1] as “the ability to prepare for and adapt to changing conditions and withstand and recover rapidly from disruptions. Resilience includes the ability to withstand and recover from deliberate attacks, accidents, or naturally occurring threats or incidents.” The National Association of Regulatory Utility Commissioners defines grid resilience as “robustness and recovery characteristics of utility infrastructure and operations, which avoid or minimize interruptions of service during an extraordinary and hazardous event.” From either definition, resilience of the power grid is a very important topic when one discusses natural events such as the extreme weather events covered in this text or cyber or physical attacks against the grid. The importance of latter two risks has been made evident by events that have occurred over the last few years. This chapter starts with a discussion of Superstorm Sandy, then turns to the subject of resilience. It discusses lessons learned from Sandy, which should supplement lessons learned from the previous chapters. The destruction that resulted from Sandy, namely the storm’s impacts on the power grid including critical infrastructures, prompted discussions of system resilience. In addition, this chapter details some applications of microgrids, distributed energy resources (DERs), and PV systems, which came more into the spotlight after Sandy as elements of resiliency against storms. However, a widespread use of DER (wind, solar, and energy storage) as well other grid modernization aspects introduce cybersecurity concerns for the grid. At the same time, however, the islanding operations and black-start capability of microgrids with DERs are useful if the broader grid goes down due to a cyber or physical incident. As shown in previous chapters, hardening against extreme weather includes undergrounding of circuits, upgrading poles and towers to withstand hurricaneforce winds, providing flood protection for substations, and using technologies that minimize the potential impacts of a major weather event. However, such measures should be supplemented by hardening of critical physical components and cybercomponents of the power infrastructure to ensure that these systems remain operational during, and after, extreme weather events, while not introducing new failure modes. Accordingly, this chapter discusses factors that increase system resiliency against extreme weather events and touches on new threats: cyberattacks and intentional physical attacks on the grid.

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Superstorm Sandy Hurricane Sandy (unofficially referred to as Superstorm Sandy) was the most destructive hurricane of the 2012 Atlantic hurricane season and the second-costliest hurricane in U.S. history. Sandy slammed into the eastern seaboard on October 29, 2012, causing widespread power outages due to damage from high winds and flooding, both from fresh and salt water. The impacts of Superstorm Sandy were witnessed in 24 states, including the entire eastern seaboard from Florida to Maine and west across the Appalachian Mountains to Michigan and Wisconsin, with particularly severe damage in New Jersey and New York. Over 8.5 million customers experienced power outages. In New England, Hurricane Sandy severely impacted many regions with record winds and storm surge, resulting in a 4.3-m (14-ft) storm surge in Manhattan at the Battery monitoring station. Large swaths of New York City were without power due to preemptive shutdowns and severe flooding. As of October 31, over six million customers were still without power in 15 states and the District of Columbia (as restoration was hampered by several factors including a winter storm that hit the region affected by Sandy), with nearly four million of these in New Jersey and New York alone. In fact, over a week later, more than 1.3 million were without power [1, 2]. See this chapter’s appendix for more information on Superstorm Sandy. Physical damage to the distribution system caused by Sandy included broken poles and crossarms, broken or damaged insulators, conductor (phase and static) wire damage, flooding of substations, and flooding of ground-mounted and underground electric equipment including damaging salt water intrusion. The electric system sustained significant damage; see Figures 12.1 and 12.2. The transmission side of the system was not as severely affected as the distribution system; the most significant problem for distribution centered on HV lines and the need to take lines out of service to prevent major equipment damage. In addition to the energy electric sector, Sandy affected other utilities such as gas, communications, and water. Some natural gas lines broke causing fires in some locations. Also, the U.S. Federal Communications Commission (FCC) reported that 25% of cell sites across 10 states and Washington, D.C., were out of service. This

Figure 12.1

Sample of damage by Superstorm Sandy.

Superstorm Sandy

Figure 12.2

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Sample of damage by Superstorm Sandy. (Source: FEMA.)

brings to light the issue that stronger sector interdependencies may trigger cascading events. The topic of tightly entwined operations among critical sectors had been raised in the aftermath of other major storms. Despite extensive planning, energy disruptions in some areas brought transportation, communication, and water services to a halt. The increasing interdependence and integration among infrastructures has created hidden risks that are not widely understood. The complex networks of interconnected infrastructures in and between geographic areas have allowed outages to trigger cascading events in unexpected ways. Utility Preparations for Superstorm Sandy

Based on a report by the North American Electric Reliability Corporation (NERC) on Superstorm Sandy [3], utilities, generation owners, grid operators, and other stakeholders, coordinated within the area forecasted to be impacted worked to ensure that sufficient numbers of additional field operation crews were scheduled and available to respond to the expected storm disruptions. Where possible, previously scheduled outages were postponed to ensure that facilities were available during Sandy; generators were advised to be ready for abnormal dispatch instructions, and black-start units readied to run for an extended duration. In addition, the utilities activated existing storm preparation plans and put many of the transmission lines and generation assets that had been out of service back on-line. In the meantime, major substations were staffed with qualified personnel to provide situational status to emergency operations center; loose equipment and materials were inspected and secured; the operational status of roof and sump pumps were inspected and confirmed; and sandbags and barriers were deployed. In addition, planning for quick restoration, utilities in the line of Sandy acquired critical materials, contacted service vendors, and scheduled additional field resources. On the protection side,

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threatened utilities confirmed the status of special protection systems (SPSs) and implemented dynamic reratings for key facilities. Power Restoration

In the weeks after the storm, public officials criticized utilities for their slow restoration times. An analysis one month after the storm showed that power restoration occurred faster than average, even though Sandy was worse than any storm East Coast utilities had ever faced. However, additional data has shown that the full power restoration took more than twice as long following Sandy than it did following Hurricane Irene [4]. Figure 12.3 compares the progress of power outage restoration following Hurricanes Irene and Sandy. With Hurricane Irene, utilities restored 70% of the peak reported outages after only three days and 95% after five days. In the case of Sandy, outages from peaked on October 30, 2012, and after three days only 57% of the peak was restored; six days later, power had been restored to 84%. Power restoration after Sandy was delayed due to a powerful winter storm, the November 2012 northeaster or nor’easter, which brought significant early season snow to the northeastern United States, slowing the progress of utility crews and adding outages. Many of the areas hit by the nor’easter had been affected by Superstorm Sandy days before, which further complicated recovery efforts. Before the nor’easter, restoration had reached more than 90%. Other impediments to fast restoration of power after Sandy included the loss of power to control facilities as well as obstructed accessibility to substations and transmission lines because of

Figure 12.3 DOE.)

Comparison of power outage restoration percentages by storm. (Data from: U.S.

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fallen trees and equipment damage from salt water and flooding. Fuel for crews and emergency generators was also a challenge in some areas of New York and New Jersey areas following Hurricane Sandy. On the supply side, Sandy impacted fossil, and nuclear generation in the states over which it passed. In fact, some fossil generation units were forced off the grid both before the storm (in anticipation of potential flooding), or as the result of flooding or being unable to stay on line due to feeder conditions (such as severe fluctuations feeder voltage, frequency, and reactive power). As a result, 17 GW of generation capacity became unavailable. On the nuclear generation side, several nuclear units were affected by Sandy for a variety of reasons including the loss of transmission system load, transmission HVs, and loss of off-site power. Other nuclear generation plants in the area, while not impacted directly by Sandy, were off-line for refueling prior to the storm.

The Inherent Resiliency of the Power Grid Before we discuss system resiliency, we need to make a note on the inherent resiliency of the power grid. The bulk power system in the Unites States, and in most developed countries, is highly redundant and planned with sufficient resources to accommodate contingencies, some severe. The United States has 150 balancing areas, with each tasked and capable of maintaining system reliability even with the loss of more than the single largest generating unit in the area. Various planning tests stress the resilience of the grid to accommodate a wide range of severe multiple contingency conditions without resulting in cascading outages. Even with this inherent resilience, certain key nodes, if damaged, would have a greater impact on system restoration than others. As the grid becomes smarter, grid-communicating devices are enabling unprecedented situational awareness and operational efficiency gains. While these advances have resulted in many operational and economic benefits they have resulted in a reduction in the redundancy of the system, which can affect its resiliency against threats like extreme weather.

Defining System Resiliency Several lessons have been learned from the response to and recovery from Superstorm Sandy and other major storms of the last two decades. This chapter summarizes some of these lessons as part of an overall roadmap to enhance resilience of the grid. The first step to adequate resiliency is the acknowledgment that fully protecting the power system from extreme weather is not possible. In its simplest form, infrastructure resilience is the ability to reduce the magnitude and/or duration of disruptive events. System resiliency has four elements: •

Hardening: The ability to absorb shocks and continue operating through hardening of components;

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Ride-through: The ability to manage a crisis as it unfolds and maintain some basic level of electrical functionality without totally collapsing; Rapid recovery: The ability to get system and services back as quickly as possible; Adaptability: The ability to learn and incorporate lessons from past events to improve resilience for future events.

The following sections discuss some of the main attributes of each of the above four elements of system resiliency as highlighted by Superstorm Sandy and other major storms, each leaving millions of residents without power, sometimes for extended periods of time exceeding several days. An understanding of these elements of resiliency supplements the lessons learned from the previous chapters. Hardening Modeling Issues

The first step to hardening any system starts with good modeling. Better transmission and distribution line damage prediction models improve utilities’ ability to predict potential storm damage and to enhance, and focus, system restoration plans. Better models can predict facility susceptibility to high winds, flooding, or other extreme weather. Better models can reduce outage times. They are also useful for sensitivity analyses of potential resilience improvements and prioritizing future investments. Better weather forecasting can improve emergency preparedness in prestaging of resources and equipment before the storms. Planning of Systems and Components

There are a number of issues that utilities need to consider for hardening their systems against extreme weather events. When designing a new system or addition, utilities should focus on building in ability to fail gracefully (e.g., SCADA systems designed to lose up to 30% of power in 10% incremental stages) and recover rapidly in case of outage. Resilience should be planned into a system based on analysis of severe contingencies. Where possible, utilities should install new major electrical infrastructure, including substations, outside flood areas. Increasing the inventory of key power components (e.g., EHV transformers and protective relays) is also essential. For new transmission lines, it is important to implement double deadend structures to limit cascading events on distribution and transmission lines. It is further recommended that spare HV transformers not be colocated with those they are intended to replace to protect them from fires that could be initiated by the failed units. On the technology side, utilities can now use many solutions that were not available before. These include deploying a combination of grid modernization technologies along with traditional hardening of targeted infrastructure to optimize resilience and improve power restoration efforts. For example, utilities should leverage AMI to facilitate power restoration and integrate new field intelligence systems (processes, tools, and data) to locate outages more accurately. This necessitates the

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use of advanced communications channels and capabilities to increase the accuracy of estimated times and enhance monitoring and control capabilities to effectively dispatch distributed energy resources. Other measures include installing additional sectionalizing switches for better isolation of flood-prone areas. In addition, managing the vegetation around transmission and distribution lines is necessary, as indicated in earlier chapters. Resources, Processes, and Human Factors

To be ready for major storms, establishing and continually updating a storm risk management committee and emergency response plan is recommended. Drilling the plan once or twice a year and performing unannounced emergency drills for control centers have also been noted to be very effective, as is the testing of the primary and backup systems that monitor and control key points on the grid. It is also advisable for utilities to develop and conduct joint exercises with local and governmental agencies of emergency response plans to improve coordination among infrastructure sectors and government. Furthermore, restaging of replacement equipment has been shown to advance a speedy recovery. On the operational side, utilities should update critical load requirements and develop replacement power to them and establish emergency operational agreements with critical customers. To speed up restoration, utilities should establish plans to manage HVs during periods of significant load loss due to storms, thereby reducing the burden on operators during major storms and protecting against equipment damage. Finally, it is essential that utilities develop interoperability guidelines for technology to ensure more effective management of mutual assistance resources. Ride Through Systems and Components Issues

By taking proactive steps to minimize equipment damage, utilities have been able to ride through extreme weather event. Such steps include utilizing phasor technology (PMUs) to rapidly pick up problems on the grid; automating system transfer upon of critical power paths failure; ensuring that substations at flood risk have supply switching capabilities so that most customers continue to have supply; and using selective deenergization of some transformers in such substations, Other effective steps for ride through include: removing debris from substation grounds; relocating relays for deenergized transformers (and any other deenergized equipment) away from flood-prone areas; and sealing and waterproofing tap changes, motors for high side switches, control cabinets, and batteries. It is also helpful for utilities to have adequate critical replacement equipment in storage and rapidly deployable repair crews on standby and to plan for alternate transportation means for crews to go to downed lines when roads are blocked. Resources, Processes, and Human Factors

Some of the processes that have enhanced utilities’ ride-through capabilities during storms include creating a storm readiness checklist, granting electric utility resources

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first responder status, and predeploying resources based on storm forecasts. In addition, building information-sharing partnerships with other stakeholders (e.g., key government agencies) and establishing prearrangements with supply chains for access to emergency fuel, equipment, and supplies have been crucial.

Rapid Recovery Systems and Components Issues

Utilities’ rapid recovery after storms has hinged on maintaining a fleet of mobile small to medium transformers, having access to shared inventory of spare EHV transformers, and having the ability to clear local roads to get to downed lines and substations. Rapid recovery has also hinged on having adequate black-start capability and the capability to rapid reroute around problem areas. Some utility restoration practices have shifted from centralized to decentralized restoration management tailored to the events, magnitudes, and types of disruption (e.g., wind, flood, earthquake, and terrorist or cyber-attacks). Resources, Processes, and Human Factors

Some of the essential processes for rapid restoration include stationing rapid responders close to potential problems for quick recovery, drawing on mutual assistance groups, and utilizing prearrangements with vendors to ensure continuity of supplies. In the events of large outages or blackouts, utilities tend to restore their own systems to an appropriate stability and level of operability and then connect with others to rapidly reestablishing power to essential services (e.g., hospitals, fire, police, and emergency).

Adaptability

As each storm comes with a different learning experience, revising the system and the emergency response plan accordingly might be necessary. On the system side, this could include reconfiguring lines based on known threats or vulnerabilities, revaluating risk conditions based on geographic locations (or interdependencies), and adding new contingencies to the state estimator. On the emergency response side, this could entail documenting and creating mitigation plans for newly discovered risks (e.g., new cascading failures).

Use of the Smart Grid to Increase System Resiliency

The smart grid can enhance system resiliency by making the power system more flexible. This can be accomplished through employing automatic switching and sectionalizing equipment to reduce the footprint and duration of power outages. During Sandy, entire neighborhoods were without power. Although a smart grid for such a massive storm might not have limited the extent of such outages, it might have made it possible to restore power to some neighborhoods faster. Smart grid technologies

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enable better intelligence regarding the status of the grid, thereby improving utility response to equipment failure and expediting restoration of power. The major components of a smart grid especially important for system resiliency are described as follows: •





AMI and meter data management: The AMI system allows two-way communications with smart meters and, coupled with a distribution management system, assists utilities in determining which customers have lost service, thereby informing restoration strategies. Smart meters allow utilities to receive notification of power outages immediately. Successful meter pings reduce truck rolls to check that power has been restored, thereby reducing time from the end-of-outage restoration activities following a major event. AMI systems work in unison with new automated restoration systems during electrical interruption events to try to automatically restore power. For example, for small storms, automated systems are able to recognize an outage and utilize the reclosers on the grid to isolate the outage and reroute the flow of electricity around the outage, thereby reducing the number of customers affected by an interruption. However, such features, while important, would not have as large of an impact in a significant storm such as Sandy, since there would not be sufficient lines operable to reroute the flow of electricity. Distribution-SCADA (D-SCADA): D-SCADA systems collect voltage, current levels, and equipment state and operational states so that operational can be made. Distribution management systems (DMSs): A DMS assists control room and field operating personnel to monitor, control, and optimize electric distribution system operations. In addition, DMSs identify the location of faults more precisely to mobilize repair teams more quickly to restore service. Coupled with an AMI system and a D-SCADA system, a modern DMS can provide utilities with improved situational awareness of their distribution systems for faster response and restoration.

Use of Social Media

Sandy marked a shift in the use of social media in disasters. Throughout the course of Sandy, including the days prior to landfall and for several weeks following, government agencies, response partners, utilities, and individuals leveraged various social media tools for sharing information about the storm. Many of these instances represent the first time a government agency officially used social media for response activities. Utilities could use social media to collect photos of damaged equipment from the public and/or emergency responders and GIS to identify the equipment’s location. Throughout Sandy, the public turned to social media for updates and assistance. Twitter and Facebook were used extensively by individuals, first responder agencies, and utility companies to provide updates on the storm, relay information, and share evacuation orders. Social media was used extensively to assist in response and then recovery efforts.

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Appeal of Microgrids in System Resilience

Microgrids (see Figure 12.4) came to the spotlight after Sandy as a key component for grid resiliency during the event and an element suited to provide backup power supply during system restoration. This came on top of an accelerating interest in customer-owned distributed generation for active participation markets or enhanced reliability. In the United States, the DoE and DoD have supported roughly 30 microgrid demonstration projects worth over $500 million over the last five years. DoD has been a leading adopter of microgrids for military stationary bases, typically done as engineered solutions for each application, with equipment and systems selected based on the energy security for mission criticality. Energy security is also important for some industrial plants, facilities, and campuses (hospitals, corporations, universities, national laboratories). Campus- and community-based microgrids

Figure 12.4 Example of a microgrid.

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have the most attractive and cost-effective applications built upon the colocation of multiple facilities, while sharing a common energy infrastructure. These microgrid opportunities may translate into over 5 GW of new microgrids over the next five years, with the top three industries most likely to deploy them being healthcare/ hospitals, government (military and nonmilitary), and utilities. The benefits of microgrids most often cited are: meeting local demand, enhancing grid reliability, and ensuring local control of supply. Such applications depend on enabling technologies in the fields of advanced sensors, energy management systems, distribution management systems, and protection and communications technologies. However, because microgrids contain technologies from distributed generation and storage, the lessons learned from those two technologies are transferable to microgrids. There are many factors to consider in the applications of microgrids. This section addresses two of them: 1) the requirements of the control system and 2) the protection concerns that all microgrids face.

Types of Microgrids

A formal definition from the DOE Microgrid Exchange Group states: “A microgrid is a group of interconnected loads and distributed energy resources (DERs) within defined electrical boundaries that acts as a single controllable entity with respect to the grid.” The distributed energy resources within the microgrid can be either distributed generation (DG) or distributed storage (DS) and are often both used to provide energy needs within the microgrid. The microgrid is customizable to enduser needs and its loads can be disconnected from and reconnected to the utility with minimal disruption to the local loads. Distributed renewable energy resources are increasingly being used in new microgrid development, and energy storage is playing a bigger role now. When energy storage is supplemented with control technologies, it provides voltage control services that facilitate elevated levels of renewable variable generating resources, such as solar photovoltaics. Microgrids are typically connected to, and synchronized with, the traditional centralized electrical grid and typically connected to it at a single point of connection. The microgrid can typically disconnect from the grid and function as an autonomous power system. A microgrid, present and future, can be put in one of the four broad categories: • •





Utility- (or nonutility-) owned remote microgrid to power an isolated community; Utility microgrid to locally manage the integration of renewable generation or local load growth, to provide ancillary power, or to provide premium power to some clients; Campus type microgrid to serve several facilities that may have, in some cases, multiple points of connection with the main utility grid; Single-facility microgrid to serve single facilities (e.g., data centers and cellular communication providers) to secure the cost-effective, high-quality power supply required for these systems.

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There are also virtual microgrids, which use some of the utility infrastructure, such as wires, to connect some of its generation and load. In all the above cases, the microgrid resources under island conditions must all work together to control voltage, frequency, and active and reactive power. Supervisory Controller for the Microgrid—Example of Functionality and Requirements

Microgrids need to have an overall supervisory controller to coordinate the operation of multiple generation sources and to ensure power balancing and energy management within the microgrid and to the external grid. The development of such a system is a complex process that requires various elements, such as the following: •











A data acquisition component to acquire real-time data from the electrical system sensors and communicate that to the control system. Real-time operational monitoring and management are needed to provide accurate and timely suggestions for operational decisions and provide improved predictions of system problems before they occur. With such improved techniques, operational costs can be reduced. A system for forecasting the expected power from the intermittent resources (PV and wind generation). A real-time model of the electrical system of the microgrid that represents the current state of the electrical system, developed by collecting data from the data acquisition system. A virtual system model of the electrical system that mirrors the real-time model of the electrical system and can be used to generate predictions regarding the cost, performance, availability, and reliability of the various distributed energy sources. This would also be used to predict the price of acquiring energy from these sources, as well as the grid. An analytics server connected to generate predicted data output for the electrical system, with the following elements: – An analytics engine, configured to monitor the real-time data output and the predicted data output of the electrical system and initiate a calibration of the virtual system model; – A network-optimization simulation engine, configured to use the virtual system model, updated based on the real-time data under the modified parameters of the virtual system model. This can change the mix of distributed energy sources of the microgrid, based on the forecasted cost of operating the microgrid electrical system or its reliability and availability For mission-critical electrical systems (e.g., for data centers) the microgrid should be designed to ensure that power is always available, and therefore multiple layers of redundancy must be designed into the system to ensure that there is always a backup in case of a failure. For the controller, the added redundancy can make its complexity even greater, requiring detailed computer design and modeling of the microgrid.

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Electrical power from microgrids can be sold on complex markets. Microgrids can sell excess power to the grid and can purchase power from the grid to meet local demand, more than the generation capacity of the microgrid. Optimization of market-based power systems is a critical component of the microgrid. Thus, the controller also plays interfaces and exchanges data with the utility for participation in the energy market and coordination, as well as of the operation with the rest of the grid. The controller would need to factor in the demand for electricity, market conditions (e.g., pricing and availability of electrical power), overall availability and reliability of the system, routine maintenance, system changes, as well as unplanned events that impact the electrical power network.

Static and Adaptive Microgrids

Microgrids can be either static or adaptive. A static microgrid has predefined boundaries. On the other hand, the boundaries of an adaptive microgrid (also known as a dynamic microgrid) change depending on the load requirements; it can serve as a function of the available generation and the priority of load to be served. An adaptive microgrid thus should have the capability to break into smaller independently survivable islands with controllable resources, as well as those with blackstart capability. Microgrids should also be able to attach to other microgrids in the area. This requires the highest level of communication among generation devices and adaptive grid command and control that can shift from one controller to the next as the system changes state. The protection schemes and operating set points would also have to adapt to the changing states. For dynamic microgrids to become a reality, certain innovations need to become mainstream, such as decentralized control mechanisms with the ability to function in a centralized manner and better modeling mechanisms and capabilities for planning and operational requirements.

Protection Issues with Microgrids

The major challenge in microgrids is the protection system. Protection systems must respond to both isolated and grid-connected conditions, faults on the grid, and faults within the microgrid. For faults on the grid, the protection system should isolate the microgrid from the grid as fast as possible to protect the microgrid, including the distributed generators (DGs), loads, and feeders. The fast operation of protection improves the ability to maintain synchronism after transition to islanded operation, which is crucial for system stability. The various protection issues arise from the change in the fault current level of network when isolated versus when connected from the grid. This variation in the short-circuit capacity can translate into a reduction in the reach of distance relays, sympathetic tripping, loss of relay coordination, and or even unintentional islanding. Microgrids typically require the use of existing lines or the construction of new power lines within the defined zone. Microgrid operation may involve the exchange of power between parties or the transmission of power across streets or public areas, which could make operators subject to public utility regulation.

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During a storm or other reliability event, microgrids would be capable of automatically isolating and operating independently from the larger grid, first maintaining noninterruptible services and then providing power to critical services within the microgrid. While the microgrid may be designed to meet all of the connected load, it is conceivable in some cases that only the requirements of the noninterruptible and critical load could be met with the microgrid. The decision process regarding load management during isolating would include an assessment of the duration isolation from the larger grid. Adaptive Protection Applications for Microgrids

An adaptive protection scheme can potentially solve protection issues in both gridconnected and islanded mode. Such a scheme would be built around the concept of automatic readjustment of relay settings when the microgrid changes from islanded mode to grid-connected mode by modifying the preferred protective response. Practical implementation of an adaptive protection system makes use of numerical directional overcurrent relays that have several tripping characteristics, with several settings groups that can be parameterized locally or remotely. (Standard solid-state relays do not provide the flexibility for changing the settings of tripping characteristics and they may lack the current direction sensitivity feature.) Communication between individual relays with a central computer or between different individual relays is needed to maintain the settings of each relay about the current state of a microgrid. This can be achieved with existing/new communication infrastructure (e.g., twisted-pair) and with standard communication protocols (e.g., Modbus and IEC61850), so that individual relays can communicate and exchange information with the controller or with other relays. Each individual relay would need to make a tripping decision locally to keep the system stable and to isolate the fault as quickly as possible. The controller would have to have a module responsible for the periodic inspection and updating of the relay settings. The controller would need to monitor the state of microgrid by polling all individual relays. Tactically, the information about the precalculated values of fault parameters (done during off-line fault analysis of a given microgrid) would be combined with the on-line information about the system to achieve an adaptive approach to protection to avoid the nonselective operation of relays in the microgrid. It is possible to send blocking signals in the right direction so that relays on both sides of a faulty element trip, isolating the fault and leaving the nonfaulted system intact and operational. An adaptive protection system that would satisfy the above requirements would require a high investment cost in comparison to a conventional protection system. Cost would correspond to investment and operating costs over the system lifetime, and the benefit would correspond to reduced outage time and opportunity loss, such as selling to the market. Case Histories

During Superstorm Sandy, several locations in the outage-affected areas reported that on-site power generation and the ability to operate independently of the grid allowed them to have electricity while neighboring streets were blacked out. University and

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college campuses such as Princeton University, Stony Brook University, New York University, and the College of New Jersey, used combined heat and power (CHP) plants to keep the lights (and heat) on both during and after Sandy. As an example, key buildings on NYU’s campus stayed lit by using a self-sufficient microgrid system that was designed to distribute electricity independently of the utility grid. A 13.4MW CHP powered the university’s 26 electrically connected buildings. Similarly, South Oaks Hospital on Long Island and Connecticut’s Danbury Hospital used CHP to keep medical facilities online. Some commercial buildings, and residential communities like Co-op City in Bronx County, New York, also used CHP during Sandy. Microgrids in Black-Start Scenarios after a Storm

Besides contributing to ride-through capability during storms, it is conceivable that dynamic microgrids could stitch systems back together after a major storm by creating islands of balanced supply and demand, thereby moving more quickly to recovery. Microgrids can contribute to black-starting (BS) the grid following a blackout caused by extreme weather events, thereby reducing the social and economic impacts of storms and shortening the overall time of power system restoration. Microgrid black-start capability can be used to fully profit from the potential of dispersed distributed energy resources. To date, functionalities for operation restoration are available only for conventional power system resources. Conventional black-start restoration techniques are based on a top-down approach; that is, they would begin by starting up conventional generation units and end with the connection of loads. For microgrids, this would be essentially a bottom-up black-start approach. For microgrids to be used for black-starting portions of the grid, there needs to be automatic load disconnection after system collapse within the microgrid and in the local grid to which the microgrid is connected. It is a prerequisite that the network to which the microgrid is connected has the capability of operating in islands before the overall grid is available again after a blackout; that is, the grid needs to be capable of area separation. For microgrids to perform service restoration at the microgrid level, microgrids should be able to power their auxiliary control systems and local loads and should have bidirectional communication links to the system operator. Figure 12.5 shows a logic that can be used to black-start a portion of the electric grid following a blackout. For the logic in Figure 12.5 to work, disconnection of all loads in the microgrid and the network is needed to start the black-start process to avoid large frequency and voltage deviations. To facilitate the starting of the microgrid itself, the microgrid should be divided into micro-islands: those that are black-start capable and those without black-start capability. Storage devices within the microgrid are typically the first to receive control orders from the microgrid controller to energize the microgrid cables. As the distribution transformer typically serves as the point of earthing for the microgrid, it is energized next for safety and protection considerations. Transformer energization should be performed using a ramp-wise voltage. The micro-islands are synchronized later. The synchronization of the microislands within the microgrid (phase sequence, frequency, and voltage differences) should be verified to avoid large transient currents and power exchanges. The

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amount of power to be connected should be limited to values that would not cause large frequency and voltage deviations during load connection. The Future of Microgrids

The resiliency shown in the above situations has proved that that microgrids can play a key role in system resiliency in the future, especially when developed in conjunction with plans to protect critical loads. Microgrid deployments are expected to increase significantly over the next five years, especially in mission-critical operations, such as in hospitals and military bases. It is also expected that the present

Figure 12.5

A scheme to black-start a portion of the grid from a microgrid.

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deployments and pilots, as well as the demand in rapidly developing countries and rural communities, will increasingly push the larger-scale adoption of microgrids. This is further reinforced by the fact that the developing world would not be able to sustain its economic growth by building solely on centralized electrical systems. Because microgrids can serve nonutility sponsors, it may seem that they challenge traditional utility interests; yet, microgrids can serve both the utility and the sponsor. Utility-controlled microgrids can take advantage of the islanding features of microgrids, which reduce load on a stressed grid and/or defer capital investment in capacity or to meet load growth. Thus, microgrid benefits can include meeting peak load constraints and load shifting. The ability of the microgrid to defer capital investment in infrastructure acts as an alternative to more capital-intensive infrastructure projects to handle load growth, optimize the supply-load mix on specific parts of the overall grid, and monetize some ancillary services (such as frequency regulation). Microgrids also allow utilities to optimize their available resources, and at the same time, maximize the use of renewable energy, limiting greenhouse gas emissions while still meeting load requirements. This approach is being explored in California. Similarly, the goals of meeting renewables targets and complying with aggressive mandates to limit greenhouse gas emissions are driving the European Union to see the most near-term growth in microgrids. However, this growth could be at risk if the European Union backs off its environmental mandates for economic reasons. In the meantime, in New York, the nonutility potential microgrid sponsors are looking at microgrids to boost system resiliency in the wake of storms, such as Sandy. However, with no in-place policy drivers, the challenge for utilities to develop a positive business case for microgrids remains daunting, but it is not always insurmountable, especially when some factors, such as those detailed above, are met. On the other hand, the current low cost of gas is boosting several business cases for microgrids, which have a sizable percentage of conventional sources, rather than renewable sources. This may also propel some other aspects of the microgrid, such as CHP natural-gas-fueled projects. Policy drivers, if they become a reality in the United States, may be fragmented, given that there are over 50 state-level public utility commissions to navigate and from which to gain approvals. Developers of microgrids face differing regulations based on the state they are in, as the concept and definition of a microgrid does not exist or is not recognized in many states; thus, in these states, the microgrid may fall under regulations intended for other concepts. For example, it may be classed as a public distribution or may fall under the regulations developed to regulate steam-heating utilities if it has thermal storage. If it has components that cross public roads, it may fall under regulations and T&D cost allocations or may be required to obtain a municipality franchise or to serve as provider of last resort. If full-fledged microgrids are not feasible based on cost or other factors, there are always merits to on-site generation as a backup energy source during power outages. Fuel cells can run on several fuels (e.g., natural gas and biogas) and can provide baseload power generation without battery backup when separated from the grid as current standards, for safety concerns, require that distributed generation systems shut off when the utility grid shuts down.

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Cybersecurity with Microgrids

Properly designed microgrids isolate failures and maintain continuity of service when the grid experiences problems. In combination with DERs, microgrids, can supply black-start capabilities to the grid in storm situations or during cyber or physical incidents. However, the presence of DERs, when microgrids are connected to the grid, raises new challenges for resilience. The deployment of DERs redefines the nature of the traditional protection perimeter with respect to cybersecurity by extending the network into homes and businesses. Cybersecurity concerns stem from the two-way digital controls for DERs, which necessitate more widespread and intensive cybersecurity protection. Utility mutual response agreements for responding to natural disasters, discussed earlier in this chapter, may not work well for cyberattacks. In networks with significant active DER participation, information and communications technology (ICT) systems will need a multitude of DER devices alongside numerous centralized power stations, thus increasing system vulnerability to external events. This more complex environment may lead to common failure modes if the same DER software configurations are used across regions. DERs may need to be able to operate in a partially manual mode, or even disconnected from the main grid, if telecommunications digital controls are compromised by cyberattacks.

Performance of Solar PV Power during Superstorm Sandy

Events such as Superstorm Sandy in 2012, the 14-day heat waves in 2013 that affected Maryland, Ohio, and West Virginia and that were immediately followed by a series of powerful thunderstorms knocking out electricity for 3.8 million people; and the record-breaking 2015 blizzards in the Northeast compel us to seriously consider renewable energy resources as part of a plan for resilience against extreme events. Like the conventional grid components, renewable sources, such as wind and solar power resources, are exposed to extreme weather as well as long-term phenomena, such as heat waves and droughts. However, we know from past weather events that they are robust as a group, even though single units may be vulnerable to extreme weather events. For their transmission systems, wind and solar farms are based on many independent, units. As each renewable source is designed to withstand foul weather, it is highly unlikely that every renewable unit in a wind or PV farm will be damaged by one extreme weather event. Most would survive extreme weather and would be able to generate electricity once the event passed. Figure 12.6 [5] shows the performance of a 1-MW utility-owned PV segment of a ground-mount utility solar farm during and after Sandy. The right side of Figure 12.6 follows the local irradiation levels; there was very low irradiation the day before and during the storm and sunny to partially cloudy days from after that (October 30). It is assumed that most solar PV systems in the region affected by Superstorm Sandy were inoperable due to a lack of dynamic controls (e.g., dynamic inverters and transfer switches), which would have allowed them to be operated in island mode during a grid outage. There are very few known cases of nonutility-owned PV systems operating during Sandy. One of the few examples was a system at school, where facility staff

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Figure 12.6 Performance of a 1-MW segment of a utility owned solar PV system during Superstorm Sandy.

could operate the school’s PV system by manually disconnecting from the grid and isolating equipment. According to a technical report by NREL, most of the PV systems in New Jersey may have been able to operate during Sandy if they had been preemptively equipped with islanding controls and dynamic inverters. Inspections following Sandy have shown that most PV systems received no damage, or only minor damage [6], from the storm and would have been able to operate. Their operation would have allowed police dispatch centers and communication towers to operate without grid power while residents would have been able to use critical appliances and electrical devices. Damage inspections after Sandy and other extreme storms have shown that the most vulnerable parts of our energy system today are not the electricity generation units or transmission systems, but the power distribution systems. Thus, to adapt to the increasing risk of extreme weather events, future efforts need to focus on improving and weatherproofing the distribution grid. Distributed solar PV systems have the potential to supply electricity during grid outages resulting from extreme weather. As such, distributed PV can bring more resiliency to the distribution system and the grid in general. To benefit from this capability, PV systems must be designed with resiliency in mind and combined with other technologies, such as energy storage. This will need to be reinforced by policy and regulatory support. Increasing the grid’s resilience through DERs, such PV systems equipped with battery storage can reduce the restoration time and resources needed to supply power to critical facilities (e.g., hospitals and wastewater treatment facilities) after extreme weather events and return the entire system to normal operations. Concerns with PV and Prevailing Standards

PV systems have some well-known concerns. Injecting power at various points on distribution PV systems increases the voltage at the points of interconnection. The power output from PV systems is intermittent as their output changes, sometimes significantly, over short periods of time due to cloud coverage or fog onset/burnout. Legacy utility equipment for voltage correction may not be able to fully correct such effects as the aggregate number and size of PV systems continue to increase. In addition, PV units connected to distribution feeders are expected to trip automatically during voltage and frequency excursions, as specified in IEEE Standard 1547:

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“Interconnecting Distributed Resources with Electric Power Systems,” which has defined the behavior of grid-connected PV inverters for over a decade. Over that time, this standard has served to demonstrate both the pros and cons of an interconnection standard focusing exclusively on utility concerns for the safety and integrity of the traditional distribution system, and without system resiliency in mind. PV Systems Coupled with Battery Energy Storage

For a rooftop-PV system to provide electricity during a utility power outage, it must be designed to function as a stand-alone resource that can isolate itself from the grid and continue to supply power and store excess energy for later use. To date, the major barrier to the deployment of energy storage devices, in conjunction with PV systems, has been cost. However, the picture is changing fast as battery prices have declined markedly in recent years, and costs are expected to continue dropping. Increased demand for backup power, lower battery prices, and uncertainty in the future cost of grid power are motivating interest in distributed energy storage. Focus is being placed on optimizing the economic viability of energy storage by identifying the most cost-efficient system size for PV applications. When battery systems are designed to supply the on-site load only, battery costs could be lower than when designed to supply other wider grid services. However, if the owner of the battery system is compensated through market mechanisms for the benefits that storage provides to the broader electricity system and to society, then the effective cost of the battery could be more economical, or could even be totally offset. Such ancillary services can include voltage control frequency regulation, demand-side management, and increased ability to integrate elevated levels of distributed generation onto the electricity system. Most PV systems in place today are not coupled with batteries or auxiliary power sources to allow them to provide continuous power to a load. In addition, current operating standards, for safety purposes, require that grid-connected solar PV systems automatically disconnect from the grid during a power outage. As most systems are not designed to function as both a grid-connected and a stand-alone system, any disturbance causes the systems to disconnect from the grid and shut down. The Need for Smart Battery Inverter Systems

Battery energy storage, integrated through an inverter, can allow a PV system to provide reliable power during a grid outage. The inverter must be able to automatically select between charging the batteries, providing electricity to the load, and even feeding the grid. This is based on different conditions such as: battery status, on-site load demand, and grid status. The inverter should isolate the PV system from the grid while continuing to supply power to the on-site load with power from the PV system or the battery. It must also be capable, for safety reasons, of isolating all local load from the grid upon grid disturbances, such as those caused by severe weather. Most inverters produced for the United States have the physical components required to provide enhanced response, but they may lack the firmware functionality, which could be added with modest increases in cost. Enhanced inverter functionality is desired to achieve fault ride-through capability, so that

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distributed PV could contribute to grid stability during system disturbance, where the grid voltage or frequency may go outside the normal operating ranges. Today, and per IEEE Standard 1547, if the frequency dips below 59.3 Hz for more than a second or two, the smaller PVs (less than 30-KW) may trip. If the frequency drops below 57 Hz all the IEEE-1547 compliant PVs would trip off-line. If large numbers of PV generators trip, it could push frequency down even further. Large conventional generators will act to recover the frequency depending on how much load is still connected and how much PV generation has tripped. To ensure that PV systems provide grid support during system frequency events caused by tripping of large generators during extreme weather events, it would be ideal if inverters were to disconnect in a random manner. Germany has developed standards that require inverters to provide dynamic reactive support and low voltage ride-through (LVRT) capability. The primary reason for testing this inverter is to explore features not used in inverters that must comply with U.S. standards. These features include the ability to communicate with other devices, adjust ramp rates, low-voltage ridethrough, adjust the power factor, and inject or absorb VARs into the systems during voltage deviations. Effect of Droughts and Heat Waves on PV

Droughts do not affect rooftop PV system output as they do for thermal central station power plants. Accordingly, distributed PV systems can increase grid resilience. Climate change may affect thermal power plants in two ways. Increased ambient temperature reduces the efficiency of thermal power plants. At high ambient temperatures, the output of a thermal power plant may be limited by maximum condenser pressure regulations on maximum allowable temperature for return water or by reduced access to water because of droughts. Heat waves and droughts have forced numerous thermal plants in the United States and Europe off-line or to reduce their output. For example, during the 2003 summer heat wave in Europe, more than 30 nuclear power plants were forced to shut down or reduce their power production, as nuclear plants are vulnerable. High ambient temperatures may reduce PV panel efficiency linearly. If heat waves are accompanied by high humidity, it affects solar PV in ways comparable to dust accumulation. Water vapor particles might reduce the irradiance level of sunlight that is required for PV panels to reach high efficiency. In fact, the impact of relative humidity could be 50% higher than the impact of higher temperature. Therefore, rooftop solar panels may have a negative impact on system resiliency in heat waves. Impacts of Rate Structures on the Use of Distributed Solar with Storage

Economic factors such as rate structure and compensation for PV generation can influence their use. Customers that are subject to demand charges may find that battery storage for load shifting would be economical. Time-of-use (TOU) rate structures incentivize the use of solar generation when prices for grid electricity are highest. The typical residential net metering rate structure provides little or no economic incentive to use battery storage with the PV system. In Germany, owners of PV systems with battery storage are incentivized to store excess solar power to be

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used when solar generation does not meet on-site load. Therefore, if increased grid resilience for extreme weather (and other grid disturbances) is an objective, then this will require policymakers to encourage the deployment of distributed storage systems with careful attention to the way that the rate structures and incentives encourage certain behaviors and usage patterns for the energy generated by the PV systems.

Cyber and Physical Security Cyber and physical security threats pose a significant and growing challenge to electric utilities. Unlike the threat from extreme weather, cyber and intentional physical attacks are less predictable and therefore more difficult to anticipate, address, and protect against. The ways in which cyberattacks can be conducted are growing in complexity, with increased potential targets and vulnerabilities. As more grid modernization systems and products are introduced, the attack entry points, the different points where an attacker can try to enter or extract data, are increasing. On the other hand, the distributed nature of the grid, while providing a degree of resiliency against severe weather, presents challenges to protecting against physical attacks—individual or coordinated. For a more complete coverage of system resiliency, this section touches on those two threats, cyber and physical security. While it is by no means a comprehensive coverage of the two subjects, several recommended readings covering this subject in depth are listed at the end of the chapter. Cybersecurity

Supplementing hardening of infrastructure against extreme weather with modern remote monitoring capabilities would enable utilities to make decisions to protect critical assets and minimize disruptions. Lessons learned from previous extreme weather events have shown measures to prevent outages and to minimize outages when they do occur, as well as to speed up power restoration after outages. When such measures (several which are part of grid modernization efforts) are properly incorporated into planning and response processes, they can be highly effective in extreme weather situations. However, such increasing grid modernization also allows cybervulnerability to become an increasingly sophisticated threat to the power grid. This is in part because remote monitoring, control,1 and automation are dependent on the use of wireless communicating controls and systems to operate, heightening concerns about cybersecurity and adding complications in the resiliency equation of the grid. Distribution systems may be particularly vulnerable due to the increased modernization that they are witnessing and the bigger role of automation to increase the efficiency and reduce the impact of outage. Cybersecurity is a heightened concern in situations in which a distribution system is already compromised by severe storms. 1

Control systems used to be isolated so there was minimal need for cybersecurity. This is no longer the case. Control systems increasingly use remote access for operators (e.g., control centers, regional power pools, and independent system operators), vendors, and other entities.

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Types of Cyberattacks

Cyberthreats can take several forms, including the following: •









Distributed denial of service (DDOS) attack: In a DDoS attack, hacked sensors, which may be geographically distributed, are instructed by the hacker to simultaneously send a large volume of traffic to a victim sensor or to the control center. The victim sensor and/or control center will be overwhelmed by the huge volume of traffic, and thus normal data cannot be handled properly. Simultaneous shutdown attack: An attacker, pretending to be a control center, sends fake control messages to command sensors and other system devices to shut down, thus rendering the smart grid ineffective. Rogue device: An unauthorized device accesses the system, manipulating it or providing incorrect data to system operators. An attacker can intercept and alter the estimated usage schedules from the smart meters to the operation network and change the demand for power. Unauthorized access and use attacks: Attacks to take control over the system and access/manipulate assets, or attacks that can result in system operators being given inaccurate information needed for decision-making. Malicious code (malware), including viruses, worms, and Trojan horses: The usual purpose of malware that is targeted at electric utilities is to obtain control of a utility’s systems and components. The goals may not be always to shut down an entire system. The goals from injecting the malware could be to game pricing models, disrupt certain regions, access certain information, or prepare for future attacks. The potential now exists in the cybersphere for common modal failure of assets, where a single exploiting of one vulnerability can be propagated across a cyber or power system network to potentially affect an entire fleet of assets simultaneously. This is a single point of failure from a system planner’s perspective, distributing the effects of a single attack across an entire system or network.

Examples of Potential Cybervulnerabilities of Grid Components

Cybervulnerability extends from the control room into communicating devices to the transmission and distribution systems. Smart grid devices are another potential pathway of a cyberattack. Smart meters have been identified as the point of weakness of the AMI and of the smart grid communication system. They introduce the potential for remote disconnect and manipulation of demand response programs and provide access points to distribution and transmission systems through the communications channels. As smart meters are located within the customer premises, it may be difficult, or even impossible, for control centers to protect them from potential attackers especially since smart meters have limited processing power to run complex protective measures. The concern is not with the attack or manipulation of a single smart meter or device, but the potential for sabotage of an entire smart meter network or a sizeable portion of it. While individually these assets may not have an impact on bulk power system reliability, in aggregate they would, especially since they are now widespread and constitute a substantial portion of load or generation.

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In the past, SCADA systems, distributed control systems, and programmable logic controllers were all designed as closed systems with limited control interfaces. Today, these technologies are digitized and include more intelligent software and hardware components. SCADA is increasingly using IP networks for operational control. This creates potential cybervulnerabilities. In addition, over 85% of all system protective relays are now digital, with a substantial number remotely accessible and settable. Other potentially vulnerable devices include remote terminal units (RTUs)/ intelligent electronic devices (IEDs), 2 plant control systems, component controllers (e.g., for static VAr compensators and capacitor banks), DRSs, meters, and energy management systems (EMSs). Manipulating data streams from phasor measurement units (PMUs) may have significant impact on the situational awareness and operation of bulk power systems. In the future, SCADA and distributed control systems may have a secondary diagnostic infrastructure for verifying that the system is operating properly and data is not being tampered with. The growth of the Internet of things (IoT) also expands vulnerabilities if sufficient cybersecurity and encryption have not been built in and vulnerable wireless protocols (e.g., ZigBee) are used. Wirelessly connected IoT devices, including sensors, cameras, and smart appliances are vulnerable to cyberdisruptions and attacks and could spread malicious code. Case History: Cyber Attack on Ukraine Power Grid, December 23, 2015

On December 23, 2015, synchronized multistage, multisite attacks on the Ukrainian electric power system resulted in unscheduled power outages impacting many customers.3 There have also been reports of malware found in Ukrainian companies in a variety of critical infrastructure sectors. The cyberattack was synchronized and coordinated. According to Ukraine power company’s officials, the cyberattacks at each company occurred within 30 minutes of each other and impacted multiple central and regional power facilities. During the cyberattacks, malicious remote operation of the breakers was conducted by multiple external humans using either existing remote administration tools at the operating system level or remote industrial control system (ICS) client software via virtual private network (VPN) connections. The companies believe that the actors acquired legitimate credentials prior to the cyberattack to facilitate remote access. In the attack, the adversary delivered a targeted e-mail with a malicious attachment that appeared to come from a trusted source to specific individuals within the organizations.

2

Remote terminal units (RTUs)/ intelligent electronic devices (IEDs): RTUs collect data from sensors in the field and convey them to EMS and SCADA systems. IEDs are devices incorporating one or more processors with the capability to receive or send data/control from or to an external source (e.g., electronic multifunctioning meters, digital relays, and controllers). These devices are used to implement control and management commands remotely. 3 An interagency team comprised of representatives from the US National Cybersecurity and Communications Integration Center (NCCIC)/Industrial Control Systems Cyber Emergency Response Team (ICS-CERT), U.S. Computer Emergency Readiness Team (US-CERT), Department of Energy, Federal Bureau of Investigation, and the North American Electric Reliability Corporation traveled to Ukraine to collaborate and gain more insight.

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Lessons learned from the Ukraine Grid Attack Based on the details of this attack, e-mail seemed to have come from a trusted source so white-listing would have had a limited success in this case. Practices as mundane as enforcing a password reset policy in the event of a compromise, especially for VPNs and administrative accounts, would have gone a long way toward preventing such an attack. Other practices suggested by the lessons learned from this attack include: performing network security monitoring to continuously search through the networked environment for abnormalities, planning and training incident response plans that incorporate both the IT and OT network personnel, and developing active defense models for security operations such as the active cyberdefense cycle. The Selected Bibliography section of this chapter lists a good resource to gain more insights into this attack. In the United States, the bulk power system is comprised of hundreds of thousands of miles of HV transmission lines and over 150 balancing authority areas— add to that millions of digital controls. Hardening to an ever-changing threat is neither feasible nor cost-effective. In addition, power system components have long lifetimes and may not be able to be modified to meet new cyberthreats. As a result, effectively mitigating the effects of a coordinated attack on the system requires a strong mix of preventative measures designed to build on the inherent resilience of the power system and preparatory measures that enable system operators to recognize an attack, respond to it when it does occur, and restore the system if the attack is successful in the disruption of power. Cyberattacks may result from an asset being misused to affect assets connected to it. Accordingly, priority should be given to designing for survivability, so that a system is able to withstand and recover from a structured multinode attack. Physical Security

The distributed nature and diversity of the system, while providing a degree of protection, presents important physical vulnerabilities. Today, varying levels of security surround critical bulk power system assets. These range from heavily guarded and monitored generators to geographically remote substations with little physical protection. Installing additional protection elements around all the assets is not cost-effective. A physical attack on the PG&E Metcalf substation near San Jose, CA, in April 2013 brought attention to the need to address the physical security of the U.S. power grid. This incident led to FERC’s requirement that NERC establish critical infrastructure protection (CIP) standards to bulk system physical security threats and vulnerabilities. NERC subsequently developed and issued reliability standard CIP014. CIP-014-1 became effective on January 26, 2015. Under CIP-014, transmission owners are required to identify their critical transmission stations and substations that, if rendered inoperable, could result in grid instability, uncontrolled separation, or cascading failures, for 200-kV systems and above, if they meet certain criteria. Transmission owners and operators are required to evaluate potential threats of physical attacks against their respective transmission stations and substations and to develop and implement documented security plans to address those threats and vulnerabilities. Both the identification of vulnerable transmission facilities and the

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security plans developed by transmission owners and transmission operators are subject to verification by an unaffiliated third party. Coordinated Attacks

Highly structured physical, cyber, or blended attacks could potentially target multiple power systems assets at once, pushing the system outside the protection provided by system design criteria. The risk of a coordinated cyber, physical, or blended attack against the bulk power system has become more acute as digital communicating equipment has introduced cybervulnerability to the system, and resource optimization has allowed for a reduction in inherent physical redundancy. The specific concern with respect to such threats is the targeting of multiple key nodes on the system that, if affected in a coordinated fashion, could push the system beyond the planning criteria. Such attacks could make the system behave very differently than with traditional risks. Intelligent attackers could manipulate assets and provide misleading measurement data to system operators attempting to address the issue. The electric sector has taken important steps toward mitigating these issues with the development of NERC’s CIP standards.

Summary and Conclusions Superstorm Sandy was most destructive hurricane of the 2012 Atlantic hurricane season and the second-costliest hurricane in U.S. history. In the United States, Hurricane Sandy affected 24 states. Although the electric utilities and other stakeholders in the predicted path of Sandy made several arrangements to prepare for the storm, over 8 million people were affected by outages. Restoration of power after Sandy was longer than from 2005’s Hurricane Irene due to a winter storm, the 2012 Nor’easter, which hit some of the areas affected by Sandy when the restoration was at 90% level. The Nor’easter led to a loss of power to control facilities as well as obstructed accessibility to the substations and transmission lines because of fallen trees and equipment damage from salt water and flooding. There are several lessons learned from Sandy that supplement those lessons learned from HIWs, detailed in Chapter 11. Microgrids came to the spotlight after Sandy as a key component for grid resiliency during the event and an element suited to provide backup power supply during system restoration. In the past, microgrids have been of interest primarily for military bases and remote communities, but the application of microgrids is rapidly evolving, driven by resiliency concerns. During Superstorm Sandy, several locations in the outage-affected areas by storms reported that on-site power generation and the ability to operate independently of the grid allowed them to have electricity while neighboring streets were blacked out. This chapter details some of the benefits of microgrids, as well as their essential technologies. PV systems with battery storage and smart controls can contribute help create a more resilient power grid for extreme weather events. The PV industry is working on solutions to overcome several technical challenges to become a truly reliable

References

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energy provider on a large scale. Among these challenges are improving PV system reliability, solving intermittency problems, and solving the unique problems associated with high-penetration of PV. Battery energy storage and smart inverter technologies are key to such solutions, and both are presently receiving intense focus in multidisciplinary research and development programs globally. Policymakers should implement policies and incentives to advance distributed solar generation supported with battery storage to make communities more resilient to extreme weather events. Utilities need to be prepared to contain and minimize the consequences of cyber and physical attacks on the system. The consequences associated with a coordinated cyber and/or physical attack could result in the physical damage or destruction of critical assets. If conducted on a large enough scale, it is possible that the bulk power system could not recovered islands or using rotating outages where enough equipment was still available to operate the system. Future power systems with high penetration of DERs are envisioned to have features that are favorable for their resilient operation. Microgrids, with DERs, are helpful for resilience against extreme weather, and with islanding operations that can assist in black-start or continued operations if the broader grid is brought down due to a cyber or physical incidents. Severe weather and complex physical and cyberrisks are straining aging infrastructure to perform beyond its design limits. Strategies that build in resilience into the design and construction of physical and cyberstructures offer one of the best opportunities to reduce long-term risks. By reducing the risk of assets (derisking) from one threat we can reduce the risk from another. For example, on many occasions, reducing risk to extreme weather would actually improve the physical security of the system. Protecting against the risks of extreme weather, cyber and physical planning need to be coordinated as much as possible as part of the normal design activities of the grid.

References [1] [2]

[3]

[4]

[5] [6]

https://www.dhs.gov/sites/default/files/publications/EO-13636-PPD-21-Fact-Sheet-508. pdf Abi-Samra, N., “One Year Later: Superstorm Sandy Underscores Need for a Resilient Grid,” http://spectrum.ieee.org/energy/the-smarter-grid/one-year-later-superstorm-sandyunderscores-need-for-a-resilient-grid, IEEE Spectrum Magazine, November 2013. The North American Electric Reliability Corporation (NERC), “Hurricane Sandy Event Analysis,” http://www.nerc.com/pa/rrm/ea/Oct2012HurricanSandyEvntAnlyssRprtDL/ Hurricane_Sandy_EAR_20140312_Final.pdf, 2014. U.S. Department of Energy, Office of Electricity Delivery and Energy Reliability, “Comparing the Impacts of Northeast Hurricanes on Energy Infrastructure,” https:// energy.gov/sites/prod /files/2013/04/f0/ Northeast%20Storm%20Comparison _ FINAL_041513b.pdf, 2013. Fthenakis, V., “The Resilience of PV during Natural Disasters: The Hurricane Sandy Case,” IEEE Photovoltaic Specialists Conference (PVSC), 2013, 2013. National Renewable Energy Laboratory, “Distributed Solar PV for Electricity System— Resiliency Policy And Regulatory Considerations,” http://www.nrel.gov/docs/ fy15osti/62631.pdf, 2014.

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Selected Bibliography Abi-Samra, N. C., J. McConnach, S. Mukhopadhyay, and B. Wojszczyk, “When the bough breaks: Managing extreme weather events affecting electrical power grids,” IEEE Power and Energy Magazine, Vol. 12 No. 5, 2014, pp. 61-65. Abi-Samra, N. C., “Getting Lights Back on Can be Maddeningly Complex,” USA Today, http:// www.usatoday.com/story/news/nation/2012/10/31/power-utilities-restore-substationsflood/1671403/, October 2012. Abi-Samra, N. C., “Power Industry Faces Down Hurricane Sandy,” http://spectrum.ieee.org/ tech-talk/energy/the-smarter-grid/power-industry-faces-down-hurricane-sandy, IEEE Spectrum Magazine, November 2012. Abi-Samra, N. C., “Impacts of Extreme Weather on Power Systems and Components,” EPRI Report 1017901, 2009 Abi-Samra, N. C., “Impacts of Extreme Weather Events on Transmission and Distribution Systems Case Histories, Lessons Learned and Best Practices,” EPRI Report 1020145, 2010. Bipartisan Policy Center, “Cybersecurity and the North American Electric Grid: New Policy Approaches to Address the Evolving Threat,” 2014. Campbell, R. J., “Cybersecurity Issues for the Bulk Power System,” Congressional Research Service, R43989; 7-5700, June 10, 2015. E-ISAC, “Analysis of the Cyber Attack on the Ukrainian Power Grid,” file:///C:/Users/nas/ Downloads/Documents-E-ISAC_SANS_Ukraine_DUC_18Mar2016.pdf, 2016. Lawrence Berkeley National Laboratory (LBNL), “Microgrids at Berkeley Lab: Borrego Springs,” http://building-microgrid.lbl.gov/borrego- springs, www.fas.org/sgp/crs/misc/R43989.pdf, 2014. Bipartisan Policy Center, “Cybersecurity and the North American Electric Grid: New Policy Approaches to Address the Evolving Threat,” February 2014.

Appendix 12A: Expanded Information on Superstorm Sandy General Information on Sandy

Hurricane Sandy (unofficially referred to as “Superstorm Sandy”) was the most destructive hurricane of the 2012 Atlantic hurricane season and the secondcostliest hurricane in U.S. history. Sandy developed from a tropical wave in the western Caribbean Sea on October 22, quickly strengthened, and was upgraded to Tropical Storm Sandy six hours later. Sandy was a category 3 storm at its peak intensity when it made landfall in Cuba and was downgraded to category 2 storm off the coast of the northeastern United States. It spanned over 1,800 km (1,100 miles). Sandy slammed into the eastern seaboard on October 29, 2012, with massive winds and record-breaking storm surge and led to massive power outages in New York, New England, and the Mid-Atlantic states. See Figures 12A.1 and Figure 12A.2. Sandy had tropical and extra-tropical characteristics, brought high winds and coastal flooding, and made landfall on the New Jersey as a post-tropical cyclone with winds of 36 m/s (80 mph). Estimates of assessed damage have been about $75

Appendix 12A: Expanded Information on Superstorm Sandy

Figure 12A.1 Geographical extent of Sandy.

Figure 12A.2 Path of Sandy from October 22 to 30, 2012.

295

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billion (2012 USD), a total surpassed only by Hurricane Katrina4. In the United States, Hurricane Sandy affected 24 states, including the entire eastern seaboard from Florida to Maine and west across the Appalachian Mountains to Michigan and Wisconsin, with particularly severe damage in New Jersey and New York. Over 8.5 million customers experienced power outages. In New England, Hurricane Sandy severely impacted many regions with record wind and storm surge, resulting in a 4.3-m (14-ft) storm surge in Manhattan at the Battery monitoring station. Large swaths of New York City were without power due to preemptive shutdowns and severe flooding. As of October 31, over six million customers were still without power in 15 states and the District of Columbia, with nearly four million of these in New Jersey and New York alone; over a week later, more than 1.3 million were without power. The electric grid sustained substantial damage. Examples of the types of physical damage include the following: • • • • •



Broken poles and crossarms; Broken or damaged insulators; Conductor and static wire damage; Damage from trees being blown into the right of way; Flooding of substations and ground-mounted and underground electric equipment; Salt water intrusion into damage.

In addition to the energy electric sector, Sandy affected other utilities such as gas, communications, and water. Some natural gas lines broke causing fires in some locations. The FCC reported that 25% of cell sites across 10 states and Washington, D.C., were out of service.

4 An interagency team comprised of representatives from the U.S. National Cybersecurity and Communications Integration Center (NCCIC)/Industrial Control Systems Cyber Emergency Response Team (ICS-CERT), U.S. Computer Emergency Readiness Team (US-CERT), Department of Energy, Federal Bureau of Investigation, and the North American Electric Reliability Corporation traveled to Ukraine to collaborate and gain more insight.

About the Author Nicholas Abi-Samra is an expert in power system planning, operations, and maintenance across the energy value chain from power generation, through transmission and distribution systems to end use. He has developed a knowledge base of design practices, operational considerations, and analysis tools to evaluate potential impacts of many different types of threats, including extreme weather. Nicholas Abi-Samra received his education at the American University of Beirut, University of Missouri, and Carnegie-Mellon University. He has authored over 100 publications on diverse subjects related to power systems in the IEEE, CIGRE, and trade magazines. He has two U.S. patents, and is the winner of over a dozen prestigious industry awards. He served as the general chair and technical program coordinator for the 2012 IEEE Power & Energy Society (PES) General Meeting. He was also the chair of the Local Organizing Committee for the 2014 IEEE Safety Conference and served as the chair of the IEEE Power & Energy and the Power Electronics societies in San Diego for eight years. Presently he teaches several advanced courses in power systems that he has developed at the University of California San Diego. He is also the president of Electric Power & Energy Consulting. Before that, he held senior leadership positions at leading edge companies. Some of the positions that he held were senior vice president and regional director for the Americas at DNV GL (Kema); vice president at Quanta Technology; senior technical director at the Electric Power Research Institute (EPRI); and western region manager of Consulting, Advisory and Training Services at Westinghouse Electric. He was a Westinghouse Fellow and an EPRI senior technical executive, the highest technical positions at those two companies.

297

Index

1998 Auckland, New Zealand cable failures cited reasons for failures, 96 overview, 95–96 soil temperature, 97 soil thermal resistivity, 97 technical specification and design, 96–97 2003 heat wave: France lessons learned, 6–7 nuclear power plants, 5–6 overview, 5 values of concern, 6 water-use agreements and, 7 See also Case histories; Heat waves 2006 Auckland blackout, 97 2006 heat wave: France, 7–8 2006 heat wave: North America impact in California, 8–9 impact in Canada, 10 impact on power markets, 9–10 overview, 8 2011 heat wave demand response deployment of emergency reserves, 12 demand response usage, 10 ERCOT peak demand, 11 overview, 10 2012 heat wave, 12 2015 heat wave: Europe, 13–15 2015 heat wave: Poland lessons learned, 14–15 overview, 13–14 power plant failure, 14 2015 heat wave: Texas, 15–16 A Adaptability, 272, 274 Adaptive microgrids, 279 Advanced Fire Information System (AFIS), 194–95

Advanced metering infrastructure (AMI) technology, 78, 275 Aluminum conductor steel reinforced (ACSR), 146 Ambient air and water temperatures high, effect on power generation systems, 3 high, effect on thermoelectric power plants, 3–4 Ambient soil temperature, 89 Ampacity adjustment factor in determination, 92 cable, 82–85 conductor calculations, 82 insulation temperature rating and, 99 Ancillary services DR, 18 Angle structures, 199 Ardrossan, Ayrshire wind turbine (U.K.), 227 Australian Energy Market Operator (AEMO), 207 Australia wind farm cable failures, 97–98 B Backfill, 89 Backflashovers, 109–10, 111, 118 Backflash rate (BFR), 110, 112 Blackout event in South Australia (2016), 206–7 BPA’s corona loss approach conservative estimates, 164 example use of (230-kV line), 164–65 example use of (345-kV line), 165–66 overview, 163–64 sensitivity analysis, 166–67 See also Corona losses Bundle gradient average, 150 defined, 150 example calculations for, 152–53 maximum, 153

299

300

Bureau of Reclamation (BOR), 38 Buried underground cables. See Underground cables C Cable adjustment factor, 92 Cables. See Underground cables California drought changes of hydroelectric and gas-fired generation, 37 comparison aerial views, 36 cumulative precipitation, 35 effects on hydroelectric generation, 35–37 negative correlation, 37 See also Droughts California GO 95 districts map, 237 loading requirements summary, 243 NESC differences, 242–57 California heat wave (2006) conclusions, 78–79 effect on the aging of transformers, 77 failure of distribution transformers and, 61–79 hourly ambient temperature, 77 impact on power system, 62–63 introduction to, 61 lessons learned, 77–78 load on distribution transformer, 76 monthly transformer failures, 63 transmission and generation systems behaviors, 63–64 California State Water Resources Control Board (SWRCB), 56 Case histories 1998 Auckland, New Zealand cable failures, 95–97 2003 heat wave: France, 5–7 2006 Auckland blackout, 97 2006 heat wave: France, 7–8 2006 heat wave: North America, 8–10 2011 drought in Texas, 58 2011 heat wave, 10–12 2012 heat wave, 12 2015 heat wave: Europe, 13–15 2015 heat wave: Poland, 15–16 2015 heat wave: Texas, 15–16 Ardrossan, Ayrshire wind turbine (U.K.), 227 Australia wind farm cable failures, 97–98

Index

China snowstorm of 2008, 139–40 corona losses due to extreme contamination, 170–71 cyberattack, 290–91 cyclone Heta, New Zealand (2004), 189 drought effects on hydroelectric generation in California, 35–37 drought effects on Lake Mead and Hoover Dam, 38–40 firestorms, 195–96 Gross Eilstorf wind farm (Germany), 227 high-intensity winds (HIWs), 176, 182–91 high wind impact on wind turbines, 204–7 HIW storm, Brazil (2005), 189 Japan snow storm of 2005, 137–39 June 2012 derecho, 176 measurement of corona losses under hoarfrost, 170 microburst, France (1996), 189 microgrids, 280–81 Nissan factory wind farm (Sunderland, U.K.), 227 overview, 4–5 Pacific DC Intertie, 1989, 182–84 San Diego area fires, 195–96 Sweden (2005), 189–90 345-kV line cascade, Nebraska, 184 tornado damage in United States, 178 Ukraine power grid cyberattack, 290–91 underground cables, 95–98 water treeing and, 98–99 wind storm, Kansas (2006), 190–91 windstorms, Europe (1999), 187–89 China snowstorm of 2008, 139–40 CIGRE working groups, 134 Concrete poles, 244, 247 Conductor bundling, 150 Conductor surface gradient for bundled conductors average estimation, 150 defined, 150 example calculations for, 152–53 maximum, 153 overview, 150 transmission lines, 151 Conductor surface gradient for single conductor altitude and, 147 approximate equation for, 149 average, 147

Index

example calculations for, 149–50 examples, 148 maximum, 147 overview, 146–47 Coordinated attacks, 292 Corona defined, 145 effects on transmission lines, 145 onset, 154 Corona losses altitude and, 145 annual transmission line, 160–61 case histories, 170–71 conclusions, 171 conductor and surface gradients, 145–53 corona onset gradient, 153–57 decrease, with increase in phase conductor diameter, 166 dependencies, 145 due to extreme contamination, 170–71 estimating, 161–67 exercise, 171–73 expression of, 157 in fair weather, 157–58 in foul weather, 158 introduction to, 145 measurements under hoarfrost, 170 occurrence of, 157–60 rain and, 158–59 reduction of, 168–69 resistive losses comparison, 168 sensitivity analysis (heavy rain), 166–67 snow, ice, and hoarfrost and, 159–60 surface irregularity parameter and, 156–57 transmission line voltage upgrades and, 167–68 voltage considerations and, 167–69 voltage reduction and, 168 Corona onset gradient defined, 154 example calculations for, 155–56 overview, 153–54 surface gradient and, 156 surface irregularity parameter and, 156–57 Corona rings, 169 Critical flashover (CFO) voltage defined, 105 for lightning and switching impulse strengths, 107 Cumulative distribution function (CDF), 212

301

Cyberattacks, 289 Cybersecurity case history, 290 cybervulnerability examples, 289–90 lessons learned, 291 with microgrids, 284 overview, 288 threat types, 289 Cyclone Heta, New Zealand (2004), 189 D Dead-end structures, 199, 250–51 Demand response (DR) ancillary services, 18 defined, 17 economic, 18 emergency, 18 programs, 17 schemes, 17–18 in United States, 18–19 Denmark high wind event (2005), 204 Derating calculations, underground cables, 91–92 Derating factors, 93, 95 Derecho (June 2012), 176 Distributed energy resources (DERs), 277, 284 Distribution management systems (DMSs), 275 Distribution poles alternative materials, 247 application of guy wires to, 248 bracing technique, 248 concrete, 244, 247 failure, 254 hardening of, 235–40 physical hardening of, 234–35 steel, 245, 247 upgrading of, 236 wind forces illustration, 235 wind performance of, 235 wood, 243–45, 246–48 Distribution-SCADA (D-SCADA), 275 Distribution transformer failures California heat wave (2006) and, 61–79 conclusions, 78–79 during heat waves, 64–65 lessons learned, 77–78 percentage, 63 rate of, 62 relative monthly, 63

302

Distribution transformers hot spot and top oil temperatures during heat waves, 65–66 IEEE C57.91-1995 and, 67–77 incremental aging, 76 loading and failure mechanisms, 64–65 loss of life formulation, 67–69 rating practices, 64 remaining life estimation, 67 solar heating and, 72–77 thermal mechanisms, 69 Diversion-type hydroelectric plants, 30–32 Drought effects case histories 2011 Texas, 58 hydroelectric generation in California, 35–37 Lake Mead and Hoover Dam, 35–37 summaries, 43–46 Droughts case histories, 35–40, 58 categories and potential impacts, 24 conclusions, 40–41 defining, 24 diversion-type hydroelectric plants and, 30–32 effect on hydroelectric power plants, 29–33 effect on thermoelectric power plants, 47–58 impoundment-type hydroelectric plants and, 29–30 introduction to, 23 pumped-storage type hydroelectric plants and, 32–33 solar PV power and, 287 Dry cooling defined, 54 installations, 54–55 overview, 53–54 schematic, 54 See also Thermoelectric cooling Dynamic pitch angle control, 223 E Economic DR, 18 EF-scale classification of tornadoes, 199, 200 Electric energy, water potential energy conversion into, 26–27 Electric Power Research Institute (EPRI), 55 Electromagnetic interference (EMI), 145 Emergency DR, 18

Index

ENERCON Storm Control, 224 Extra-high-voltage (EHV), 126 Extreme coherent gust (ECG), 232 Extreme operating gust (EOG), 232 Extreme weather buried underground cables and, 81–101 corona loss calculation, 163–67 See also Droughts; Heat waves F Fair weather corona losses overview, 157–58 Peek’s approach for calculating, 161 Peterson’s approach for calculating, 161–63 Federal Energy Regulatory Commission (FERC), 18–19 Finland corona losses measurement under hoarfrost, 170 Fires (wind turbines) case histories, 227 causes of, 226 depiction of, 226 effect of high winds on, 225–27 Firestorms case histories, 195–96 overview, 193–94 San Diego area fires, 195–96 South African Advanced Fire Information System (AFIS), 194–95 Flashover on insulator covered with snow and ice, 141 minimum voltage on insulator strings, 135 of partially covered insulators, 132–34 voltage tests of snow-accreted insulators, 139 Floods hardening against floods, 261–62 post actions, 262 substation, measures to reduce impact, 262 substation concerns, 260–62 Foul weather corona losses, 158 F-scale classification of tornadoes, 199, 200 G General loading map, 236 Geometric mean distance (GMD), 152, 153 Grand Coulee Dam, 30, 31 Grid resilience adaptability, 274 defined, 267

Index

defining system resiliency and, 271–88 hardening, 271–73 inherent, 271 introduction to, 267 microgrids and, 276–84 rapid recovery, 274 ride through, 273–74 security and, 288–92 social media and, 275 solar PV power and, 284–88 summary and conclusions, 292–93 Superstorm Sandy, 268–71, 284–88 use of smart grid to increase, 274–75 Gross Eilstorf wind farm (Germany), 227 Ground flash density (GFD), 107 Grounding systems impulse and low-frequency resistances, 115 parallel grounding rods, 114 tower footing resistance (TFR), 115 transmission lines, 113–15 transmission towers, 111–13 Ground wires, wind pressure on, 241 Guyed structures, 198–99 H Hardening (system resiliency) , 273 defined, 271 modeling issues, 272 systems and components planning, 272–73 Heat waves 2003: France, 5–7 2006: California, 61–79 2006: France, 7–8 2006: North America, 8–10 2011, 10–12 2012, 12 2015: Poland, 13–15 2015: Texas, 15–16 case histories, 4–27 defining, 20–21 hot spot and top oil temperatures during, 65–66 overview of possible footprints, 1 power transformers and, 2 preparation for, 16–17 solar PV power and, 287 High-intensity winds (HIWs) cascade failures, 193 case histories, 176, 182–91

303

cyclone Heta, New Zealand (2004), 189 damage to transmission and distribution infrastructure, 177–81 data collection after the storm, 191 defining, 175–76 design considerations and, 191–92 effect on power delivery system, 175–202 failure analysis from, 178–81 hardening/quick restoration balance and, 193 HIW storm, Brazil (2005), 189 hurricanes and, 179–80 identification of, 175 impact on aerial conductors, 181 introduction to, 175 list of techniques to reduce, 213 microburst, France (1996), 189 Pacific DC Intertie, 1989, 182–84 physical hardening against, 234–59 salient lessons learned from, 191–93 summary and conclusions, 201–2 Sweden (2005), 189–90 345-kV line cascade, Nebraska, 184 types of, 176 upgrading and retrofitting existing structures and, 192 windstorms, Europe (1999), 187–89 High wind impact on wind turbines blackout event in South Australia (2016), 206–7 case histories, 204–7 conclusions, 227–28 Denmark (2005), 204 hardening against, 212–14 hurricanes, 211–12 introduction to, 203 ride-through capability, 222 stresses, 207–11 Taiwan (2008), 205 United Kingdom (2011 and 2015), 205 HIW storm, Brazil (2005), 189 Hoarfrost corona losses and, 159–60 defined, 159 measurements of corona losses under, 170 Hoover Dam enhancing the power pool level of, 39–40 hydroelectric generation, 39 intake structures, 39 “wide-head,” 40

304

Hot spot temperature derivation of, 69–72 during heat waves, 65–66 rise, 72 Hurricanes damage from, 180 heavy rains and storm surge, 180–81 utility systems and, 179–80 wind turbine vulnerability to, 211–12 Hybrid cooling, 55 Hybrid wind turbine shutdown, 220–21 Hydroelectric generation California drought and, 35–37 Hoover Dam, 39 variability, 33–34 Hydroelectric power plants classifications of, 25–26 dam schematic, 27 diversion-type, 30–32 dought case histories and, 35–40 drought effects on, 29–33 impoundment-type, 29–30 penstock sizing, 28–29 pumped-storage type, 25, 32–33 run-of-the-river (ROR), 32, 41 turbines, 28–29 variability of generation, 33–34 water use by, 24–25 Hydroelectric turbines, 28–29 I Icing stress product (ISP), 134 IEC 61400, 230–31 IEC wind turbine classes, 231–32 IEEE C57.91-1995 Clause 7, 67, 69–77 defined, 67 per-unit loss of life, 67–68 in remaining life estimation, 67 solar heating and, 72–77 table, 68 thermal model for transformer aging, 69–77 transformer loss of life formulation, 67–69 IEEE Gold Book, 62 IEEE Standard 1783, 136–37 Impoundment-type hydroelectric plants, 29–30 Impulse resistance, 115–16, 117–19 Insulator dielectric strength electrical withstand reduction, 134–36 rain effect on, 129–31

Index

snow and ice effects on, 131–32 Insulators EHV, 134 minimum flashover voltages of, 135 partially covered, 132–34 snow-/ice-covered, 132 snow-/ice-covered, withstand voltage, 136 Integrated vegetation management (IVM), 257 Intergovernmental Panel on Climate Change (IPCC), 20–21 J Japan snow storm of 2005 flashover voltage tests, 139 investigation of failures, 137 overview, 137 snow accumulation on insulators, 138 L Lake Mead background and characteristics, 38 impact of prolonged droughts on, 40 surface elevation, 38 Lake Powell, 38 Lightning backflashover analysis modeling, 118 backflashovers and, 109–10, 111 ground flash density (GFD), 107 strokes to transmission lines, 108–9 Lightning overvoltages, 107–8 Line-insulation coordination defined, 104 goal behind, 104 overview, 104–5 summary of requirements, 126–27 Locational marginal price (LMP), 19 Low-frequency resistance, 115–16 M Mechanical brakes, wind turbine, 221–22 Microburst, France (1996), 189 Microgrids adaptive, 279 adaptive protection applications for, 280 benefits of, 277, 283 in black-start scenarios after a storm, 281–82 case histories, 280–81 categories of, 277 cybersecurity with, 284 electrical power from, 279

Index

example illustration, 276 future of, 282–83 overview, 276–77 protection issues with, 279–80 static, 279 supervisory controller for, 278–79 types of, 277–78 virtual, 278 See also System resiliency MKS system, 27 Moderate resolution imaging spectroradiometer (MODIS), 194 Moisture, soil thermal resistivity and, 85– 87 N National Aeronautics and Space Administration (NASA), 5 National Electric Safety Code (NESC), 126, 236 California GO 95 and, 242 general loading map, 236 loading requirements summary, 242 requirements for vegetation management, 254–57 Rule 250C1, 240–42 strength factors, 239–40 wind load calculations, 239 National Oceanic and Atmospheric Administration (NOAA), 5 National Renewable Energy Laboratory (NREL), 25, 40 Nissan factory wind farm (Sunderland, U.K.), 227 North American Electric Reliability Corporation (NERC), 269, 291–92 O Once-through cooling (OTC) system defined, 50 phaseout in California, 56 surface water sources, 51 water consumption of, 51 P Pacific DC Intertie, 1989 description of event, 182 event toll, 182 illustrated, 183 lessons learned, 182 tower strengthening measures and, 184

305

Palmer hydrological drought index (PHDI), 23 Peek’s expression for corona loss, 161 Penstock, sizing of, 28–29 Peterson’s corona loss formula, 161–63 Phase conductors, wind pressure on, 240–41 Physical security, 291–92 Pitch angle control in combination with stall regulation, 220–21 dynamic, 223 illustrated, 213 ramp-rate, 223 in stopping wind turbines, 216–18 Pole-mounted equipment, 249–50 Poles. See Distribution poles Pole-top distribution transformer model, 74 solar azimuth and altitude, 75 solar heat gain, 75 solar heating of, 72–77 Potential energy of water, 26–27 Power systems heat wave effects on, 1–3 high ambient and water temperature effects on, 3 high wind effects on, 175–81 resiliency, 271–88 structural hardening against storms, 233–65 tornado damage on, 177 Power transformers heat waves and, 2 permissible load, 3 Pumped hydro plants, 25 Pumped-storage type hydroelectric plants, 32–33 R Rain conductor aging and, 159 corona losses and, 158–59 insulator dielectric strength and, 129 lightning and switching surge withstand effects, 131 sensitivity analysis of corona loss under, 166–67 soil thermal resistivity and, 86–87 surface irregularity parameter and, 156–57 vertical insulator strings susceptibility to, 130

306

Rainfall rate, 130 Ramp-rate pitch angle control, 223 Rapid recovery, 272, 274 Recirculating systems, 52–53 Resistance impulse, 115–16, 117–19 low-frequency, 115–16 tower footing (TFR), 115, 116–19 Ride-through (system resiliency) defined, 272 resources, processes and human factors, 273–74 systems and components issues, 273 Ride-through capability, 222 Room temperature vulcanization (RTV), 132 Running above higher wind conditions approaches to, 222–25 dynamic control of pitch angle, 223 ENERCON Storm Control, 224 implementation by manufacturers, 224–25 overview, 222 ramp-rate control of pitch angle, 223 Siemens high-wind ride through, 225 See also Wind turbines Run-of-the-river (ROR), 32, 41 S San Diego area fires, 195–96 San Onofre Nuclear Generating Station (SONGS), 56–57 Security. See Cybersecurity; Physical security Self-supporting structures, 199 Siemens high-wind ride through, 225 Smart grid, 274–75 Snow and ice accumulation on post, 133 corona losses and, 159–60 dead-end-transmission line structure with, 133 dielectric failures and, 132 electrical withstand reduction due to, 134–36 flashover on insulator covered with, 141 insulator dielectric strength and, 131–32 surface irregularity parameter and, 156–57 withstand voltage per insulator length, 136 Snow conductivity, 135 Social media, 275 Soil electrical resistivity defined, 119

Index

dependence on temperature, 122–23 lightning performance and, 119–21 measurements, 123 in TFR calculation, 117 typical ranges of, 119 Soils moisture content, 123 seasonal variations of grounding resistance, 121 sensitivities of, 120 Soil temperature, 89, 122–23 Soil thermal resistivity 1998 Auckland, New Zealand cable failures, 97 backfill and, 89–90 dry density and composition and, 87–89 influencing factors of, 85–91 moisture and, 85–87 organic and quartz dependencies, 88 rain effect on, 86–87 sensitivity to, 121 thermal runway and, 90–91 variations along the circuit and, 89 Solar altitude, 73–74, 75 Solar azimuth, 73–74, 75 Solar declination, 73 Solar heating calculation symbols, 73 heat gain value, 76 pole-top distribution transformer, 72–77 Solar PV power concerns with standards and, 285–86 coupled with battery energy storage, 286 droughts and heat waves and, 287 overview, 284–85 performance during Superstorm Sandy, 284–88 rate structure impacts, 287–88 smart battery inverter systems and, 286–87 South African Advanced Fire Information System (AFIS), 194–95 Stall regulation active schemes, 220 in combination with pitch control, 220–21 disadvantages of, 220 illustrated, 218 passive schemes, 218–19 stopping wind turbines with, 218–20 See also Wind turbine shutdown Static microgrids, 279

Index

Steel poles, 245, 247 Storm surge damage due to, 180–81 hardening against, 260–63 Stresses from high winds, wind turbines, 207–11 Stress strength analysis, 106 Strokes, lightning, 108–9 Structural hardening dead-end structures, 250–51 of distribution line poles, 234–35 distribution system, 234–59 against floods and storm surges, 260–63 against HIWs, 234–59 introduction to, 233–34 pole-mounted equipment, 249–50 shorter spans, 248–49 smaller conductors, 249 strategies against wind storms, 259–60 summary and conclusions, 264–65 undergrounding of overhead structures, 257–59 vegetation management, 251–57 Substation flooding circuit breakers, 263 concerns, 260–62 hardening against, 261–62 lessons learned for measures to reduce, 262 lessons learned from post flood actions, 262–63 transformers, 263 Superstorm Sandy defined, 268 general information on, 294–96 geographical extent of, 295 overview, 268–69 path of, 295 power restoration, 269–70 samples of damages, 268, 269, 296 solar PV power performance during, 284–88 utility preparation for, 269–70 Supervisory control and data acquisition (SCADA), 65, 78 Surface gradients altitude and, 147 approximate equation for (single conductors), 149–50 average, 147 bundled conductors, 150–53

307

corona offset gradient and, 156 defined, 145 determination at corona onset, 154 examples, 148 maximum, 147 single conductors, 146–50 Surface irregularity parameter, 156–57 Surge impedance loading (SIL), 150 Sweden (2005), 189–90 Switching overvoltages (SOVs), 127 System resiliency adaptability, 274 defining, 271–88 hardening, 271–73 microgrids in, 276–84 rapid recovery, 274 ride through, 273–74 social media and, 275 solar PV power and, 284–88 use of smart grid to increase, 274–75 T Taiwan high wind event (2008), 205 Tangent structures, 198 Temporary overvoltages (TOVs), 157 Thermal capacity, 71 Thermalito Power Canal, 31 Thermal resistivity adjustment factor, 94 of common components, 85 moisture and, 85–87 of soil, 85–91 underground cables, 83 Thermal runaway, 90–91 Thermoelectric cooling case study, 56–57 dry cooling, 53–54 hybrid cooling, 55 OTC, 50–51, 56–57 recirculating systems, 52–53 technologies, 50–55 vintage systems in United States, 50 Thermoelectric power plants case history: drought of 2011 in Texas, 58 conclusions, 57–58 cooling technologies, 50–55 drought effect on, 47–58 fresh water withdrawals by, 48 heat waves and, 2

308

Thermoelectric power plants (Cont.) high ambient and water temperature effects on, 3–4 hybrid cooling, 55 introduction to, 47–48 phaseout of OTC in California, 56–57 water usage in United States, 48–50 water use in, 47 Third Power Plant, Grand Coulee Dam, 30, 31 345-kV line cascade, Nebraska description of event, 184 event toll, 184–85 general failure of mechanism, 185–86 lessons learned, 186–87 tower failure, 185 Top oil temperature C57.91 Clause 7, 69–70 rise, 72 time constant correction, 71 transformer faults and failure and, 66 Top-oil time constant, 70 Tornado alley, 200–201 Tornado classifications, 199–200 Tornado damage examples on power grid, 177 toppled transmission line tower, 179 in United States, 178 Tower footing resistance (TFR) calculation method, 116–19 current dependence of, 116 drying of soils and, 103 estimation exercise, 124 example estimation, 117–19 target level, 115 Tower structures angle structures, 199 common types of, 198–202 dead-end structures, 199 guyed structures, 198–99 self-supporting structures, 199 tangent structures, 198 tornado alley and, 200–201 See also Transmission line towers Transient temperatures, 71 Transmission line insulation case histories, 137–40 China snowstorm of 2008, 139–40 chronological sequence of flashover, 132 conclusions, 140–41

Index

design and specification, 104 dielectric failures, 132 electrical withstand reduction, 134–36 IEEE Standard 1783 and, 136–37 Japan snow storm of 2005, 137–39 rain effect on insulator dielectric strength, 129–31 snow/ice effect on insulator dielectric strength, 131–32 winter precipitation effects on, 129–41 Transmission lines aerial conductors, wind force on, 181 annual corona losses, 160–61 backflashovers, 109–10, 111 backflash rate (BFR), 110, 112 corona losses, 145 grounding systems, 113–15 lightning overvoltages, 107–8 parallel grounding rods, 114 strokes to, 108–9 supplemental grounding system, 113 voltage upgrades, 167–68 Transmission line towers connection to electrodes, 113 grounding of, 111–13 illustrated, 105 with two-conductor phase conductors, 152 See also Tower structures U Ukraine power grid cyberattack, 290–91 Ultra-high-voltage (UHV), 126 Underground cables 1998 Auckland, New Zealand failures, 95–97 ambient and conductor temperature adjustment factor, 92–95 ampacity and thermal conditions, 82–85 cable-soil system for heat transfer, 84 conclusions, 99 derating calculations, 91–92 dry zone formation, 99 exercise, 100–101 extreme weather and, 81–101 introduction to, 81 overexposure to moisture, 81 steady-state current rating computations, 84 thermal resistivity, 83, 85 Undergrounding distribution lines, 257

Index

electric facilities, 257–58 of overhead structures, 257–59 transmission lines, 258–59 United Kingdom high wind events (2011 and 2015), 205 United States demand response in, 18–19 ground electrical resistance data, 123 hydroelectric generation variability, 33–34 mix of bulk system power generating technologies, 49 NESC general loading map, 236 thermoelectric plat water usage, 48–50 tornado damage in, 178 vintage cooling systems, 50 United States Geological Survey (USGS), 24, 48 Urban heat island (UHI) effect, 21 V Vegetation management costs of, 253–54 cycle, 254 integrated (IVM), 257 lessons learned on, 254–57 NESC requirements, 253 overview, 251–52 scope of, 252–53 targeted, 255 use of drones for, 255 See also Structural hardening Virtual microgrids, 278 Voltage corona losses and, 167 critical flashover (CFO), 105, 107 reduction as means of reducing corona losses, 168 transmission line upgrades, 167–68 W Water consumption definition, 24 OTC consumption, 51 potential energy conversion, 26–27 use by hydroelectric plants, 24–25 Water treeing, 98–99 Wind pressure on ground wires, 241

309

on phase conductors, 240–41 on structure, 242 Wind storm, Kansas (2006), 190–91 Windstorms, Europe (1999) description of event, 187 French government intervention, 188–89 lessons learned, 188 storm toll, 188 Wind turbines cut-in/cut-out speeds, 209–10 effect of high winds on fires in, 225–27 hardening against high winds, 212–14 high wind impact on, 203 high wind speed shutdown, 215 IEC classes, 231–32 maximum power curve, 209 mechanical brake, 213 mechanical power, 208 pitch angle, 208 pitch control, 213 power coefficient, 210 power output versus speed, 210 ride-through capability, 222 running above higher wind conditions, 222–25 supporting towers, 213 vulnerability to hurricanes, 211–12 yaw control, 213 See also High wind impact on wind turbines Wind turbine shutdown hybrid method, 220–21 illustrated, 215 by mechanical brake, 221–22 methods of, 215–22 overview, 215 by pitch regulation, 216–18 with stall regulation, 218–20 Wood poles alternative materials, 247 bending load, 244 classes, 243 in-place hardening, 246–48 replacing with steel (and other) poles, 245 specification, 244 See also Distribution poles World Meterological Organization (WMO), 4–5, 21