Renewable Energy Production and Distribution: Recent Developments 0323918921, 9780323918923

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Renewable Energy Production and Distribution

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Renewable Energy Production and Distribution Recent Developments VOLUME 1

Edited by Mejdi Jeguirim

The Institute of Materials Science of Mulhouse (IS2M), University of Haute Alsace, University of Strasbourg, CNRS, Mulhouse, France

Academic Press is an imprint of Elsevier 125 London Wall, London EC2Y 5AS, United Kingdom 525 B Street, Suite 1650, San Diego, CA 92101, United States 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom Copyright Ó 2022 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein).

Notices

Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. ISBN: 978-0-323-91892-3 For information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Charlotte Cockle Acquisitions Editor: Lisa Reading Editorial Project Manager: Joshua Mearns Production Project Manager: Kamesh Ramajogi Cover Designer: Vicky Pearson Esser

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Dedicated to the memory of my father Mongi Jeguirim from whom I have learnt to be helpful in all honor.

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Contents List of contributors

xv

Part I Solar thermal energy 1.

Utilization of mono and hybrid nanofluids in solar thermal collectors Osama Ayadi, Otabeh AleOran, Mohammad Hamdan, Tareq Salameh, Afif Akel Hasan, Adel Juaidi, Ramez Abdallah and Mustafa Jaradat 1.

2. 3.

4. 5.

2.

Introduction 1.1 Status of solar energy markets 1.2 Solar thermal collectors (ST) 1.3 Enhancement of solar thermal collectors Performance of flat plate solar collector (FPSC) using hybrid nanofluids Performance of evacuated tube solar collectors (ETSC) using nonfluids 3.1 Metal nanofluids 3.2 Metal oxide nanofluids 3.3 Carbon nanofluids 3.4 Hybrid or combination nanofluids Performance of concentrated solar collectors using hybrid nanofluids Conclusions References

3 4 5 5 8 11 11 14 19 22 22 38 40

Solar air heater performance improvement by photovoltaic-powered thermoelectric heat pumping Josue´ Rock Segnon and Howard Okezie Njoku 1.

Introduction 1.1 Designs of solar energy systems 1.2 Thermoelectric-integrated solar energy systems

45 45 49

vii

viii Contents 2.

Materials and methods 2.1 System description 2.2 Experimental procedures 3. Results and discussions 3.1 Indoor experiments 3.2 Outdoor experiments 4. Conclusions References

52 52 55 58 58 62 64 65

Part II Solar photovoltaic energy 3.

A grid connected PV system based on a reduced delta inverter Asma Ben Rhouma 1. 2.

3.

4.

5. 6. 7.

4.

Introduction PV system 2.1 Description of the PV system 2.2 Description of the PV panel 2.3 DC/DC boost converter 2.4 MPPT controls for DC/DC converters 2.5 Simulation results of the PV system Modeling of the conventional DC/AC inverter connected to the grid 3.1 Structure 3.2 Mathematic model of the grid 3.3 Conventional control strategy Modeling of the delta inverter connected to the grid 4.1 Structure of the delta inverter 4.2 Photovoltaic delta inverter configuration 4.3 Photovoltaic delta inverter connected to the grid 4.4 Dedicated control strategy for the photovoltaic delta inverter connected to the grid Simulation results Experimental results Conclusion References

71 73 73 74 75 76 76 81 81 81 83 86 86 87 88 88 94 98 103 103

An experimental test bench for emulating the standard characteristics of photovoltaic (PV) systems Intissar Moussa and Adel Khedher 1. 2.

Introduction PVS general overview 2.1 PV cells technologies 2.2 PV systems topologies and types

107 109 110 113

Contents

3.

4.

5. 6.

2.3 PV models 2.4 Static and dynamic parameters extraction of PVS 2.5 Control methods of PVS Proposed PV emulator design 3.1 PV model choice 3.2 PV emulator synoptic diagram Real-time (RT) digital simulation and hardware-in-the-loop (HIL) test of the PVE 4.1 RT PV digital simulation 4.2 HIL test and validation of the PVE controller Experimental test bench and results Conclusion Appendix Acknowledgments References

ix 114 118 118 120 121 122 125 125 126 130 132 133 133 133

Part III Bioenergy production 5.

Green pellets production and applications in energy sector Mejdi Jeguirim and Besma Khiari 1. 2.

Introduction Biomass pellets production 2.1 Biomass raw materials: types, composition, and characterization 2.2 The pelletization process 2.3 Pellets characterization 3. Pellets combustion 3.1 Domestic use combustion technologies 3.2 Communal and industrial use combustion technologies 3.3 Combined heat and power production at domestic scale 3.4 Biomass based power production 4. Conclusion References

139 141 141 146 147 149 149 166 172 173 179 182

Part IV Hydrogen production 6.

Hydrogen production by supercritical water gasification: a review Ibtissem Houcinat, Nawel Outili, Bele´n Garcı´a-Jarana, Jezabel Sa´nchez-Oneto, Juan R. Portela and Abdeslam-Hassen Meniai 1. 2.

Introduction Supercritical water gasification process

189 190

x Contents 2.1 Supercritical water properties 2.2 The supercritical water gasification of biomass 2.3 Reaction mechanism of hydrogen production by hydrothermal gasification 3. Hydrogen production reactors in supercritical gasification 3.1 Batch process 3.2 Continuous process 3.3 Pilot scale process 4. Effect of operating parameters on hydrogen production in supercritical water gasification 4.1 Temperature 4.2 Feed concentration 4.3 Residence time 4.4 Pressure 4.5 Catalytic supercritical water gasification 5. Hydrothermal gasification challenges 6. Conclusion References

190 192 196 197 198 199 202 203 203 205 207 208 210 215 218 219

Part V Wind energy 7.

Wind energy in Jordan and Palestine: current status and future perspectives Adel Juaidi, Ramez Abdallah, Osama Ayadi, Tareq Salameh, Afif Akel Hasan and Ahmad Ramahi 1.

Introduction 1.1 Country overviewdJordan 1.2 Country overviewdPalestine 1.3 Energy status and renewable energy in Jordan 1.4 Energy status and renewable resources in Palestine 1.5 Objective and scope of the chapter 2. Wind energy potentials in Jordan and Palestine 2.1 Wind speed and potentials in Jordan 2.2 Wind speed and potentials in Palestine 3. Pilot and commercial projects in Jordan and Palestine 3.1 Pilot and commercial projects in Jordan 3.2 Wind energy projectsdPalestine 4. Future perspectives of wind energy in Jordan and Palestine 4.1 Future perspectives for wind energy in Jordan 4.2 Future perspectives for wind energy in Palestine 5. Conclusions References

229 229 232 234 237 238 240 240 250 257 257 262 263 263 264 265 265

Contents

xi

Part VI Geothermal energy 8.

Tapping hot rocks: a review of petrothermal energy and Enhanced Geothermal Systems (EGSs) Markus Loewer and Maximilian Keim 1. 2. 3.

Introduction Technological retrospective Methodology 3.1 Creation of the reservoir 3.2 Borehole stimulation 3.3 Chemical stimulation 3.4 Monitoring 4. EGS in the context of global deep geothermal energy 4.1 Fenton Hill (United States) 4.2 Rosemanowes Quarry (United Kingdom) 4.3 Hijiori (Japan) 4.4 Soultz-sous-Foreˆts (France) 4.5 Basel (Switzerland) 5. The technical potential of the example of Germany 6. Discussion and comparison 6.1 HDR versus EGS 6.2 Back to the HDR concept? 6.3 Differences from natural gas and oil fracking 7. Environmental aspects 7.1 Life cycle analysis 7.2 Groundwater protection and scalings 7.3 Induced seismicity 8. Conclusion References

273 274 275 275 278 279 281 282 283 284 284 285 285 286 287 287 288 289 290 290 291 291 292 293

Part VII Hydropower 9.

Retrofitting and Refurbishment of hydropower plants: case studies and novel technologies Emanuele Quaranta and Julian Hunt 1. 2. 3. 4.

Introduction Benefits of hydropower modernization Dam heightening Waterways and penstocks 4.1 Reduction of the wall roughness by special lining and coating

301 302 303 304 304

xii Contents 4.2 Increase of the diameter of the headrace tunnel and shaft or penstock 4.3 Providing a new parallel waterway system for RHPPs 5. Inflow increase and larger equipment 6. Efficiency increase at best efficiency point (BEP) 7. Efficiency improvement at part load 8. Digitalization and flow forecast 9. Integration with other energy sources 10. Environmental and practical considerations 11. Conclusions Acknowledgment References

305 305 306 307 309 311 312 313 315 315 315

Part VIII Energy storage 10.

Thermocline packed bed thermal energy storage system: a review Baoshan Xie, Nicolas Baudin, Je´roˆme Soto, Yilin Fan and Lingai Luo 1. 2.

3.

4.

5.

6.

Introduction Packed bed thermal energy storage system components 2.1 Solid fillers 2.2 Heat transfer fluid 2.3 Wall and insulation Performance evaluation and influence factors 3.1 Performance evaluation indicators 3.2 Performance influencing parameters Types of thermocline packed-bed systems 4.1 Sensible-heat thermocline packed-bed (SHTPB) system 4.2 Latent-heat thermocline packed-bed (LHTPB) system 4.3 Heterogeneous-heat thermocline packed-bed (HHTPB) system Numerical models 5.1 Single phase models 5.2 Two phase models 5.3 Three-phase models 5.4 Comparison and improvement of models 5.5 Experimental validation cases Conclusion Acknowledgment References

325 328 329 333 334 335 335 343 347 348 351 357 360 361 362 364 366 366 371 372 372

Contents

xiii

Part IX Smart grids 11.

Long-term load forecasting in the smart grid framework using time series and econometric approaches S. Essallah and Adel Khedher 1. 2.

Introduction Dataset 2.1 Load pattern 2.2 Influencing factors 3. Time series approaches 3.1 ARIMA models 3.2 Nonlinear autoregressive neuronal network, NAR 4. Econometric approaches 4.1 MLR technique 4.2 NARX technique 5. Performance measurement criteria 6. Simulation results and discussion 7. Conclusion References

12.

389 393 393 393 396 397 399 399 400 400 401 403 410 410

A short review of grid voltage sags and current control techniques of voltage source inverters in distributed power generation systems Mohamed Hamdi and Mahmoud Hamouda 1. 2. 3.

Introduction Grid faults and voltage sags characteristics Voltage support concept and strategies to determine active and reactive power injected by the VSI during the fault and postfault operation 3.1 Power injection in case of purely inductive grid impedance: voltage support oriented strategy proposed in Ref. [19] 3.2 Power injection in case of resistive-inductive grid impedance: voltage supporteoriented strategy proposed in Ref. [20] 4. Current control methods 4.1 Control principle 4.2 Voltage oriented control technique in a double dq synchronous reference frame 4.3 Voltage oriented control in the ab stationary reference frame 4.4 Finite control set model predictive control 5. Conclusion References

415 417 425 425 431 435 435 435 437 438 442 443

xiv Contents

Part X Sustainability, policies, and regulations 13.

Sustainable renewable energy policies and regulations, recent advances, and challenges Michail Tsangas, Antonis A. Zorpas and Mejdi Jeguirim 1. 2. 3.

Introduction Energy planning policy advances Renewable energy policy challenges 3.1 Political challenges 3.2 Economic challenges 3.3 Social challenges 3.4 Technical challenges 3.5 Environmental challenges 3.6 Summary of challenges 4. Conclusion and recommendations References

Index

449 451 454 455 455 457 458 458 459 460 461

467

List of contributors Ramez Abdallah, Mechanical & Mechatronics Engineering Department, Faculty of Engineering & Information Technology, An-Najah National University, Nablus, Palestine Otabeh AleOran, Mechanical Engineering Department, The University of Jordan, Amman, Jordan; Department of Energy Engineering, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Budapest, Hungary Osama Ayadi, Mechanical Engineering Department, The University of Jordan, Amman, Jordan; Renewable Energy Technology Department, Applied Science Private University, Amman, Jordan Nicolas Baudin, Nantes Universite´, CNRS, Laboratoire de thermique et e´nergie de Nantes, LTeN, Nantes, France Asma Ben Rhouma, Universite´ de Sousse, Ecole Nationale d’Inge´nieurs de Sousse, LATIS-Laboratory of Advanced Technology and Intelligent Systems, Sousse, Tunisia S. Essallah, Universite´ de Sousse, Ecole Nationale d’Inge´nieurs de Sousse, LATISLaboratory of Advanced Technology and Intelligent Systems, Sousse, Tunisie Yilin Fan, Nantes Universite´, CNRS, Laboratoire de thermique et e´nergie de Nantes, LTeN, Nantes, France Bele´n Garcı´a-Jarana, Department of Chemical Engineering and Food Technology. Faculty of Sciences. University of Cadiz, Campus Universitario Rı´o San Pedro s/n, Puerto Real, Spain Mohammad Hamdan, Mechanical Engineering Department, The University of Jordan, Amman, Jordan Mohamed Hamdi, Higher Institute of Technological Studies, Department of Electrical Engineering, Gafsa, Tunisia Mahmoud Hamouda, Research Laboratory LATIS, National Engineering School of Sousse, University of Sousse, Sousse, Tunisia Afif Akel Hasan, Mechanical & Mechatronics Engineering Department, Birzeit University, Birzeit, Palestine; Department of Mechanical Engineering, Birzeit University, Birzeit, Palestine Ibtissem Houcinat, Laboratoire de l’Inge´nierie des Proce´de´s de l’Environnement, De´partement de Ge´nie Chimique, Universite´ Constantine 3 Salah Boubnider, Constantine, Algeria

xv

xvi List of contributors Julian Hunt, International Institute for Applied Systems Analysis, Laxenburg, Austria Mustafa Jaradat, Energy Engineering Department, German Jordanian University, Amman, Jordan Mejdi Jeguirim, The Institute of Materials Science of Mulhouse (IS2M), University of Haute Alsace, University of Strasbourg, CNRS, Mulhouse, France Adel Juaidi, Mechanical & Mechatronics Engineering Department, Faculty of Engineering & Information Technology, An-Najah National University, Nablus, Palestine Maximilian Keim, Technical University of Munich, Geothermal-Alliance Bavaria, Munich Institute of Integrated Materials, Energy and Process Engineering, Germany Adel Khedher, Universite´ de Sousse, Ecole Nationale d’Inge´nieurs de Sousse, LATIS Laboratory of Advanced Technology and Intelligent Systems, Sousse, Tunisie Besma Khiari, Wastewaters and Environment Laboratory, Water Research and Technologies Center (CERTE), Technopark Borj Cedria, University of Carthage, Tunisia Markus Loewer, Technical University of Munich, Geothermal-Alliance Bavaria, Munich Institute of Integrated Materials, Energy and Process Engineering, Germany Lingai Luo, Nantes Universite´, CNRS, Laboratoire de thermique et e´nergie de Nantes, LTeN, Nantes, France Abdeslam-Hassen Meniai, Laboratoire de l’Inge´nierie des Proce´de´s de l’Environnement, De´partement de Ge´nie Chimique, Universite´ Constantine 3 Salah Boubnider, Constantine, Algeria Intissar Moussa, Universite´ de Sousse, Ecole Nationale d’Inge´nieurs deSousse, LATIS-Laboratory of Advanced Technology and Intelligent Systems, Sousse, Tunisie Howard Okezie Njoku, Sustainable Energy Engineering Research Group, University of Nigeria, Nsukka, Nigeria; Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa Nawel Outili, Laboratoire de l’Inge´nierie des Proce´de´s de l’Environnement, De´partement de Ge´nie Chimique, Universite´ Constantine 3 Salah Boubnider, Constantine, Algeria Juan R. Portela, Department of Chemical Engineering and Food Technology, Faculty of Sciences, University of Cadiz, Campus Universitario Rı´o San Pedro s/n, Puerto Real, Spain Emanuele Quaranta, European Commission Joint Research Centre, Ispra, Italy Ahmad Ramahi, Industrial Engineering Department, An-Najah National University, Nablus, Palestine Tareq Salameh, Department of Sustainable and Renewable Energy Engineering, College of Engineering, University of Sharjah, Sharjah, United Arab Emirates

List of contributors xvii

Josue´ Rock Segnon, Sustainable Energy Engineering Research Group, University of Nigeria, Nsukka, Nigeria Je´roˆme Soto, Nantes Universite´, CNRS, Laboratoire de thermique et e´nergie de Nantes, LTeN, Nantes, France; Institut Catholique d’Arts et Me´tiers de Nantes, ICAM, Carquefou, France Jezabel Sa´nchez-Oneto, Department of Chemical Engineering and Food Technology, Faculty of Sciences, University of Cadiz, Campus Universitario Rı´o San Pedro s/n, Puerto Real, Spain Michail Tsangas, Laboratory of Chemical Engineering and Engineering Sustainability, Faculty of Pure and Applied Sciences, Open University of Cyprus, Latsia, Nicosia, Cyprus Baoshan Xie, Nantes Universite´, CNRS, Laboratoire de thermique et e´nergie de Nantes, LTeN, Nantes, France Antonis A. Zorpas, Laboratory of Chemical Engineering and Engineering Sustainability, Faculty of Pure and Applied Sciences, Open University of Cyprus, Latsia, Nicosia, Cyprus

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Part I

Solar thermal energy

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Chapter 1

Utilization of mono and hybrid nanofluids in solar thermal collectors Osama Ayadi1, 2, Otabeh AleOran1, 3, Mohammad Hamdan1, Tareq Salameh4, Afif Akel Hasan5, Adel Juaidi6, Ramez Abdallah6 and Mustafa Jaradat7 1

Mechanical Engineering Department, The University of Jordan, Amman, Jordan; 2Renewable Energy Technology Department, Applied Science Private University, Amman, Jordan; 3 Department of Energy Engineering, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Budapest, Hungary; 4Department of Sustainable and Renewable Energy Engineering, College of Engineering, University of Sharjah, Sharjah, United Arab Emirates; 5Department of Mechanical Engineering, Birzeit University, Birzeit, Palestine; 6 Mechanical & Mechatronics Engineering Department, Faculty of Engineering & Information Technology, An-Najah National University, Nablus, Palestine; 7Energy Engineering Department, German Jordanian University, Amman, Jordan

1. Introduction The vast sustainable and renewable worldwide transmission of energy is being aided by annual growth in worldwide energy consumption, as well as environmental difficulties and concerns. The sun is a limitless source of energy that may be utilized directly or indirectly, and the energy derived from it is referred to as solar energy [1e3]. Solar energy is the most plentiful renewable energy source currently accessible, and its evolution over the last decade has surpassed all other energy resources. There are varieties of available technologies that convert solar energy into useful forms for the end-users. The most widely used techniques are Solar thermal (ST) collectors, photovoltaic (PV) systems, and concentrated solar power (CSP) [4e10]. This chapter starts with a presentation of the status of solar energy markets. Then, a description of the numerous types of ST collectors and the enhancement of solar collector performance are introduced. Finally, this chapter reviews latest advancement in using nanofluids with a focus on hybrid nanofluids (HNF) to enhance performance of solar collectors. A particular attention is paid to the effect of nonfluids on the main types of solar collectors. Renewable Energy Production and Distribution. https://doi.org/10.1016/B978-0-323-91892-3.00008-X Copyright © 2022 Elsevier Inc. All rights reserved.

3

4 PART | I Solar thermal energy

1.1 Status of solar energy markets The global capacity of ST water collectors increased from 62 GWth (89 million m2) in 2000 to 479 GWth (684 million m2) in 2019 generating an annual ST energy production of 51 TWh in 2000 and 389 TWh in 2019 [11]. Globally, the installed PV generation capacity is the fastest-growing power generation system worldwide; a total of 116.9 GW of solar was added in 2019. By the end of 2020, the total installed solar PV power capacity increased to 707.5 GW. Furthermore, it is expected that it will achieve the following milestones in the next years: 1.0 TW and 1.2 TW will be installed in 2022 and 2023, respectively [12e14]. Among the previously mentioned technologies, CSP technology presents the least installed capacity, the large-scale deployment of CSP began in the USA in 1980. The industry has experienced modest growth over the past decade. The total installed capacity in 2020 is around 6.5 GW. The majority of recent and new CSP plants incorporate thermal storage of around 6e10 h duration [15,16]. Fig. 1.1 presents the global ST, PV, and CSP installed capacity during the period 2010e20. The phenomenal growth of solar energy in recent years is related to several factors; technological advancements leading to cost reductions, government policies encouraging the development of renewable energy, increasing of fossil fuel prices, and the environmental impacts of fossil fuels, notably greenhouse gas emissions [17]. 1200

Installed capacity [GW]

1000 800 600 400 200 0 2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Year ST [GWth]

PV [GW]

CSP [GW]

FIGURE 1.1 Total installed capacity of ST, PV, and CSP solar energy technologies worldwide. Data based on [11e16].

Utilization of mono and hybrid nanofluids Chapter | 1

5

1.2 Solar thermal collectors (ST) ST collectors are used to convert the electromagnetic waves of solar radiation into thermal energy. This thermal energy could be utilized for space heating, production of domestic hot water, industrial process heating, solar cooling, power generation, and many other applications. ST collectors can be classified according to several criteria, some of which are given below: l

l l

The heat transfer fluid (HTF). While the most used HTF is water, some collectors utilize air, thermal oil, and molten salt. The type of installation, that is, fixed versus tracking, Optical properties, that is, concentrating versus nonconcentrating, etc.

Fig. 1.2 presents the most used collectors classifying them according to their optical properties and type of installation. In addition to that, an arrow presenting the operating temperature range of these collectors is presented on the right-side Fig. 1.2, starting from the lowest temperature at the top to the highest at the bottom. The wide variation of ST technologies allows the designers to adopt the most appropriate technology that satisfies the end-user requirements with the highest efficiency and lowest cost.

1.3 Enhancement of solar thermal collectors Since its invention by the Swiss scientist Horace-Benedict de Saussure in 1767, ST collectors are undergoing continuous modification to increase their

FIGURE 1.2 Solar system classification based on their optical properties and type of installation.

6 PART | I Solar thermal energy

efficiency and to be manufactured at lower costs. Both passive methods and nanofluids were studied to improve the heat transfer of solar collectors. Although collectors have different designs, geometries, and optical features, common basic functional elements such as the absorber and the HTF exist in all types of collectors. In this section, the latest developments on the basic functional elements of ST collectors are presented. Several studies on the selective coating of the absorber have been done. This coating aims to increase the absorber absorptivity in the solar spectrum while reducing its emissivity in the infrared region. Metals (copper or aluminum sheets) are covered with specialized paints that absorb solar light more efficiently than typical black paints in traditional absorbers [18]. For over 3 decades, black chromium has been used in solar water heater applications [19]. Ma et al. studied the performance and durability of a mediumtemperature selective coating creating by cosputtering titanium and aluminum targets. It was found that the instantaneous efficiency based on gross area hG can reach 0.46 at the temperature of 150
C [20]. In order to cover solar collectors with NiCrAlO/Al2O3, Ning et al. have used DC magnetron sputtering and water boiling. The results showed a high solar absorptance of 0.964 and a low thermal emittance of 0.066 [21]. Lizama-Tzec et al. have fabricated a solar collector with electrodeposition of black nickel (E BN0 selective coating on the absorber. And compared their results with thermal collectors coated with those of CuO and Nitrogen-doped Titanium Dioxide (PVD Ti) The obtained results showed that at a maximum operating temperature of (TieTa) ¼ 70
C, the EBN collector is found to have an instantaneous thermal efficiency that is 14% and 31% higher than the PVDTi and CuO collectors, respectively [22]. Herrera-Zamora has also electrodeposited black cobalt for ST collectors, and the findings showed that selective black cobalt coatings are stable for operation at temperatures up to 700
C. When tested at 100
C, the absorber showed a solar absorptance of 95% and thermal emittance of 7% [22]. Yalin and Chen have prepared solar absorbers with CuO nanostructure selective coating by chemical oxidation for different time intervals, when tested at 100
C, the absorber showed a solar absorptance of 90% and thermal emittance of 11% [23]. Using carbon nanotubes and cupric oxide nanoparticles, Abdelkader et al. improved the solar selectivity of black paint, the absorber showed a solar absorptance of 96.4% and thermal emittance of 12.4% [24]. Utilizing nanofluid is a modern enhancement method that has an important role in improving the thermal transmission and absorption energy of any base fluid types (water, oil, etc.) that appeared in the last few years. The nanofluid is formed by mixing the particles that have nanosize into the base fluid to produce a new alternative thermal fluid. This is aimed to improve thermal conductivity and heat transfer of the fluid, which is achieved by reducing the thickness of the thermal boundary layer, this leads to an increase in the efficiency of the entire system.

Utilization of mono and hybrid nanofluids Chapter | 1

7

HNF and conventional nanofluids (CNF) are two types of nanofluids. In the base fluid of HNF, there are many types of nanoparticles, but in the base fluid of CNF, there is only one type of nanoparticle. CNF does not always have all of the favorable applicative characteristics. Although certain single-particle nanofluids have high thermal conductivity, they have high viscosity. For example, the rheological properties of GnP nanofluids approach Newtonian and non-Newtonian behaviors where viscosity decreases linearly with the rise of temperature. The thermal conductivity results show that the dispersed nanoparticles can always enhance the thermal conductivity of the base fluid, and the highest enhancement was obtained to be 27.64% in the concentration of 0.1 wt.% of GnPs with a specific surface area of 750 m2/g [25]. The application characteristics of nanofluids can be improved by combining nanoparticles with the ability to trade off different strengths. The research interest in the utilization of nanofluids for ST applications has increased significantly during the last few years. Bibliometric analysis has lately been acknowledged as a useful technique for tracking the advancement of a scientific topic. Bibliometric analysis was recently recognized as a powerful tool that allows studying the progress of a certain scientific topic [26e29]. Bibliometric research was conducted using the Scopus database between the years 2000 and 2020 to assess scientific publications in this field. This will aid in demonstrating the advancement of HNF technology and forecasting future trends. Fig. 1.3 shows the yearly number of publications in the fields of solar and nanofluid, as well as solar and “hybrid nanofluid” since 2007.

Number of publica ons

400 350 300 250 200 150 100 50 0 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Year Solar + Nanofluid

Solar + "Hybrid Nanofluid"

FIGURE 1.3 Annual number of publications in the (solar and nanofluid) (solar and “hybrid nanofluid”) area from 2007 to 2020.

8 PART | I Solar thermal energy

In 2015, the first results mentioning the terms (solar and “hybrid nanofluid”) appeared and after that considerable growth was observed. Furthermore, there is a pattern of faster expansion, indicating that the area is in its ascendant period in scientific study and the future potential will be greater.

2. Performance of flat plate solar collector (FPSC) using hybrid nanofluids One of the most prominent applications of solar energy is the FPSC for domestic and industrial usages. It takes solar energy and turns it to heat, which is then transmitted via a suitable working fluid such as water, oil, or ethylene glycol [30,31]. FPSCs have several drawbacks, including low thermal efficiency and a poor heat transfer coefficient due to convection heat transfer between the working fluid and the absorber [32]. Using nanofluids instead of conventional fluids is one of the most current developments in improving the performance of FPSCs. They offer improved thermophysical characteristics, allowing for more efficient heat transfer and energy absorption [33,34]. The thermophysical characteristics of the nanofluid, such as thermal conductivity, viscosity, density, and specific heat, are directly influenced by dispersing nanoparticles. Enhancing nanofluids’ thermal conductivity is important for improving their convective heat transfer properties. Many parameters, including nanoparticle type, base fluid type, nanoparticle shape, nanoparticle size, nanoparticle concentration, and temperature, influence the thermal conductivity of nanofluids. Nanofluids were utilized in a wide range of technical applications, including solar collectors, heat exchangers, home freezers, cosmetics, and the manufacture of antibiotics and medicines [35]. An extensive review of the performance of FPSC using nanoparticles is presented by Zayed et al. [36] and Hamdan and Sarsour [37]. Most recent work on the performance of FPSC using HNFs is presented below. Farajzadeh et al. [38] have investigated an FPSC with three distinct nanofluids computationally and experimentally. As nanofluids, they utilized TiO2/water (15 nm and 0.1 vol%), Al2O3/water (20 nm and 0.1 vol%), and a hybrid of TiO2eAl2O3/water. According to their research, the energy efficiency of the collectors using the hybrid TiO2eAl2O3 nanofluid was 26% higher than those using pure water (PW) as a base fluid. The corresponding values observed when TiO2/water and Al2O3/water nanofluids were studied individually were also 21% and 16% higher when the flow rate was 2 kg/min as shown in Fig. 1.4 below. They also developed a numerical model based on computational fluid dynamics (CFD), which they tested by comparing the output findings to the experimental results [38]. Verma et al. investigated the thermal behavior of CuO and MgO hybridized with multiwall carbon nanotubes (MWCNTs) in water at various mass flow rates (0.5e2 kg/min) and nanoparticle concentrations (0.2e0.25 wt%) for

Utilization of mono and hybrid nanofluids Chapter | 1

9

FIGURE 1.4 The thermal efficiency of flat plate solar collector with water, Al2O3, TiO2 and mixture nanofluid as working fluid 0.1%wt at 1.5 L/m volume flow rate [38].

FPSC performance improvements. When compared to water, the thermal efficiency improvements of FPSC for MgO/MWCNTs and CuO/MWCNTs HNFs were 20.5% and 18%, respectively, the concentration and mass flow rate of the nanofluid were 0.75 wt% and 1.5 kg/min, respectively [39]. Nasrin and Alim have investigated an FPSC using five nanofluids: alumina/ water, copper/water (double copper and alumina)/water, copper oxide/water, and silver/water. When all types of nanofluids were tested at a weight fraction of 5%, they observed that using (double Copper and Aluminum)/water nanofluids gave the best FPSC performance when compared to the others [40]. Covalent Functionalized-MWCNTs (CF-MWCNTs) and Covalent Functionalized-Graphene Nanoplatelets (CF-GNPs) with hexagonal boron nitride (h-BN) were suspended in distilled water to create the HNFs as working fluids within the Flat Plate Solar Collector (FPSC) [41]. Tween-80 was employed as a surfactant and several concentrations of hybrid nanoparticles were examined. Different measuring instruments were used to assess the stability and physical characteristics of the thermos. FTIR, XRD, UVevis spectroscopy, HRTEM, FESEM, and EDX were used to investigate the structural and morphological characteristics. The thermal efficiency of the FPSC was evaluated at three different volumetric flow rates (2, 3, and 4 L/min), and the collector’s efficiency was calculated using ASHRAE standard 93-2010. As a consequence, using HNF as the absorption medium and a 4 L/min flow rate, the most thermally efficient solar collector improved up to 85% as indicated in Fig. 1.5. Increasing the concentration of nanoparticles increased the energy achieved and produced higher fluid output temperature. Varying weight concentrations of 0.05%e0.15% were generated as circulation liquids HTFs within absorbers using nanodiamond-cobalt oxide (NDeCo3O4) HNFs at various volume flow rates of 0.56e1.35 L/min [42]. The use of an NDeCo3O4 HNF improved the thermo-physical characteristics

10 PART | I Solar thermal energy

FIGURE 1.5 Effect of the different flow rate of the hybrid nanofluid on the FPSC efficiency [42].

and heat transmission, resulting in improved absorber energy performance as compared to water. At 0.15 wt% and 60
C, the largest improvements in conductivity and fluid viscosity were about 15.71% and 45.83%, respectively. The Nusselt number (Nu) increased by about 21.23% when 0.15 wt %and the highest friction factor penalties of 1.13 times against water were used. The absorbers efficiency was 59% for 0.15 wt percent, whereas the water efficiency was 48%. Thermal efficiency of single and HNFs (Al2O3eH2O, Al2O3/FeeH2O) was investigated at varying concentrations of 0.05 vol% and 0.1 vol % by Okonkwo et al. [43]. The enhancement of Al2O3eH2O was larger than that of Al2O3/FeeH2O, with 2.16% and 1.79%t, respectively, utilizing concentrations of 0.1% for both nanomaterials compared to H2O, respectively. Such behavior was attributed to the fact that the HNF has a high dynamic viscosity due to the large nanoparticles used and therefore did not provide a superior thermal alternative to water. However, because less heat was lost due to heat transfer from the sun to the absorber, it enhanced exergy efficiency by 6.9% compared to 5.7% with Al2O3eH2O. In a solar collector, Li et al. investigated the optical stability and thermal performance of SiC-MWCNT/ethylene glycol nanofluid circulation. Using a 1 wt% SiC-MWCNT nanofluid, the highest thermal efficiency was 97.3%. It was 48.6% higher than the result obtained for pure ethylene glycol [44]. To make water-based nanofluids, Akram et al. used covalently functionalized carbon nanoplatelets and noncovalently functionalized metal oxide nanoparticles (surfactant-treated). Nanofluid stability is determined using UVevisible (UVevis) spectroscopy, and the findings demonstrate that nanofluid is stable for 60 days for carbon and 30 days for metal oxides [45]. Experimental and theoretical confirmation is provided for the thermophysical properties. The thermal conductivities of f-GNPs, SiO2, and ZnO nanofluids have been enhanced by 25.68%, 11.49%, and 15.42%, respectively. LueLi and Bruggeman’s thermal conductivity models are quite close to the experimental data. In the same way, nanofluids’ viscosity, density, and specific heat capacity

Utilization of mono and hybrid nanofluids Chapter | 1

11

are all evaluated and compared to theoretical models. In contrast to distilled water, f-GNPs, ZnO, and SiO2 increase density, specific heat, and viscosity by 0.12%, 0.22%, and 0.12%; 1.54%, 0.96%, and 0.73%; 12%t, 9.41%, and 24.05%, respectively. A flat-plate collector is assessed using carbon and metal oxides-based nanofluids in accordance with ASHRAE standard 93-2003, at various heat flux (597, 775, and 988 W/m2), flow rate (0.8, 1.2, and 1.6 kg/ min), inlet liquid temperature (30e50
C), and concentration (0.025e0.2%). The thermal efficiency is evaluated for distilled water in comparison with functionalized carbon and metal oxide-based nanofluids with weight concentrations of 0.025e0.20. A comparison of 0.1 wt% water-based nanofluids can be sequenced f-GNPs > ZnO > SiO2 because of a percentage improvement in thermal efficiency of the flat-plate solar collector obtained at a mass flow rate of 1.6 kg/min with values of 17.45%, 13.05%, and 12.36%, respectively, in comparison with water. Table 1.1 summarizes the main findings of the reviewed research which investigated the utilization of HNF in flat plate collectors. Accordingly, the base fluid type, nanoparticles type, and concentration of the nanofluid is mentioned side by side, the major findings of the efficiency.

3. Performance of evacuated tube solar collectors (ETSC) using nonfluids There are three main basic working fluids of evacuated tube solar collectors (ETSC). These working fluids are water, air, and a mixture of water and propylene glycol. Adding single nanoparticles (mono) or a combination of nanoparticles (hybrid) to the basic fluid will enhance the thermophysical properties of nanofluids. Many researchers used mono or HNFs as working fluids for ETSC. Researches were performed based on the features of nanoparticles such as type of material, volume fraction concentration of nanoparticles, and the shape of nanoparticles. Moreover, operating conditions such as mass flow rate, level of irradiance, and temperature are also important for the thermal and exergy efficiencies of ETSC. The review literature below is based on type of the nanofluids; metal nanofluids, metal oxides nanofluids, carbon nanofluids, and HNFs.

3.1 Metal nanofluids The metal nanoparticles were used with basic fluid as nanofluids such as mono Cu/water [46] and Ag/water [47]. The spherical Cu nanoparticle in water based on 0.01%, 0.02%, and 0.03% volume fraction were tested in ETSC. Three values of volume flow rates were used in the test starting from 0.6 L/min to 0.8 L/min. The results show that the output temperature increased by 50% and the gained heat increased from 417 to 667 W (60%). The removal factor reached 0.97. The 0.8 L/min and 0.03% was the best condition for maximum

Nanofluid Base fluid

Nanoparticles

Concentration

Efficiency

Major points

Reference

Water

Tio2, Al2O3/Hybrid

0.1%v

26

The energy efficiency of the collector using hybrid TiO2e Al2O3 nanofluid was 26% higher than the corresponding ones using pure water as a base fluid.

[38]

Water

MgO/MWCNTs

0.2%w

20.5

Thermal efficiency improvements of FPSC for MgO/ MWCNTs and CuO/MWCNTs hybrid nanofluids were 20.5% and 18% with respect to water when the concentration mass flow rate of the nanofluid were 0.75 wt% and 1.5 kg/min, respectively

[39]

CuO/MWCNTs

18

Water

Al2O3þCu, Al þ Cu, Ag,

5%

5

The best performance of the FPSC was obtained by using (double copper and Aluminum)/water nanofluid compared to the others, considering all types of the studied nanofluids were tested at a weight fraction of 5%

[40]

Water

NDeCo3O4

0.15%

9

The collector thermal efficiency is found to 59% for the case of 0.15% mass concentration of hybrid nanofluid, where the thermal efficiency of water is 48%.

[42]

Water

Al2O3eH2O, Al2O3/FeeH2O

0.1%

The enhancement of Al2O3eH2O was higher than of Al2O3/FeeH2O such as 2.16% and 1.79%,

[43]

12 PART | I Solar thermal energy

TABLE 1.1 Main findings of reviewed research on the utilization of HNF in FPSCs.

SiC-MWCNT

1%

Water

Covalently functionalized carbon nanoplatelets Noncovalent functionalized metal oxides nanoparticles

0.1%

Water

CF-MWCNTs CF-GNPs

48

85

The maximum thermal efficiency was 97.3% using 1 wt% SiC-MWCNT nanofluid. It was 48.6% greater than that of pure ethylene glycol data

[44]

Percentage improvement of thermal efficiency of the flat-plate solar collector obtained at a mass flow rate of 1.6 kg/min with values of 17.45% > 13.05% > 12.36%, for f-GNPs > ZnO > SiO2 respectively in comparison with water

[45]

As a result, the most thermal efficient solar collector improved up to 85% with hybrid nanofluid as the absorption medium at 4 L/min flow rate.

[41]

Utilization of mono and hybrid nanofluids Chapter | 1

Ethylene glycol

13

14 PART | I Solar thermal energy

absorbed and removal energy. The copper nanoparticle shows high potential in the CO2 reduction compared with other nanoparticles in the literature. The spherical gelatin-stabilized silver nanoparticles (Ag NPs) with 15 nm were used to prepare the working fluid Ag/water and tested the efficiency of the evacuated U-tube solar collector (EUSC) as shown in Fig. 1.6. The experiments for 0.035% based on weight percentage with four different values of mass flow rate (0.02, 0.033, 0.051 and 0.063 kg/s) were carried out at outdoor conditions. The results show that the 0.051 kg/s was the optimum mass flow rate where the efficiency reached 72.2%, which is 21.3% higher than that in PW as shown in Fig. 1.7.

3.2 Metal oxide nanofluids Several metal oxide nanoparticles were used with basic fluid as nanofluids such as mono CuO, ZnO, MgO, TiO2 SiO2, CeO2, ZrO2, Cu2O, Al2O3, WO3, and Fe2O3. A mass concentration of 1.2% for CuO nanoparticles was used by Lu et al. [48] in thermosiphon ETSC. The results showed that the optimal thermal performance of the thermosiphon increased as the temperature increased. Both enhancement in heat transfer coefficient and optimal filling ratio to the evaporator were 30% and 60% at 1.2 wt.%, the enhancement heat transfer ratio were 1.3, 1.23, and 1.13, 1.09 at operating temperatures 50 and 160
C, respectively. The novel integration between the simplified compound parabolic concentrator (CPC) and open thermosiphon was used to provide hot and moderate air temperatures [49]. The ETSC with CuO/water nanofluids consists of only two collecting panels was used as solar collectors as shown in Fig. 1.8. The air outlet temperature for this integration reaches up to 170
C at an air volume rate of 7.6 m3/h during the winter season. The integration shows better collecting performance when compared to the integration of a common concentric tube. Again, the thermosiphon system circulations with internal coil and ETSC with CuO/distilled water nanofluid were used by Ghaderian et al. [50]. Both volume fraction and mass flow rate of water inside the coil were

FIGURE 1.6 SEM image of gelatin-stabilized Ag NPs [47].

Utilization of mono and hybrid nanofluids Chapter | 1

15

FIGURE 1.7 The effect of different mass flow rate on the efficiency for Pure water and Ag/water nanofluid [47].

FIGURE 1.8 schematic of experimental apparatus used in [49].

16 PART | I Solar thermal energy

varied from 0.03% to 0.06% and 20e60 L/h, respectively. The results show that the CuO nanofluid enhanced the absorption medium by 14% compared with PW at a 0.03% volume fraction. The 1 wt% of CuO/water nanofluid in the heat pipe shows an increase in the thermal conductivity by 31.2% and a decrease in the thermal resistance by 66.1% [51]. In comparison with Al2O3/ DI, the CuO/DI water nanofluid shows a high thermal conductivity enhancement ratio, and the heat transfer coefficient for base fluid increased by 15% [52]. They found that increasing the concentration of nanoparticles and the tilting angle reduces the thermal resistance ratio of the heat pipe [53]. The two concentrations volume fraction (0.25% and 0.5%) of CuO and Al2O3/acetone nanofluids was used in the gravity-assisted heat pipe (GAHP) installed in ETSC [54]. The optimal performance was determined at the first stage by studying the effect of five filling ratios (40%, 50%, 60%, 70%, and 80%) and three tilt angles (30 degrees, 45 degrees, and 60 degrees). Their results show that the nanofluids enhanced the thermal performance efficiency from 20% to 545% and 15%e to 38%, respectively, at the optimal performance of the system with 70 filling ratio and 45 degrees tilt. A three-dimensional numerical simulation for the ETSC with U- shaped using CuO, Al2O3, and TiO2/water nanofluids under steady-state conditions was done by Ref. [55]. The singlephase and discrete ordinary models were used for the flow field and radiation process. The water temperature range was from 0 to 150
C and the thermos-physical properties were a function of the temperature range. The CuO nanofluid shows higher thermal efficiency by 13.8%, 1.5%, and 1.3% when compared to PW, TiO2/water, and Al2O3/water nanofluids, respectively. Also, the results show the importance of the heat capacity of working fluid in the thermal performance of ETSC. The effect of the size of nanoparticles and the concentration of Al2O3 nanofluid on the efficiency of U-shaped ETSC were studied by Kim et al. [56]. The results were compared with ETSC using water. The thermal conductivity of the nanofluids was increased with the concentration and decreased with the size of the nanoparticle, respectively. The results show that the highest efficiency occurred under the operating conditions 20 nm, 1.0 vol%, 0.047 kg/s, and when the ambient and inlet fluid temperatures are the same. The efficiency of ETSC for 20 nm and 1.0 vol% was higher than the 0.5vol% and 1.5 vol% and 50 and 100 nm by 9.7% and 5.6% and 3.05% and 5.32%, respectively. Four different volume concentrations and three different nanoparticle shapes of Al2O3/PW were investigated numerically for evacuated U-tube solar collector (EUSC) [57]. The volume concentrations were 1.0, 2.0, 3.0, and 4.0 vol % and the shapes were blade, brick, and platelet as shown in Fig. 1.9. Three mass flow rates were studied (0.01, 0.015 and 0.025 kg/s). The results show that the collector efficiency was higher than the EUSC used PW by 19.1%, and the highest efficiency obtained at 67.1% for 4.0 vol%. Both experimental and numerical works were performed for ETSC with Al2O3/Water in Baghdad, Iraq [58]. The experimental work used 16 evacuated tubes having a 38.6 aspect

Utilization of mono and hybrid nanofluids Chapter | 1

17

FIGURE 1.9 Boundary conditions and solar energy analysis for evacuated U-tube [57].

ratio and a 12 L thermally insulated tank. The results show that the collector efficiency increased by 28.4%, 6.8%, and 0.6% when the concentrations were 1.0 vol %, 0.6 vol%, and 0.3 vol%, respectively. The efficiency also increased by 7.08% and 16.9% when flat plate and curved plate reflectors used, respectively. The TiO2/distilled water nanofluid was used as a working fluid under optimum conditions in ETSC to study the thermal efficiency and entropy [59]. The optimum thermal conductivity of TiO2/distilled water nanofluid was determined by using response surface methodology at 0.5 vol %, 1:1 surfactant-to-nanoparticle ratio, and 10.0 min sonication time. The thermal conductivity increases by 7.28% when prepared under the optimum condition. The results show that the thermal efficiency increases with an increase in the mass flow rate from 0.017 to 0.033 kg/s, the efficiency of TiO2/distilled water increases by 16.5% compared with water at optimum condition of 0.033 kg/s mass flow rate. The entropy generation decreases, and the thermal efficiency increases under optimum conditions of nanofluid by 1.23% and 16.5%, respectively, at 0.033 kg/s mass flow rate of nanofluid when compared to distilled water. The heat transfer enhances by high thermal conductivity and mass flow rate. The ZnO/Etylene Glycol-PW (ZnO/EG-PW) nanofluid was used inside the EUSC [60]. Fifty percentage EG and 50% PW were used as base fluid. Four different volume fractions were tested (1.0%, 2.0%, 3.0%, and 4.0%). The thermal conductivity of ZnO/EG-PW nanofluid increases by increasing the volume concentration of nanoparticles. The maximum collector efficiency occurred when the ambient temperature and the inlet temperature of working were the same for all experiments. This maximum efficiency was 62.87% at 0.045 kg/s and 3.0 vol%. The value of maximum efficiency was 26.42%, 5.2%, and 6.88% higher than EG-PW as a working fluid, 0.03 kg/s, and 0.02 kg/s mass flow rates of base fluid, respectively. The evacuated heat pipe solar collector (HPSC) using MgO/water nanofluid was tested under different concentrations [61]. The topography of

18 PART | I Solar thermal energy

FIGURE 1.10 Topography of nanostructure and optical properties of MgO (A) SEM image; (B) FTIR spectra; (C) X-ray diffraction pattern; (D) Absorption spectrum [61].

nanostructure and optical properties were characterized by scanning electron microscopy (SEM), Fourier transform-infrared (FT-IR), X-ray diffraction (XRD), and UVevisible analysis as shown in Fig. 1.10. The results show that collector efficiency increases when the coolant flow rate increases, the efficiency of using MgO/water nanofluid was higher than the PW working fluid, and the increase in the concentration enhances the HPSC performance. The CeO2/water with 25 nm size and three different volume concentrations (0.015%, 0.025%, and 0.035%) was used inside ETSC [62]. Zero potential machine was used to check the stability of nanoparticles. Three different mass flux rates were tested. The results showed that the absorption energy and the temperature difference between the out and inlet flow increases by using the nanofluid. The maximum removal factor, the thermo-optical characteristic, and the thermal loss coefficient for ETSC were obtained at 0.035 vol% and 0.017 kg/s.m2. The thermo-optical characteristic of ETSC reaches up to 34%. The ETSC using WO3/Water nanofluid was studied for the 90 nm spherical shape of nanoparticles in Budapest, Hungary [63]. Three different volume concentrations (0.014%, 0.028%, and 0.042%) and mass flux rates (0.013 kg/ s.m2, 0.015 kg/s.m2 and 0.017 kg/s.m2) were tested as shown in Fig. 1.11. The stability of nanofluid was examined. The results show that adding WO3 nanoparticles to the base fluid increases the temperature difference of the fluid to 21%. More nanoparticles added more enhancements to the efficiency of ETSC. The thermal-optical efficiency was 72.8, and the heat removal factor

Utilization of mono and hybrid nanofluids Chapter | 1

19

FIGURE 1.11 The schematic of experimental setup (1) evacuated tube (2) Heat exchanger (3) pump (4) Flow meter (5) Thermometer (6) Tank [63].

was growth proportionally between 1.05 and 1.16 at the same mass flux rate compared with ETSC used water. The copper oxide/water (Cu2O/W) nanofluid and a parabolic concentrator was used to enhance the thermal characteristics of ETSC [64]. Three different volumetric flow rates (10, 30 and 50 L/h) and different volume concentrations were tested as shown in Fig. 1.12. The Artificial Neural Networks (ANNs) were used to check the accuracy of the experimental results. The Multilayer Perceptron model was a more accurate prediction of the collector performance than Radial Basis Function model. They concluded that the thermal performance of ETSC increases by an increase in both volume concentration and mass flow rate.

3.3 Carbon nanofluids The graphene nanoparticles were used in ETSC for [65,66]. The effect of GNP/distilled water nanofluid was studied experimentally [65]. Four different mass percentages (0.025, 0.5, 0.075, and 0.1 wt%) were used. The thermosphysical properties of nanofluid and stability were investigated. Three volumetric flow rates (0.5, 0.1, and 1.5 L/min) were tested, and the efficiency of ETSC was calculated based on ASHRAE standard 1993e2003. The results showed that the enhancement of the efficiency of ETSC reached up to 90.7% at a volumetric flow rate of 1.5 L/min, the results showed also the thermal energy gain increases by increasing the mass percentage of nanoparticles, while the higher outlet temperature of the fluid reached when the graphene nanosheets are used. The graphene-methanol nanofluid was in ETSC [66]. Different operating conditions such as tilt angle of the collector, filling ratio, mass fraction of GNPs, and mass flow rate inside the loop of the collector were

20 PART | I Solar thermal energy

FIGURE 1.12

The Schematic of the ETSC construction and nanoscopic phenomena with ANNs [64].

Utilization of mono and hybrid nanofluids Chapter | 1

21

experimentally investigated. The results showed that the highest daily thermal energy absorption of ETSC was obtained at 35 degrees tilt angle and 60% filling ratio. Moreover, the highest temperature difference between the outlet and inlet of the graphene-methanol nanofluid and low heat capacity was at 0.1 wt%; furthermore, the thermal efficiency of ETSC reached 95% at 0.1 wt% and 3 L/min. The thermal performance of 20 kW ETSC with Single Walled Carbon Nanotubeewater nanofluid was studied by Mahbubul et al. [67]. The assessment of the improvement of efficiency of ETSC with nanofluid was done by comparing with ETSC working with ordinary water. The results showed that the efficiency of ETSC with nanofluid (0.2 vol%) and water as working fluid were 56.7% and 66%, respectively. The MWCNT nanofluid was used in 50 enclosed-type evacuated U-tube solar collectors (EEUSC) [68]. The copper fin was inserted inside the U-tube to get constant heat flux as shown in Fig. 1.13. A novel method used by

FIGURE 1.13 Enclosed-type evacuated U-tube [68].

22 PART | I Solar thermal energy

filling the air gap with liquid has high thermal conductivity. The results showed that the efficiency of EEUSC affected by the air gap, and it increases when the MWCNT nanofluid is used by 4%. The annual reduction in CO2 and SO2 emissions was 1600 and 5.3 kg, respectively.

3.4 Hybrid or combination nanofluids U-shaped ETSC using Ag, ZnO, and MgO nanoparticles in 30%:70% (by volume) was designed and simulated numerically [69]. The mixture of ethylene glycol-PW (EG-PW) was used as a base fluid with high thermal conductivity of working fluid and different volume concentrations. The results show that the highest collector efficiency was 68.7% and obtained at 4.0 vol% Ag/EG-PW nanofluid. The highest efficiency was higher than EGePW by 26.7. Moreover, using 4.0 vol% for 30 installed solar collectors will reduce the coal, CO2, and SO2 emission by 855.5 kg, 2241.4 kg, and 7.2 kg per year, respectively. Table 1.2 summarizes the main findings of the reviewed research investigating the utilization of HNF in evacuated tube collectors.

4. Performance of concentrated solar collectors using hybrid nanofluids The need to produce higher energy and temperature using solar energy has led many researchers to consider CSP applications and to improve their performances such as (i.e., Parabolic trough collector (PTC), Linear Fresnel Reflector, Solar towers, Solar dish, as presented in Fig. 1.14. PTC’s ability to produce higher temperatures that coincide with superior efficiency and limited cost compared with other CSP applications play the main role in enhancing the number of studies in this field. Accordingly, recent studies that are concerned with the PTC in various ways (i.e., design geometry, optical efficiency, and heat transfer enhancement methods) are summarized in Refs. [70e72]. Many researchers have worked with different nanofluids to improve thermal performance and efficiency for PTCs [73e75]. The effect of mono nanofluid shows high interest in utilizing alumina oxide compared with others nanoparticles. Such interest is attributed to its cost and its ability to be synthesized in various base fluids [76,77]. In addition, some studies coupling two passive augmentation methods to gain a high thermal efficiency as in Jafar and Sivaraman research [78]. Their research examined the enhancement experimentally in Nu by using nail-twisted tape with nanofluid of Al2O3/Water under volume concentration at 0.3%. Their results were conducted experimentally under the, laminar flow rate range (710e2130), and constant heat flux conditions. The evaluated results showed that the enhancement in Nu number reaches 16% for the using nanofluid under concentrations 0.3 in comparison with base fluid in a plane tube; while it was

TABLE 1.2 Main findings of reviewed research on the utilization of mono nanofluids and hybrid nanofluid in ETSCs. Nanofluid

Max., increase%

Nanoparticles

Max concentration %

Efficiency

Heat transfer coefficient

Water

Cu

0.03 vol.

83

e

Water

Ag

0.035 wt.

72.2

e

CuO

1.5 wt.

e

30%

Base fluid

Major points

Reference

The 0.8 L/min and 0.03% was the best condition for maximum absorbed and removal energy for ETSC. The output temperature gained heat and efficiency increased by 50%, 60% and 51%, respectively.

[46]

The 0.051 kg/s was the optimum mass flow rate where the efficiency reached 72.2% which higher than that in pure water by 21.3% for EUSC.

[47]

The optimal thermal performance of the thermosiphon ETSC increased as the temperature increased. Both enhancement in heat transfer coefficient and optimal filling ratio to the evaporator were 30% and 60% at 1.2 wt.%.

[48]

Metal nanofluid

Water

Utilization of mono and hybrid nanofluids Chapter | 1

Metal oxide nanofluid

23 Continued

Nanofluid

Max., increase%

Base fluid

Nanoparticles

Max concentration %

Water

CuO

1.5 wt.%

6.6% for max. 12.6% for mean

Distilled water

CuO

0.06 vol.

51.4

Efficiency

Heat transfer coefficient e

e

Major points

Reference

The novel integration between the simplified compound parabolic concentrator (CPC) and open ETSC thermosiphon. The air outlet temperature for this integration reaches up to 170
C at an air volume rate of 7.6 m3/h during the winter season. The optimum value of the heat transfer coefficient was obtained at 1.2 wt.%.

[49]

The thermosiphon system circulations with internal coil and ETSC with CuO/ distilled water were used. The absorption medium enhanced by 14% compared with pure water at a 0.03%.

[50]

24 PART | I Solar thermal energy

TABLE 1.2 Main findings of reviewed research on the utilization of mono nanofluids and hybrid nanofluid in ETSCs.dcont’d

CuO

1.5 wt.

24.9%

29.4%

The increase in the thermal conductivity for heat pipe was 63.5% and the decrease in the thermal resistance was 66.1% at 1 wt.%.

[51]

DI water

CuO & Al2O3

1.5 wt.

e

15%

The CuO/DI has a higher thermal conductivity enhancement ratio.

[52]

DI water

CuO

1.5 wt.

30.5%

e

The thermal resistance ratio of the heat pipe reduces by increasing both the concentration of nanoparticles and the tilting angle.

[53]

Acetone

CuO and Al2O3

0.5 vol.

74

e

The optimal performance of the system was at 70 filling ratio and 45 degrees tilt. The efficiency for GAHP was for Al2O3/ acetone based at 0.5 vol. %.

[54]

Water

CuO Al2O3 and TiO2

4 vol.

13.8%

e

A three-dimensional numerical simulation for the ETSC with U-shaped under steady-state conditions. The CuO

[55]

25

Continued

Utilization of mono and hybrid nanofluids Chapter | 1

Water

Nanofluid

Base fluid

Nanoparticles

Max., increase% Max concentration %

Efficiency

Heat transfer coefficient

Major points

Reference

nanofluid shows higher thermal efficiency by 13.8%, 1.5%, and 1.3% when compared to pure water, TiO2/water, and Al2O3/water nanofluids, respectively. The mass flow rate was fixed at 0.005 kg/s at irradiance equal to 500 W/m2 and ambient temperature 303 K. Water

Al2O3

1.5 vol.

72.4

e

The efficiency of ETSC for 20 nm and 1.0 vol. % was higher than the 0.5vol. % and 1.5 vol. % and 50 and 100 nm by 9.7% and 5.6% and 3.05% and 5.32%, respectively.

[56]

26 PART | I Solar thermal energy

TABLE 1.2 Main findings of reviewed research on the utilization of mono nanofluids and hybrid nanofluid in ETSCs.dcont’d

Al2O3

4 vol.

67.1

e

Water

Al2O3

1 vol.

28.4%

e

Distilled water

TiO2

0.5 vol.

16.5%

e

The collector efficiency of evacuated U-tube solar collector (EUSC) was higher than the EUSC used PW by 19.1% for 4.0 vol. %.

[57]

The collector efficiency increased by 28.4%, 6.8%, and 0.6% when the concentrations were 1.0 vol. %, 0.6 vol. %, and 0.3 vol. %, respectively. The efficiency also increased for the flat plate and curved plate reflectors by 7.08% and 16.9%, respectively.

[58]

The entropy generation decreases, and the thermal efficiency increases under optimum conditions of nanofluid by1.23% and 16.5%, respectively, at 0.033 kg/s mass flow rate of nanofluid when compared to distilled water

[59]

27

Continued

Utilization of mono and hybrid nanofluids Chapter | 1

Water

TABLE 1.2 Main findings of reviewed research on the utilization of mono nanofluids and hybrid nanofluid in ETSCs.dcont’d Max., increase%

Base fluid

Nanoparticles

Max concentration %

50% Etylene Glycol-50% pure water

ZnO

1.2,3 and 4 vol.

62.87

e

Water

MgO

0.032 vol.

77

e

Water

CeO2

0.035 vol.

34%

e

Efficiency

Heat transfer coefficient

Major points

Reference

The maximum collector efficiency occurred when the ambient temperature equal the inlet temperature of working fluid for all experiments. The value of maximum efficiency was 26.42%, 5.2%, and 6.88% higher than EG-PW as a working fluid, 0.03 kg/s, and 0.02 kg/s mass flow rates of base fluid, respectively, for EUSC.

[60]

The highest efficiency was obtained at 0.032 vol. % and 14 L/min.

[61]

The absorption energy and the temperature difference between the out and inlet flow increases by using the nanofluid. The maximum removal factor, the thermo-optical characteristic, and the

[62]

28 PART | I Solar thermal energy

Nanofluid

thermal loss coefficient for ETSC were obtained at 0.035 vol. % and 0.017 kg/s.m2. The thermo-optical characteristic of ETSC reaches up to 34%. WO3

0.042 vol.

72.8

e

Water

Cu2O

0.08 vol.

60

e

GNP

1 wt.

90.7

e

Increases the temperature difference of the fluid to 21%. The heat removal factor increases proportionally between 1.05 and 1.16 at the same mass flux rate compared with ETSC which used water.

[63]

Three different flow rates were used. The experimental results were verified by artificial neural networks (ANNs).

[64]

The enhancement of the efficiency of ETSC was at a volumetric flow rate of 1.5 L/min, the thermal energy gain increases by increase the mass percentage of nanoparticles.

[65]

Carbon nanofluid Distilled water

Utilization of mono and hybrid nanofluids Chapter | 1

Water

29 Continued

Nanofluid

Base fluid

Nanoparticles

Methanol

GNP

Water

SWCNT

Max., increase% Max concentration %

0.2 vol.

Efficiency

Heat transfer coefficient

95

e

66

e

Major points

Reference

The highest daily thermal energy absorption of ETSC has obtained at 35 degrees tilt angle and 60% filling ratio. The highest temperature difference between the outlet and inlet of the graphenemethanol nanofluid and low heat capacity was at 0.1 wt.%. The thermal efficiency of ETSC was at 0.1 wt.% and 3 L/min.

[66]

The thermal efficiency was 56.7% and 66% for water and 0.2 vol. % nanofluid as working fluids.

[67]

30 PART | I Solar thermal energy

TABLE 1.2 Main findings of reviewed research on the utilization of mono nanofluids and hybrid nanofluid in ETSCs.dcont’d

MWCNT

e

8% compared with pure water

4 vol.

68.7

e

The efficiency of EEUSC affected by the air gap increased by 4%. The annual reduction in CO2 and SO2 emissions was 1600 and 5.3 kg, respectively

[68]

The Ag/EG-PW nanofluid has the highest collector efficiency at 4.0 vol. %. This efficiency is higher than the efficiency of EG ePW by 26.7. using 50 installed solar collectors and 4.0 vol. % will reduce the coal, CO2, and SO2 emission by 855.5, 2241.4, and 7.2 kg per year, respectively

[69]

Hybrid or combination of nanofluids 30% ethylene glycol- 70% pure water (30% EG- 0% 7 PW)

Ag, ZnO, and MgO

Utilization of mono and hybrid nanofluids Chapter | 1

0.24 vol.

31

32 PART | I Solar thermal energy

FIGURE 1.14 Concentrated solar collector’s schematics.

showed more improvements in Nu number reaches about 20% when used the same concentration but with nail-twisted tape tube. The important result they’ve come up with is that the nanofluids with nail twisted tape absorbers can significantly improve the heat transfer performance of the solar trough collector [78]. Recently, the positive effects of utilizing HNF led to an increasing attention in those types. Those new fluids are obtained by inserting two or more nanoparticles inside different base fluids [79]. The major positive impact effects of using HNFs can be summarized as follow; presenting better heat transfer properties, achieving positive hydrodynamic impact, side by side with the reasonable cost which can be reached by utilizing cheap and expensive nanoparticles [80,81]. Up to date, utilizing HNFs in a PTC has a limited number of studies due to the new promising thermal fluid, despite the advantages of using this technique, the major reported studies summarized as follows: Minea and ElMaghlany [82] reviewed intensively the previous studies from the literature along with presenting a two-dimension numerical model to show the effect of inserting different HNF types in the PTC receiver (CueAl2O3/water, Age MgO/water, GOeCo3O4/60 ethylene glycol:40 water). The results of the thermal efficiency, hydraulic performance, and heat transfer enhancement of the PTC were conducted under uniform heat flux from the bottom and the top side, and laminar flowrate condition. As shown in Fig. 1.15, the major results showed 14% enhancement in the heat transfer obtained by utilizing AgeMgO/ water at the concentration 2%.

Utilization of mono and hybrid nanofluids Chapter | 1

33

FIGURE 1.15 The effect of Reynolds number on the temperature gradient and collector efficiency of hybrid nanofluids: (A) Gradient of Re temperature variation for water and nanofluid of 2% AgeMgO water; (B) Gradient of Re temperature variation for 60 EG:40W and nanofluid of 0.15% GO/Co3O4/60 EG:40W; (C) Collector efficiency versus Re for water and 2% AgeMgO water; (D) Collector efficiency versus Re for 60 EG:40W and 0.15% GO/Co3O4/60 EG:40W [82].

Bellos and Tzivanidis [83] have compared the variation of the enhancement results between mono nanofluid of Al2O3 and TiO2 with Syltherm 800 under total volume concentration 3%, and their hybrid (Al2O3e TiO2/Syltherm 800) under the same concentration but with fraction (50:50). The numerical model was simulated using EES under constant heat flux value equal to 1000 W/m2 and different inlet temperatures (300e600 K). This simulation aimed to present the variations on the thermal efficiency, Nu, heat transfer coefficient, and exergy efficiency. They reported thermal efficiency enhancement of 0.7% using mono nanofluid compared with HNF which reaches 1.8%. While for the exergy efficiency, they reported a small variation in the enhancement reaches 0.383 for the HNF and 0.378 for the mono nanofluid. This strengthening in the efficiencies improvement results is due to enhancements in the Nu and heat

34 PART | I Solar thermal energy

transfer coefficient, which reaches 2.2 and 2.4 highest the respective of operation with pure oil, for the HNF, respectively. While it reaches as a resultant on utilizing mono nanofluid 1.23 in the Nu ratio and 1.35 in the heat transfer coefficient in comparison with pure oil. AleOran et al. [84] improved the analytical expression to evaluate the exergy and energy efficiencies obtained from utilizing different mono and JMFs using MATLAB Symbolic tools. The simulation of the LS2 PTC model has been conducted under constant heat flux boundary conditions equal to 1000 W/m2, and constant volume flow rate equal to 150 L/min while the inlet temperatures varying from 300K up to 600K. The thermal efficiency results of inserting different mono and hybrid nanoparticles (Al2O3, CeO2, CuO, Al2O3e CeO2, Al2O3e CuO) in Syltherm 800 showed that the high enhancement reaches 1.09% when using HNF of Al2O3e CeO2. In addition, the same HNF presented high enhancement exergy efficiency of 1.03% compared with the base fluid. In other investigation, AleOran and Lezsovits [85] examined the exergy and energy efficiencies by utilizing HNF of alumina and tungsten oxideTherminol VP1 on the thermal performance of the PTC. Their research has been conducted under variable radiation intensity of Budapest weather conditions as a case study and under constant radiation intensity. The major results showed that the highest enhancement was calculated at high concentrations level and high temperatures reached up to 0.39% at constant radiation, while it reached 0.25% at the radiation level of Budapest for both efficiencies. Ekiciler et al. [86] investigated the effect of inserting three different hybrid nanoparticles based Syltherm 800, namely (AgeZnO, AgeMgO, AgeTiO2) flowing in the receiver of the LS2 PTC model. A three-dimensional numerical model was solved using CFD for the turbulent flow exposed by nonuniform heat flux boundary conditions under different concentrations (1%e4%) and constant inlet temperature equal to 500K. They marked that the HNF of AgeMgO/Syltherm 800 is the best one. This result is attributed to the high thermal efficiency enhancement that reached 15%, at the high concentration, side by side with the reasonable friction factor impact. Combining the effect of HNF use in PTC with other hybrid renewable energy systems was evaluated by Tafavogh and Zahedi in their recent experimental research [87]. They have investigated the effect of utilizing HNF of MWCNT&MgO nanoparticles based Thermia B oil in a PTC as a part of their hybrid renewable system under different fraction weight, concentrations, and flow rate. Their results presented in Fig. 1.16 shows high thermal efficiency up to 61.8% under the weight fraction 50:50, weight concentration 0.5%, and flow rate equal 2 L/min. On the other hand, the HNFs have been combined and their effect is studied with other improvement methods slightly in previous studies to date, where it has been used in the recent research of Khan et al. [88]. In their research, they have analyzed and compared the thermal performance of the PTC under the influence of a mono nanofluid and a hybrid that flows in the

Utilization of mono and hybrid nanofluids Chapter | 1

35

FIGURE 1.16 The thermal efficiency of the PTC (A) MWCNT/MgO weight ratio impact at a total nanoparticle Conc. of 0.4% with an HybridNF’s flow rate of 2 L/min, (B) Nanoparticle Conc. impact at a constant MWCNT/MgO weight ratio of 50% and an HybridNF’s flow rate of 2 L/min, (C) Flow rate impact at a constant nanoparticle Conc. of 0.5% with an HybridNF’s flow rate of 2 L/ min and an MWCNT/MgO weight ratio of 50% [87].

converging-diverging absorber tube, and in the smooth absorber tube. Various cases of using MWCNT and TiO2 based therminol-VPI under total volume concentrations of 3% and wide temperature ranges (350e600 K) for mono and hybrid combinations are compared for two different tubes shapes namely (converging-diverging tube, a smooth absorber tube). The main results showed that the highest thermal efficiency was 68.95% due to the use of HNF that crosses through a converging-diverging absorber tube in comparison with the thermal efficiency of the use therminol-VPI that flow in a smooth absorber tube, which is equal 65.5% at high temperature. Recently, Al-Rashed et al. [89] examined the thermo-hydraulic performance of the PTC that simulated by utilizing HNF of MWCNT and Al2O3/oil with finned rod turbulator, in addition to the economic estimation of inserting two passive enhancement methods in this application. Their results showed that the obtained economic estimation can save up to 14% on material usage. Rostami et al. [90] studied the influence of HNF (SBA-15and Cu/oil) on the energy and exergy efficiencies of PTC, as well as the effect of the

TABLE 1.3 Main findings of the reviewed research which investigated the utilization of HNF in concentrating collectors. Max., increase%

Base fluid

Nanoparticles

Concentration

Efficiency

Heat transfer coefficient

Water, 60 ethylene Glycol:40 water

Ag þ MgO, Al2O3þCu GO þ Co3O4

2%v

60

e

Syltherm-800

Tio2,Al2O3/Hybrid

3%v

Mono 0.7% Hyb 1.8%

Syltherm-800

CeO2, Al2O3, CuO, CeO2þAl2O3, CuO þ Al2O3

4%v

Therminol-VPI

Al2O3þWO3

Syltherm-800

Ag þ ZnO, Ag þ MgO, Ag þ TiO2

Major points

Reference

Hybrid base water is better than hybrid base water and ethylene glycol. The maximum thermal efficiency was obtained using AgeMgO/ water

[82]

Mono 56% Hyb 204%

The results conducted under a constant flow rate 150 L/min and constant heat flux 1000 W/m2

[83]

1.09% CeO2þAl2O3

200.7% CeO2þAl2O3

The results conducted under a constant flow rate 150 L/min and constant heat flux 1000 W/m2

[84]

4%

0.39

169%

The simulation is presented for two cases: One under a constant radiation intensity and the other under the radiation intensity level of Budapest

[85]

4%v

15% Ag þ MgO

Mono 56% Hyb 204%

The results simulated using CFD tools under nonuniform heat flux boundary conditions and constant inlet temperature equal to 500K

[86]

36 PART | I Solar thermal energy

Nanofluid

MWCNT þ MgO

0.5% w

61.8

Therminol-VPI

Mono and HNF of MWCNT þ TiO2

3%v

5.27% HNF

197.09% HNF @ 400K

Transcal N oil

MWCNT þ Al2O3

e

e

e

Water

SBA-15and Cu

0.075

65

e

Water

Al2O3 þ CuO

0.55%wt

45.4 PTC 58.4 DAPTC

e

e

[87]

The maximum enhancement obtained for HNF flow in a converging-diverging tube under mass flowrate 0.6 kg/s and high inlet temperature of 600 K.

[88]

Found that by using HNF of MWCNT and Al2O3/oil with finned rod turbulator about 14% of used material may be saved.

[89]

The highest observed thermal efficiency up to 65% during the midday time for the highest concentrations founded by linking utilizing HNF with turbulator.

[90]

At a particle concentration of 0.55 wt%, the maximum efficiency observed with Al2O3 e CuO/water hybrid NF is 19% greater in DAPTC than in conventional PTC.

[91]

37

Experimental results evaluated under the weather condition at Bandar Abbas location obtained for the hybrid renewable energy system under oil flow rate in PTC equal 2 L/min

Utilization of mono and hybrid nanofluids Chapter | 1

Thermia B oil

38 PART | I Solar thermal energy

turbulators as a second passive enhancement method. The CFD investigation indicated that the heat transfer augmentation is smaller for low values of Reynolds number, that is, less than 3500. In addition, the average Nu of using two passive enhancement methods (turbulators and HNF) improves as contrasted to smooth absorber tube. The highest energy and exergy efficiencies were 65% and 5%, respectively, during the midday time for the highest concentrations and low Reynolds number less than 3500, which were 2% and 1% greater than the smooth absorber tube. Hybrid nanoparticles may embrace a more extensive solar spectrum, and photo-thermal achievement can be improved due to increased optical properties side by side with the thermal properties, particularly in direct absorption PTC (DAPTC) solar application. On this side, Khalil et al. [91] have compared experimentally the thermal performance results obtained by utilizing HNF of Al2O3 and CuO/water on conventional PTC and DAPTC. The PTC constructed at Kala Shah Kaku, Punjab, Pakistan was examined using the aforementioned HNFs under concentrations weight (0.11, 0.33, and 0.55wt%) and constant flow rate equal to 1 L/min. The key results showed an enhancement of 31% using HNF under a high concentration on the thermal efficiency of the conventional PTC compared to the Base fluid flow in the same PTC. On the other hand, the thermal efficiency observed by utilizing HNF in the DAPTC showed enhancement by 19% compared with the conventional PTC. Table 1.3 summarizes the main findings of the reviewed research which investigated the utilization of HNF in concentrating collectors.

5. Conclusions Nanofluids are fluids that contain nanoparticles of the same type (mono or conventional CNF) or two or more types (Hybrid NF) of 1e100 nm size dissolved in a base fluid. The greatest advantage of such particle fractions is that they have a favorable surface/volume ratio, which significantly improves thermal conductivity. The choice of particle material and size allows the thermal properties of the fluid to be influenced in certain areas. The thermal stability properties, agglomeration, and corrosion processes as well as increased pump energy due to increased viscosity properties are disadvantageous for use in ST power plants. Nevertheless, nanofluids offer a conceivable technological alternative. This book chapter presents a review of the utilization of HNFs in ST collectors. The performance of using HNFs was reviewed in three different ST collectors. Several researchers have studied the impact of NFs as HTFs in FPCs, ETCs, and concentrating collectors. Through an intensive review in the literature, we may conclude with the following points: l

Through bibliometric research that was conducted using the Scopus database between the years 2000 and 2020 to assess scientific publications in CNFs and HNFs, it was found that the first results mentioning the terms

Utilization of mono and hybrid nanofluids Chapter | 1

l

l

l

l

39

(solar and “hybrid nanofluid”) appeared in 2015. Since then, there has been considerable growth. Furthermore, there is a pattern of faster expansion, indicating that the area is in its ascendant period in scientific study and that future potential will be greater. Regarding the utilization of nanofluids in FPSCs, the literature review reported a significant improvement in the efficiency compared to conventional working fluids and higher efficiency for HNFs compared to single CNF. The improvement in the efficiency was mainly related to the concentration of the nanoparticles and in a positive proportional relationship. In addition, Al2O3 nanoparticles were the most prevalent type of nanoparticles between the conducted studies, and water is widely used as a base fluid. Regarding the ETSCs, the studies reported that adding mono or hybrid NPs to the base fluid will enhance the thermophysical properties and thus the efficiency. Several studies have been carried out on the three common ETSC types; water-in glass, U-tube, and heat pipe ETSCs. Several parameters were investigated, such as the size and the concentration of the NPs and the filling ratio of the heat pipe type, as well as experimentally and numerically applying different NPs. The results showed that the absorption energy and the temperature difference between the outlet and inlet flow increases by using the nanofluid. In addition, it was found that the heat transfer coefficient increases by increasing the filling ratio, up to a certain extent in the range of 60%, of the heat pipe. Regarding the concentrating collectors, there are few studies for applying hybrid NFs due to the new promising thermal fluids, and they were mainly for PTCs. The ability of PTCs to produce higher temperatures that coincide with superior efficiency and limited cost compared with other CSP applications play the main role in enhancing the number of studies in this field. Accordingly, those studies were concerned with the PTC in various ways (i.e., design geometry, optical efficiency, and heat transfer enhancement methods). The major positive impact effects of using HNs are presenting better heat transfer properties, achieving positive hydrodynamic impact, and the reasonable cost that can be reached by utilizing mixtures of cheap and expensive NPs. As mentioned previously, the research in this field is relatively new, and most of these studies were experimental research on a laboratory scale or numerical analysis. This leads to the question of the stability of these HNFs in the long term. The instability of NFs remains a major challenge that requires expanded studies and follow-up investigations of real applications on the ground so that this technology can reach widespread and competitive commercial levels. Furthermore, applying HNFs in low-cost FPSC is considered the main challenge regarding the economic influence of applying such fluids. This leads to the urgent need to study the economic feasibility of these systems, which are almost nonexistent in the literature.

40 PART | I Solar thermal energy

References [1] C. Smith, Revisiting solar power’s past, Technol. Rev. 98 (5) (1995) 38e47. [2] T. Salameh, M. Tawalbeh, A. Juaidi, R. Abdallah, S. Issa, A.H. Alami, A novel numerical simulation model for the PVT water system in the GCC region, in: 2020 Advances in Science and Engineering Technology International Conferences, ASET), 2020, pp. 1e5. [3] T. Salameh, M. Tawalbeh, A. Juaidi, R. Abdallah, A.-K. Hamid, A novel three-dimensional numerical model for PV/T water system in hot climate region, Renew. Energy 164 (2021) 1320e1333. [4] R. Abdallah, A. Juaidi, S. Abdel-Fattah, F. Manzano-Agugliaro, Estimating the optimum tilt angles for south-facing surfaces in Palestine, Energies 13 (3) (2020) 623. [5] R. Abdallah, E. Natsheh, A. Juaidi, S. Samara, F. Manzano-Agugliaro, A multi-level world comprehensive neural network model for maximum annual solar irradiation on a flat surface, Energies 13 (23) (2020) 6422. [6] S. Monna, A. Juaidi, R. Abdallah, M. Itma, A comparative assessment for the potential energy production from PV installation on residential buildings, Sustainability 12 (24) (2020) 10344. [7] T. Salameh, M. Alkasrawi, A. Juaidi, R. Abdallah, S. Monna, Hybrid renewable energy system for a remote area in UAE, in: 2021 12th International Renewable Engineering Conference (IREC), 2021, pp. 1e6. [8] O. Ayadi, S. Al-Dahidi, Comparison of Solar Thermal and Solar Electric Space Heating and Cooling Systems for Buildings in Different Climatic Regions, Sol. Energy, 2019. [9] O. Ayadi, R. Al-Assad, J. Al Asfar, Techno-economic assessment of a grid connected photovoltaic system for the University of Jordan, Sustain. Cities Soc. 39 (2018). [10] O. Ayadi, I. Alsalhen, Techno-economic assessment of concentrating solar power and wind hybridization in Jordan, J. Ecol. Eng. 19 (2) (2018) 16e23. [11] W. Weiss, M. Spo¨rk-Du¨r, Solar Heat Worldwide Global Market Development and Trends in 2019, 2020. [12] SolarPower Europe, Global Market Outlook for Solar Power/2020e2024, 2020. [13] International Renewable Energy Agency (IRENA), “World Energy Transitions Outlook: 1.5
C Pathway,”, 2021. Abu Dhabi. [14] International Energy Agency, Renewables 2020 Analysis and Forecast to 2025, 2020. [15] International Renewable Energy Agency (IRENA), “Renewable Capacity Statistics 2021,”, 2021. Abu Dhabi. [16] K. Lovegrove, et al., Comparison of Dispatchable Renewable Electricity Options, 2018. [17] G.R. Timilsina, L. Kurdgelashvili, P.A. Narbel, Solar energy: markets, economics and policies, Renew. Sustain. Energy Rev. 16 (1) (2012) 449e465. [18] S.A. Sakhaei, M.S. Valipour, Performance enhancement analysis of the flat plate collectors: a comprehensive review, Renew. Sustain. Energy Rev. 102 (2019) 186e204. [19] K. Xu, M. Du, L. Hao, J. Mi, Q. Yu, S. Li, A review of high-temperature selective absorbing coatings for solar thermal applications, J. Mater. 6 (1) (2020) 167e182. [20] G. Ma, Z. Yin, X. Liu, J. Qi, Y. Dai, Developments of CPC solar evacuated glass tube collector with a novel selective coating, Sol. Energy 220 (2021) 1120e1129. [21] Y. Ning, et al., NiCrAlO/Al2O3 solar selective coating prepared by direct current magnetron sputtering and water boiling, Sol. Energy Mater. Sol. Cells 219 (2021) 110807. [22] D.M. Herrera-Zamora, et al., Electrodeposited black cobalt selective coatings for application in solar thermal collectors: fabrication, characterization, and stability, Sol. Energy 207 (2020) 1132e1145.

Utilization of mono and hybrid nanofluids Chapter | 1 [23] [24]

[25] [26] [27]

[28] [29] [30] [31]

[32]

[33] [34]

[35] [36]

[37] [38]

[39]

[40]

[41]

41

Y. Lu, Z. Chen, Experimental study on thermal performance of solar absorber with CuO nano structure selective coating, Energy Proc. 158 (2019) 1303e1310. T.K. Abdelkader, Y. Zhang, E.S. Gaballah, S. Wang, Q. Wan, Q. Fan, Energy and exergy analysis of a flat-plate solar air heater coated with carbon nanotubes and cupric oxide nanoparticles embedded in black paint, J. Clean. Prod. 250 (2020) 119501. M. Mehrali, et al., Investigation of thermal conductivity and rheological properties of nanofluids containing graphene nanoplatelets, Nanoscale Res. Lett. 9 (1) (2014) 1e12. Z. Ding, W. Wu, M. Leung, Advanced/hybrid thermal energy storage technology: material, cycle, system and perspective, Renew. Sustain. Energy Rev. 145 (2021) 111088. T.M. David, P.M. Silva Rocha Rizol, M.A. Guerreiro Machado, G.P. Buccieri, Future research tendencies for solar energy management using a bibliometric analysis, 2000e2019, Heliyon 6 (7) (2020) e04452. L.F. Cabeza, A. de Gracia, G. Zsembinszki, E. Borri, Perspectives on thermal energy storage research, Energy 231 (2021) 120943. J.M. Merigo´, A.M. Gil-Lafuente, R.R. Yager, An overview of fuzzy research with bibliometric indicators, Appl. Soft Comput. 27 (2015) 420e433. W. Kong, B. Perers, J. Fan, S. Furbo, F. Bava, A new Laplace transformation method for dynamic testing of solar collectors, Renew. Energy 75 (2015) 448e458. M.J. Muhammad, I.A. Muhammad, N.A.C. Sidik, M.N.A.W.M. Yazid, R. Mamat, G. Najafi, The use of nanofluids for enhancing the thermal performance of stationary solar collectors: a review, Renew. Sustain. Energy Rev. 63 (2016) 226e236. W. Chen, C. Zou, X. Li, An investigation into the thermophysical and optical properties of SiC/ionic liquid nanofluid for direct absorption solar collector, Sol. Energy Mater. Sol. Cells 163 (2017) 157e163. M. Gupta, V. Singh, R. Kumar, Z. Said, A review on thermophysical properties of nanofluids and heat transfer applications, Renew. Sustain. Energy Rev. 74 (2017) 638e670. W.H. Azmi, K. V Sharma, R. Mamat, G. Najafi, M.S. Mohamad, The enhancement of effective thermal conductivity and effective dynamic viscosity of nanofluidsea review, Renew. Sustain. Energy Rev. 53 (2016) 1046e1058. E. Sadeghinezhad, et al., A comprehensive review on graphene nanofluids: recent research, development and applications, Energy Convers. Manag. 111 (2016) 466e487. M.E. Zayed, J. Zhao, Y. Du, A.E. Kabeel, S.M. Shalaby, Factors affecting the thermal performance of the flat plate solar collector using nanofluids: a review, Sol. Energy 182 (2019) 382e396. M. Hamdan, M. Sarsour, Effect of nanoparticles on the performance of solar flat plate collectors, J. Ecol. Eng. 19 (2) (2018). E. Farajzadeh, S. Movahed, R. Hosseini, Experimental and numerical investigations on the effect of Al2O3/TiO2H2O nanofluids on thermal efficiency of the flat plate solar collector, Renew. Energy 118 (2018) 122e130. S.K. Verma, A.K. Tiwari, S. Tiwari, D.S. Chauhan, Performance analysis of hybrid nanofluids in flat plate solar collector as an advanced working fluid, Sol. Energy 167 (2018) 231e241. R. Nasrin, M.A. Alim, Finite element simulation of forced convection in a flat plate solar collector: influence of nanofluid with double nanoparticles, J. Appl. Fluid Mech. 7 (3) (2014). O.A. Hussein, K. Habib, A.S. Muhsan, R. Saidur, O.A. Alawi, T.K. Ibrahim, Thermal performance enhancement of a flat plate solar collector using hybrid nanofluid, Sol. Energy 204 (2020) 208e222.

42 PART | I Solar thermal energy [42] L.S. Sundar, Y.T. Sintie, Z. Said, M.K. Singh, V. Punnaiah, A.C.M. Sousa, Energy, efficiency, economic impact, and heat transfer aspects of solar flat plate collector with Al2O3 nanofluids and wire coil with core rod inserts, Sustain. Energy Technol. Assess. 40 (2020) 100772. [43] E.C. Okonkwo, I. Wole-Osho, D. Kavaz, M. Abid, T. Al-Ansari, Thermodynamic evaluation and optimization of a flat plate collector operating with alumina and iron mono and hybrid nanofluids, Sustain. Energy Technol. Assess. 37 (2020) 100636. [44] X. Li, G. Zeng, X. Lei, The stability, optical properties and solar-thermal conversion performance of SiC-MWCNTs hybrid nanofluids for the direct absorption solar collector (DASC) application, Sol. Energy Mater. Sol. Cells 206 (2020) 110323. [45] N. Akram, et al., Experimental investigations of the performance of a flat-plate solar collector using carbon and metal oxides based nanofluids, Energy 227 (2021) 120452. [46] M.A. Sharafeldin, G. Gro´f, E. Abu-Nada, O. Mahian, Evacuated tube solar collector performance using copper nanofluid: energy and environmental analysis, Appl. Therm. Eng. 162 (2019) 114205. [47] H. Kaya, N. Eltugral, A. Kurukavak, K. Arslan, Efficiency assessment of an evacuated U-tube solar collector using silver nanofluid, J. Sol. Energy Eng. 141 (6) (2019). [48] L. Lu, Z.-H. Liu, H.-S. Xiao, Thermal performance of an open thermosyphon using nanofluids for high-temperature evacuated tubular solar collectors: Part 1: indoor experiment, Sol. Energy 85 (2) (2011) 379e387. [49] Z.-H. Liu, R.-L. Hu, L. Lu, F. Zhao, H. Xiao, Thermal performance of an open thermosyphon using nanofluid for evacuated tubular high temperature air solar collector, Energy Convers. Manag. 73 (2013) 135e143. [50] J. Ghaderian, et al., Performance of copper oxide/distilled water nanofluid in evacuated tube solar collector (ETSC) water heater with internal coil under thermosyphon system circulations, Appl. Therm. Eng. 121 (2017) 520e536. [51] G. Kumaresan, S. Venkatachalapathy, L.G. Asirvatham, Experimental investigation on enhancement in thermal characteristics of sintered wick heat pipe using CuO nanofluids, Int. J. Heat Mass Tran. 72 (2014) 507e516. [52] J.A. Eastman, Novel Thermal Properties of Nanostructured Materials, Argonne National Lab., IL (US), 1999. [53] S. Venkatachalapathy, G. Kumaresan, S. Suresh, Performance analysis of cylindrical heat pipe using nanofluidsean experimental study, Int. J. Multiphas. Flow 72 (2015) 188e197. [54] A.A. Eidan, A. AlSahlani, A.Q. Ahmed, M. Al-fahham, J.M. Jalil, Improving the performance of heat pipe-evacuated tube solar collector experimentally by using Al2O3 and CuO/ acetone nanofluids, Sol. Energy 173 (2018) 780e788. [55] Y. Peng, et al., Investigation of energy performance in a U-shaped evacuated solar tube collector using oxide added nanoparticles through the emitter, absorber and transmittal environments via discrete ordinates radiation method, J. Therm. Anal. Calorim. 139 (4) (2020) 2623e2631. [56] H. Kim, J. Ham, C. Park, H. Cho, Theoretical investigation of the efficiency of a U-tube solar collector using various nanofluids, Energy 94 (2016) 497e507. [57] H. Kaya, M. Alkasem, K. Arslan, Effect of nanoparticle shape of Al2O3/Pure Water nanofluid on evacuated U-Tube solar collector efficiency, Renew. Energy 162 (2020) 267e284. [58] S.M.S. Al-Mashat, A.A. Hasan, Evaluation of convective heat transfer and natural circulation in an evacuated tube solar collector, J. Eng. 19 (5) (2013) 613e628.

Utilization of mono and hybrid nanofluids Chapter | 1 [59]

[60]

[61] [62] [63] [64]

[65]

[66]

[67]

[68]

[69]

[70] [71] [72]

[73]

[74]

[75]

43

Y.Y. Gan, H.C. Ong, T.C. Ling, N.W.M. Zulkifli, C.-T. Wang, Y.-C. Yang, Thermal conductivity optimization and entropy generation analysis of titanium dioxide nanofluid in evacuated tube solar collector, Appl. Therm. Eng. 145 (2018) 155e164. H. Kaya, K. Arslan, N. Eltugral, Experimental investigation of thermal performance of an evacuated U-Tube solar collector with ZnO/Etylene glycol-pure water nanofluids, Renew. Energy 122 (2018) 329e338. M.S. Dehaj, M.Z. Mohiabadi, Experimental investigation of heat pipe solar collector using MgO nanofluids, Sol. Energy Mater. Sol. Cells 191 (2019) 91e99. M.A. Sharafeldin, G. Grof, Evacuated tube solar collector performance using CeO2/water nanofluid, J. Clean. Prod. 185 (2018) 347e356. M.A. Sharafeldin, G. Gro´f, Efficiency of evacuated tube solar collector using WO3/Water nanofluid, Renew. Energy 134 (2019) 453e460. G. Sadeghi, S. Nazari, M. Ameri, F. Shama, Energy and exergy evaluation of the evacuated tube solar collector using Cu2O/water nanofluid utilizing ANN methods, Sustain. Energy Technol. Assess. 37 (2020) 100578. S. Iranmanesh, H.C. Ong, B.C. Ang, E. Sadeghinezhad, A. Esmaeilzadeh, M. Mehrali, Thermal performance enhancement of an evacuated tube solar collector using graphene nanoplatelets nanofluid, J. Clean. Prod. 162 (2017) 121e129. M.M. Sarafraz, M.R. Safaei, Diurnal thermal evaluation of an evacuated tube solar collector (ETSC) charged with graphene nanoplatelets-methanol nano-suspension, Renew. Energy 142 (2019) 364e372. I.M. Mahbubul, M.M.A. Khan, N.I. Ibrahim, H.M. Ali, F.A. Al-Sulaiman, R. Saidur, Carbon nanotube nanofluid in enhancing the efficiency of evacuated tube solar collector, Renew. Energy 121 (2018) 36e44. Y. Tong, J. Kim, H. Cho, Effects of thermal performance of enclosed-type evacuated U-tube solar collector with multi-walled carbon nanotube/water nanofluid, Renew. Energy 83 (2015) 463e473. H. Kaya, K. Arslan, Numerical investigation of efficiency and economic analysis of an evacuated U-tube solar collector with different nanofluids, Heat Mass Tran. 55 (3) (2019) 581e593. S. Akbarzadeh, M.S. Valipour, Heat transfer enhancement in parabolic trough collectors: a comprehensive review, Renew. Sustain. Energy Rev. 92 (2018) 198e218. G.K. Manikandan, S. Iniyan, R. Goic, Enhancing the optical and thermal efficiency of a parabolic trough collectoreA review, Appl. Energy 235 (2019) 1524e1540. M.S. Kamel, O. Al-Oran, F. Lezsovits, Thermal conductivity of Al2O3 and CeO2 nanoparticles and their hybrid based water nanofluids: an experimental study, Period. Polytech. Chem. Eng. 65 (1) (2021) 50e60. O. Al-Oran, F. Lezsovits, Recent experimental enhancement techniques applied in the receiver part of the parabolic trough collectoreA review, Int. Rev. Appl. Sci. Eng. 11 (3) (2020) 209e219, https://doi.org/10.1556/1848.2020.00055. A.K. Tiwar, V. Kumar, Z. Said, H.K. Paliwal, A review on the application of hybrid nanofluids for parabolic trough collector: recent progress and outlook, J. Clean. Prod. (2021) 126031. O. Ayadi, et al., Parametric investigation of nano-fluids utilization in Parabolic trough collector, in: 2021 12th International Renewable Engineering Conference, IREC), 2021, pp. 1e5.

44 PART | I Solar thermal energy [76] K.S. Chaudhari, P. V Walke, U.S. Wankhede, R.S. Shelke, An experimental investigation of a nanofluid (Al2O3þ H2O) based parabolic trough solar collectors, Curr. J. Appl. Sci. Technol. (2015) 551e557. [77] J. Subramani, P.K. Nagarajan, S. Wongwises, S.A. El-Agouz, R. Sathyamurthy, Experimental study on the thermal performance and heat transfer characteristics of solar parabolic trough collector using Al2O3 nanofluids, Environ. Prog. Sustain. Energy 37 (3) (2018) 1149e1159. [78] K.S.J. Jafar, B. Sivaraman, Thermal performance of solar parabolic trough collector using nanofluids and the absorber with nail twisted tapes inserts, Int. Energy J. 14 (4) (2015). [79] G. Huminic, A. Huminic, Hybrid nanofluids for heat transfer applicationsea state-of-the-art review, Int. J. Heat Mass Tran. 125 (2018) 82e103. [80] H. Babar, H.M. Ali, Towards hybrid nanofluids: preparation, thermophysical properties, applications, and challenges, J. Mol. Liq. 281 (2019) 598e633. [81] O. Al-Oran, F. Lezsovits, Thermal Performance of Inserting Hybrid Nanofluid in Parabolic Trough Collector, Pollack Period, 2021. [82] A.A. Minea, W.M. El-Maghlany, Influence of hybrid nanofluids on the performance of parabolic trough collectors in solar thermal systems: recent findings and numerical comparison, Renew. Energy 120 (2018) 350e364. [83] E. Bellos, C. Tzivanidis, Thermal analysis of parabolic trough collector operating with mono and hybrid nanofluids, Sustain. Energy Technol. Assess. 26 (2018) 105e115. [84] O. Al-Oran, F. Lezsovits, A. Aljawabrah, Exergy and energy amelioration for parabolic trough collector using mono and hybrid nanofluids, J. Therm. Anal. Calorim. (2020) 1e18. [85] O. Al-Oran, F. Lezsovits, A hybrid nanofluid of alumina and tungsten oxide for performance enhancement of a Parabolic trough collector under the weather conditions of budapest, Appl. Sci. 11 (11) (2021) 4946. [86] R. Ekiciler, K. Arslan, O. Turgut, B. Kurs¸un, Effect of hybrid nanofluid on heat transfer performance of parabolic trough solar collector receiver, J. Therm. Anal. Calorim. 143 (2) (2021) 1637e1654. [87] M. Tafavogh, A. Zahedi, Design and production of a novel encapsulated nano phase change materials to improve thermal efficiency of a quintuple renewable geothermal/hydro/ biomass/solar/wind hybrid system, Renew. Energy 169 (2021) 358e378. [88] M.S. Khan, M. Abid, M. Yan, T.A.H. Ratlamwala, I. Mubeen, Thermal and thermodynamic comparison of smooth and convergent-divergent parabolic trough absorber tubes with the application of mono and hybrid nanofluids, Int. J. Energy Res. 45 (3) (2021) 4543e4564. [89] A.A.A.A. Al-Rashed, A.A. Alnaqi, J. Alsarraf, Thermo-hydraulic and economic performance of a parabolic trough solar collector equipped with finned rod turbulator and filled with oil-based hybrid nanofluid, J. Taiwan Inst. Chem. Eng. 124 (2021) 192e204. [90] S. Rostami, A. Shahsavar, G. Kefayati, A. Shahsavar Goldanlou, Energy and exergy analysis of using turbulator in a parabolic trough solar collector filled with mesoporous silica modified with copper nanoparticles hybrid nanofluid, Energies 13 (11) (2020) 2946. [91] A. Khalil, et al., Performance analysis of direct absorption-based parabolic trough solar collector using hybrid nanofluids, J. Brazilian Soc. Mech. Sci. Eng. 42 (11) (2020) 1e10.

Chapter 2

Solar air heater performance improvement by photovoltaicpowered thermoelectric heat pumping Josue´ Rock Segnon1 and Howard Okezie Njoku1, 2 1

Sustainable Energy Engineering Research Group, University of Nigeria, Nsukka, Nigeria; Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa 2

1. Introduction 1.1 Designs of solar energy systems The quick depletion of fossil fuels, coupled with the environmental issues caused by their use, provide an impetus for exploration of renewable energy sources [1]. Over the last 2 decades, renewable energies experienced a rapid growth, with solar energy representing the fastest-growing alternative energy technology. Several types solar photovoltaic (PV) devices use solar cells to convert solar radiation into electricity, with their efficiency, varying up to 23%. The PV energy output is negatively affected by temperature rises in the PV module. Solar thermal devices, on the other hand, convert solar radiation into thermal energy useful in numerous heating applications such as agricultural crop drying, water heating, space heating, etc. [1]. Solar air heaters (SAHs) use air as heat transfer fluid for this energy conversion, heating air for numerous uses. Over the years, in the quest for improved performance, a wide range of SAHs has been developed. Numerous modifications have been made on the design of SAHs with the common aim of increasing the thermal energy production. This is achieved by either increasing the heat exchange rate between the absorber plate and the working fluid (air), or reducing the heat loss through a glazing use. Thus, an SAH can be designed with air flow either over, below (or both sides) of the absorber plate. Fans can be used for forced convection to increase the air flow rate through the collector, thus enhancing the thermal energy production. Renewable Energy Production and Distribution. https://doi.org/10.1016/B978-0-323-91892-3.00002-9 Copyright © 2022 Elsevier Inc. All rights reserved.

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46 PART | I Solar thermal energy

Means of improving the performance of SAHs also include the enhancement of the heat transfer surface by the use of fins, ribs, corrugated surfaces, and the use of thermal energy storage [2e4], etc. Glazing is used to reduce re-radiation from the absorber plate back to the environment. The glazing is used to counter the re-radiation and convection heat losses during the air heating process. The use of a cover plate is associated with three main functions [5,6]: the transmission as much as possible of the solar radiation to the absorber plate; the reduction of heat losses from the absorber plate back to the ambient; and the protection of the absorber plate from the outside environment and against rain. Depending on the application and the desired heat gain, single, double, triple, or even quadruple glass sheets may be used for glazing in the construction of solar collectors. However, the single pane glazing is commonly used [7] and a thickness of 3e4 mm was reported as ideal for the glazing [5,6,8]. Energy storage enhances the performance of energy systems in addition to its role in conserving the energy. Water is widely used in liquid-based heating applications, while rock-beds are widely used in air heating applications such as agricultural drying and space heating. Latent heat storage units, especially phase-change materials, are more suitable for enhanced thermal efficiency [9]. Phase change materials (PCMs) can absorb and release energy during the processes of melting and freezing, respectively. They can thus absorb and store energy in the day for later use in the night. PCM systems reduce the required space needed for energy storage. Thus, with the use of phase-change materials, the energy efficiency of solar thermal collectors is improved by up to 15% [10e12]. The effectiveness of the heat transfer between the absorber plate and the cooling air appears to be very critical to the performance of the SAH. The expansion of the exchange surface increases the heat exchange rate, and, hence, the SAH efficiency. The number of fins or baffles, as well as the arrangement, and their effect on the performance of the system have been investigated in theoretical or experimental works [13e15]. Artificial roughness mainly consists in thin wires or ribs on the absorbing surface. Roughness can be applied to a surface by blasting sand on it, or fixing ridges and grooves or ribs on it. The aim here is to create a turbulent flow on the heat transfer surface, increasing the convection heat transfer between the absorber plate and the flowing air. This method requires a fan or a blower to enhance the turbulent flow and thus the convection heat transfer. The use of fans or blower makes this method applicable only in forced convection applications [2,16,17]. The expansion of the exchange surface increases the heat exchange rate, and, hence, the SAH efficiency. Fig. 2.1 presents various types of modified surfaces in SAH construction [18]. Surface modification include the use of corrugated sheets (Fig. 2.1B and C), fins (Fig. 2.1D), and attached baffles or porous media (Fig. 2.1E). The number of fins or baffles, as well as the arrangement, and their effect on the performance of the system have been investigated in theoretical or experimental works [13e15]. Fudholi and Sopian

Solar air heater performance improvement Chapter | 2

47

FIGURE 2.1 Types of SAHs with modified absorbing surface. (A) Basic configuration. (B) V-corrugated surface SAH. (C) square-corrugated surface SAH. (D) Finned surface SAH. (E) Porous media SAH [18].

[18,19] conducted detailed reviews on the energy performance of SAHs. They summarized the main factors affecting the energy efficiency of SAHs and gave an overview of efficiency improvements studied by many researchers. The results can be summarized in three key points: i. The energy efficiency of SAHs is strongly dependent on mass flow rate and the heat transfer surface. Thus, increasing the air mass flow rate through the SAH by means of forced convection, and/or increasing the heat transfer surface by use of fins, corrugated surfaces, baffles, etc., results in higher efficiency; ii. The exergy efficiency of SAHs increases with the intensity of the solar radiation; iii. The energy and exergy efficiencies of the SAH range from 30% to 79% and 8%e61%, respectively. Moreover, they reported that the energy and exergy efficiencies of flat plate SAH in crop drying application (outdoor testing) range from 28% to 62% and from 30% to 57%, respectively. Other advances in solar energy harnessing systems combine two or more technologies in order to improve the energy output of the combined system. To address the temperature-related causes of the decrease in the electrical output of PV modules, air can be channeled through the back of the PV module in order to cool it, and at the same time, to produce hot air for heating applications. This combination is known as hybrid SAH, or PVT. In PVTs, the same absorbing surface is used to produce electricity and useful heat, and the

48 PART | I Solar thermal energy

unused heat produced by the PV module is harnessed. This is achieved by attaching a fluid-filled metal sheet absorber to the PV module. The heat is transferred to a fluid (liquid, air, or the combination of both) which, after being heated, is used in various applications such as space heating, water heating, water distillation, crop drying, etc. [20,21], with energy efficiency ranging from 31% to 94% [22,23]. Fig. 2.2 presents the sketch of basic PVT air collector. Removal of heat from the PV module minimizes the temperature-related causes of the reduced efficiency. The PVT thus achieves higher electrical efficiency with an enhancement of PV cells lifespan [21]. The mass flow rate plays an important role in regulating the convection heat transfer, which is crucial to the energy output of the SAH. The increase in the air flow rate makes the thermal and PV efficiencies of the PVT vary in the same direction. However, since parameters such as duct dimensions and air velocity affect the air flow rate, large flow rate makes the air-passage duration too short, not allowing the air to retrieve appreciable heat from the PV panel and the absorber plate. Thus, excessively increasing the air flow rate decreases the energy efficiency of the PVT. Depending on the model studied, researchers [25e29] have defined minimum and maximum values for the air flow rate enabling optimum energy efficiencies. However, a wide range of those values exist in the literature because dimensions considerably vary in the design of PVT SAHs. Nonetheless, it is very important to determine an optimum value for the air flow rate when designing PVT SAHs [30]. Sarhaddi et al. [29] conducted an analytic study on the thermal, electrical, and overall exergy efficiencies of a flat-plate PVT air collector. They reported that the overall energy efficiency of the model studied was 45%, while the thermal and electric efficiencies were 17.18% and 10.01%, respectively, for given inlet air temperature and inlet duct dimensions. They also reported that the temperature of the inlet air and its velocity, as well as climate conditions, were critical parameters affecting the overall energy efficiency of the PVT. The increase in the air velocity would result in an increase

FIGURE 2.2 Sketch of a PVT [24].

Solar air heater performance improvement Chapter | 2

49

of the efficiency. Sopian et al. [27] analyzed the effects of parameters such as ambient temperature, mass-flow rate, length of the collector, and packing factor on the performance of flat-plate PVTs using steady-state simulation models. They reported that regardless to the packing factor, the solar cells were further cooled as the air flow rate increased, for the same value of the collector length. Hence, increase of the electric efficiency was achieved by the increase of air flow rate. However, the increase in collector length decreased the PV efficiency. The average temperature of the absorber plate increased if its length varied in the same direction. Furthermore, air flow rate exceeding an optimum value also led to a decrease in the thermal efficiency. This is because, usually, motor fans are employed for improvement of the air flow rate through the collector. The energy input to the fans, then, accounts at the input side of the energy efficiency formula of the collector, hence negatively affecting its performance. This drawback makes increment of air flow rate not to always a systematic way of improvement of SAHs performance. Furthermore, solar PVT collector performances have been enhanced by the development of PVT designs combining water and air, using nanofluids, or integrating thermoelectric (TE) modules to produce additional electrical power from the temperature difference between the PV module and the surrounding air [31e33].

1.2 Thermoelectric-integrated solar energy systems Thermoelectric modules (TEMs) are solid-state electric modules that operate on the principle of the Seebeck effect (named after the German physicist Thomas Johann Seebeck). In 1822, Seebeck first observed the relationship between heat and electromagnetism. He found that when two dissimilar materials were joined together and the junctions held at different temperatures (T and T þ DT), a voltage difference (DV) appeared, that is proportional to the temperature difference (DT). The Seebeck effect governs power generation using TEMs [34,35], and the Seebeck coefficient, a, which is related to the material properties, characterizes the TE potential of materials used in Seebeck power generation. It is greater for semiconductors than for metals. a ¼ DV=DT

(2.1)

Solar-based TE applications have great potential for both power generation and refrigeration from the natural and endless supply of energy from the sun. The attention given to this technology has then been increasing since the past 2 decades. Seebeck devices can generate electrical power by harnessing the energy from the sun (in the form of heat) [36,37]. Peltier devices can be powered by PV modules or other DC sources to perform solid state heating, cooling, or refrigeration. Solar-TE heat pumping is promising in many fields such as indoor comfort, food storage, water condensation, etc. [38].

50 PART | I Solar thermal energy

FIGURE 2.3 Hybrid PV-TE power generation [40].

From the temperature difference between the PV module and the air, thermoelectric generators (TEGs) produce an electrical output which, added to the output of the PV module, enhances the electrical energy harvested from the same absorbing surface, that of the PV module. The PV-TEG combination (Fig. 2.3) achieved energy conversion systems up to 32% [39,40], while the standalone PV and the TEGs achieve maximum efficiencies of 20% and 7%, respectively [41]. In PV-TEG systems, the integration of TE modules is aimed at enhancing the PV electrical output, rather than cooling the PV module to improve its efficiency. Moreover, with the development of new TE materials, there is a belief that efficiency increments could reach 50% [42,43]. Li et al. [44] reviewed the performance and recent advances in PV-TE, as well as the challenges faced in the field and solutions proposed by researchers. They reported that TE combination with PV collectors has more focus on extra electricity generation and that PV-TE is a very interesting solution for solar energy harnessing because it takes great advantage of the power generation of both PV and TE modules. They also reported that improvements of TE modules’ efficiencies and decrease of their cost would increasingly develop high-performance solar energy harnessing systems and give TE modules more energy systems to conquer [45,46]. TE coolers provide solid-state energy conversion. When a DC current flows through the junction of a TEC, a temperature difference is created across the TEC, allowing heat to flow from one side to the other of the TE module. In solar-TE heat pumping, PV modules produce that DC current, which is used to power the TEC. In contrast to solar-TE power generation where the input is the temperature difference and the output is the electricity, in solar heat pumping, the electricity is the input and the temperature difference the output. The DC current used to power the TECs can be produced by a PV module [47]. They provide compact, light, and reliable cooling, compared to conventional systems [48], and, when coupled with PV modules, they provide an environmentally friendly thermal energy conversion technology for space heating/ cooling, refrigeration, water desalination [49e51] (Fig. 2.4).

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51

FIGURE 2.4 Hybrid PV-TE cooling [48].

FIGURE 2.5 Structure of the hybrid PV-TEM system with supply and control [52].

Fig. 2.5 shows a structure of the hybrid PV-TEM system where TE coolers are used to pump heat from the PV panel to cool it in order to achieve higher electrical efficiency. Achieving lower PV cell temperatures allows the PV module to operate better and thus increases its electrical power output [52]. Different parameters such as wind velocity, solar irradiation, etc., affect the performance of the TE cooling and the energy output of the PV module. Cai et al. [53] modeled the air cooling and water production using TE heat pumping and reported that the increment of the input power to the TE modules increased the total cooling load but decreased the system efficiency

52 PART | I Solar thermal energy

significantly. An analytic model proposed by Moshfegh et al. [54] for predicting the PV cell temperature and the increment of the PV module efficiency showed that the electricity output of the PV module decreases due to the fact that the power for operating the TEC was provided by the PV module. Increased wind velocity acted as a cooling factor and thus increases the energy output of the module, while reducing the TEC effect. However, at low wind velocities, the TE cooling is more effective. It has been suggested that an optimization of TE cooling, combined with forced convection, should be studied to increase the efficiency of this model. In the present study, PV powered TE cooling of the absorber plate was applied in an SAH to improve the performance. Experimental work was conducted on the SAH to evaluate the effect of TE heat pumping on the heat collection, the heat losses, and the energy efficiency. TE hybridization has been shown to improve performance, mostly for additional power production. But this has not been largely attempted with solar thermal systems for enhanced heat production. Also, high temperatures in the absorber plate increase losses and decrease the performance of the SAH. With TE cooling of the absorber plate, these losses can be reduced. The TE modules, which serve as heat pumps when powered by the PV module, cool the absorber plate and dissipate the heat at their hot end. The heat transfer fluid (air) collects the heat at a higher temperature from the hot end of the TEC, and then, exits the collector with high temperature, hence improving its heat collection.

2. Materials and methods 2.1 System description Fig. 2.6 presents an overview of the PV-TE-SAH investigated in this study. The flat-plate SAH studied in this chapter was constructed with the materials presented in Table 2.1. Four TECs (TEC1-12706) were attached at the back of

FIGURE 2.6 Overview of the solar collector.

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TABLE 2.1 SAH materials. Glazing

A/R coated, 3 mm, se ¼ 0.96

Casing

Wood

Absorber plate

Fig. 2.8, ac ¼ 0.85

Insulation

20 mm thick

TE module

Table 2.2

PV module

Table 2.2

a 430  430 mm2 metal sheet absorber plate. The energy output of the 40Wp PV module, adjacent to the thermal collector, was used to power the TECs. Part of the solar radiation incident on the collector (PV þ thermal) is converted into thermal energy by the thermal collector and the TE heat pumps attached at the back of the absorber plate (Fig. 2.7) are powered by the DC power output of the PV module to pump heat from the absorber plate. Thus, the absorber plate temperature is lowered, and the pumped heat is dissipated at the hot side of the TEM into the air channel. The cold side of the TE modules is in contact with the rear side of the absorber plate, while heat sinks are attached to the TEC hot side, to improve the heat dissipation into the air channel. Although three energy conversion subsystems are involved (thermal, PV, and TE), two forms of energy are being assessed, i.e., heat and electricity. Part of the electricity produced by the PV module is used to power the TECs, attached at the back of the thermal absorber plate, to pump heat from it, and thus increase the thermal energy produced by the system. In this study, however, since no PV control (battery and charge controller) was used, and no external electrical load, all the PV output was channeled into the heat pumping system according to Fig. 2.9, which, also can only be applied for the outdoor test for validation. The final output of the system will, then, be Qu, while the input was [S  Ac].

FIGURE 2.7 Cross-sectional view of the thermal collector.

54 PART | I Solar thermal energy

FIGURE 2.8 Absorber plate. (1) Absorber plate; (2) TE Cooler; (3) Heat sinks.

TABLE 2.2 TE and PV modules specifications. Characteristics

Value

TE module Model

TEC1-12706

Couples N

127

Dimensions (mm)

40  40  4.2

DTmax (K)

68

Qmax(W)

63

PV module Model

HU 40

Cell type

Mono-Si

Pmax(W)

40  3%

Cell efficiency (%)

17.3

Module efficiency (%)

12.84

Dimensions (mm)

670  430  22

Solar air heater performance improvement Chapter | 2

55

FIGURE 2.9 Energy balance in the TE heat pumping SAH.

2.2 Experimental procedures A primary assessment of the solar energy profile in the study area (Nsukka, 6.8429 N,7.3733 E, Nigeria) was conducted to determine the minimum number of TECs of the type TEC1-12706, powered with a PV module of the type HU 40, will be necessary to produce an effect on the heat removal from the absorber plate of dimensions 430  430 mm. To evaluate the effect of the TE heat pumping on the different performance parameters of the collector, two prototypes of the SAH were constructed, of the same dimensions and configurations, and were tested under the same conditions. The two collectors were back-pass collectors, i.e., the airflow was channeled between the back-side of the absorber plate and an insulated back-plate. One collector, which had no TEC attached to the back of the absorber plate served as a reference system. The performance of the PV-TE-SAH, in which the 4 TECs were attached, was compared to those of the reference SAH. Solar irradiance is the primary form of energy incident on the air collector and varies from morning to evening, and throughout the days of the year. In order to avoid the irradiance fluctuations, hence the input energy to the collectors, indoor experiments were first conducted in a laboratory setup. Simulated irradiance, using two short-wavelength halogen lights, concentrated on the thermal collector. The halogen lights were rated 500 W each. Thus, the input energy to the collector system was constant throughout the indoor experiments. The measurement with the solarimeter (TES-1333R) revealed a constant irradiance of 890 W/m2 on the collector. The TECs were powered by a DC source rated 12 V/2 A output. In the indoor experiments, only the thermal collector was tested. The airflow was natural, no fan was used. Fig. 2.10 presents the indoor experimental setup with the different measurement instruments connected for data collection. Subsequently, in order to validate the results from the indoor experiments, and to assess the performance of the PV-TE-SAH in real-life use, outdoor

56 PART | I Solar thermal energy

FIGURE 2.10

Laboratory experimental setup.

experiments were also conducted, under real-sky conditions at the University of Nigeria, Nsukka (6.8429 N,7.3733 E, Nigeria) on two different days, and the performance parameters were evaluated and compared. Fig. 2.11 presents the outdoor experimental setup. In both indoor and outdoor experimental setups, the collector was tilted at an angle of 25 degrees to the horizontal, the average of the optimal tilt range defined by previous works in the same experimentation area [55,56]. The temperature at different points of the collector, the irradiance, as well as airflow data were collected to enable evaluation of the performance parameters such as heat collection, energy efficiency, absorber plate cooling, heat loss coefficient, overall heat losses, and heat removal factor. The temperature rise Trise (Eqn. 2.2) of the working air is the temperature difference between the outlet and the inlet of the collector. It is one of the most important performance parameters as it defines, together

FIGURE 2.11 Outdoor experimental setup.

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with the airflow rate, the amount of energy gained Qu (Eqn. 2.3) by the working air as it passed through the collector. Trise ¼ Tout  Tin

(2.2)

_ p Trise Qu ¼ mC

(2.3)

where Tin and Tout are the air temperature at the inlet and the outlet of the collector, respectively; m_ (Eq. 2.4) is the airflow rate through the collector
 (kg/s); Cp is the air heat capacity (JK1kg1) JK 1 kg1 m_ ¼ rvAd

(2.4)

r is the density of air (kg/m ), v is the air velocity (m/s), and Ad is the crosssectional area of the collector (m2). Over the duration of the experiments, the amount of energy produced can be assessed by the cumulative heat collection Qcum (Eqn. 2.5). Z t _ out  Tin Þdt Qcum ¼ (2.5) mcðT 3

0

A similar parameter for heat collection by the collector is the heat loss coefficient, determined from the energy input Ein and the energy output Qu (Eqn. 2.6) Uloss ¼

Qloss Ein  Qu ¼ AC ðTav  Tin Þ AC ðTav  Tin Þ

Qloss ¼ Uloss Ac ðTav  Tin Þ Tav ¼

Tout þ Tin 2

(2.6) (2.7) (2.8)

where Tav (K) is the collector average temperature, Qloss (W) is the rate of heat losses, and Uloss (W/m2K) is the overall heat loss coefficient. This allows the comparison of the heat losses for the two collectors and hence, the heat collection capacity and the effect of the TE heat pumping of it. Over the duration of the experiments, the cumulative heat losses can be estimated by Z t Qlosscum ¼ Uloss Ac ðTav  Tin Þdt (2.9) 0

The rate of thermal energy output, relative to the rate of energy input, is obtained by the instantaneous thermal energy efficiency hth (Eqn. 2.10) hth ¼

Qu SAc þ Pin

(2.10)

where S is the irradiance (W/m2) and Pin (W) is the power input to a TEC.

58 PART | I Solar thermal energy

Alternatively, the instantaneous efficiency of the SAH can be expressed as [57]: hth ¼ FR ðTe ac Þ  FR Uloss

Tav  Tin S

(2.11)

where ac is the absorptance of the absorber plate; FR is the heat removal factor of the collector, which is also an important performance parameter for solar flat-plate collectors [7]. From Eq. (2.11), the heat removal factor can be calculated as hth FR ¼ (2.12) Tav  Tamb ac Te  Uloss S The cumulative efficiency relates the cumulative heating rate to the cumulative energy input rate to the system, and is computed using Eq. (2.13) Rt _ out  Tin Þdt mcðT hcum ¼ 0 R t (2.13) 0 ðSAc Þdt

3. Results and discussions 3.1 Indoor experiments In the indoor experiments, the prototypes were tested for 3 h, subdivided in two parts. The transient phase, during which the significant changes in the temperature profiles were observed, lasted for 50 min. After 1 h, the temperature profiles were stabilized and therefore showed less variations. Fig. 2.12 presents the temperature profiles for the inlet and outlet air. The inlet air was about 29 and 28 C for the reference SAH and the TE-SAH, respectively.

FIGURE 2.12 Temperature profiles. (A) Inlet and Outlet; (B) Temperature rise.

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But the outlet air exited with higher temperatures in the TE-SAH than in the conventional SAH. A maximum outlet air temperature (Tout) value of 63 C was observed in the TE-SAH, 5 C higher than in the conventional SAH where the maximum value of Tout was 58 C (Fig. 2.12A). Correspondingly, the maximum value of the temperature rise Trise in the reference and the TE heat pumping SAHs were 26 and 33 C, respectively, representing an increase of 7 C by the application of TE heat pumping (Fig. 2.12B). The heating rate, or heat collection rate Qu, also increased by the application of TE heat pumping. After 50 min of operation, when variations became more stabilized, Qu reached an average value of 100 W for the TE-SAH, against 65 W for the conventional SAH (Fig. 2.13A). The cumulative heat collection rates were evaluated from the experiments using Eq. (2.5). As shown in Fig. 2.13B, the cumulative thermal energy produced by the SAH was 11.1 and 16.2 kJ, without TEC and with TEC, respectively. That represents an addition of 5.1 kJ of thermal energy by the TE heat pumping. Relative to the conventional SAH, this addition in heat corresponds to an increment of 45.9%, which is a significant figure. Analysis of the airflow rate through the collector (Fig. 2.14) showed that the natural air convection rate was higher in the TE-SAH than in the conventional SAH. This additionally contributed to the increased heat collection in the TE-SAH, as similarly reported by Refs. [4,19]. Thus, TE heat pumping resulted in two outcomesdincreased Tout and airflow rate, which increased the heat collection in the TE-SAH. Fig. 2.14 also showed that the absorber plate temperature Tplate was higher in the TE-SAH than in the conventional SAH, despite the higher airflow rate in the former. This depicts the fact that the airflow in the TE-SAH was still not enough to properly evacuate the heat rejected at the hot ends of the TECs (temperatures at the hot sides reached values above 110 C). Since the mass flow rate needed for heat transfer depends on the temperature (the geometry

FIGURE 2.13 Heat collection. (A) instantaneous; (B) Cumulative.

60 PART | I Solar thermal energy

FIGURE 2.14

Heat collection rate.

being the same) of the heat source, there is then need for further increase in the airflow rate to achieve proper cooling of the absorber plate. This would increase the heat collection and hence the SAH performance. Fig. 2.15 compares the energy efficiency of the two collectors and shows that the instantaneous values of hth were higher in the TE-SAH than in the

FIGURE 2.15 Energy efficiency.

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reference SAH. Over the experiments duration, the TE-SAH achieved a cumulative efficiency of 44.95%, which was 5% higher than what was obtained without TE heat pumping (39.92%). Relatively to the reference SAH, this corresponds to an increase in the energy efficiency of 13%, which is rather moderate compared to the increase in heat gain. This may be explained by the fact that the power input to the TECs (Pin) added to the irradiance (GAc), increased the energy input to the system in the TE-SAH, compared to the reference SAH. This should reduce the energy efficiency of the collector. However, the increase in the thermal energy output (Qu) was enough to compensate for the increase in the input energy. Furthermore, the heat loss factor and the overall heat losses could be evaluated by estimating an average temperature for the collector Tavr [4]. Using Eq. (2.6), the heat loss coefficient was computed and the scatter plot in Fig. 2.16 shows an estimated value of 7.4 W/m2K for the conventional SAH, against 3.95 W/m2K for the TE-SAH. Hence, the heat loss factor was significantly reduced (by as much as 47%) in the TE-SAH, compared to the conventional SAH. Also, using Eq. (2.7), the overall heat losses of the collectors were estimated. As shown in Fig. 2.16, the heat losses were significantly decreased in the TE-SAH compared to the conventional SAH. The cumulative heat losses, for the duration of the experiments, were 3 kJ for the TE-SAH, against 4.01 kJ for the conventional SAH. This depicts a decrease in the heat losses by as much as 34.23% due to the application of TE heat pumping. Next, using the heat removal factor FR,

FIGURE 2.16 Estimated heat loss coefficient.

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the actual thermal energy gain of the collector could be related to the theoretical energy gain if the whole collector were at the inlet temperature. The instantaneous values of FR were computed and an estimate of its value determined for the duration of the experiments. As in the case of the heat loss factor, values of FR presented little variations about a mean value after the system reached a steady state (after 50 min). Hence, the estimated value of the heat removal factor in the TE-SAH was 0.59, against 0.52 in the conventional SAH. This depicts an addition of 0.7 in the heat removal factor, which corresponds to an increase of 13.46%, relative to the reference SAH. TE heat pumping, thus, also improved the heat removal factor of the solar air collector.

3.2 Outdoor experiments In an outdoor setup, the two collectors were tested under real-sky conditions on two typical sunny days, at the University of Nigeria, to validate the results obtained using simulated irradiance in the indoor setup. Fig. 2.17A shows that the irradiance recorded during tests on the conventional SAH was higher than those obtained during tests on the TE-SAH. Despite this, the temperature rises of the working air reached higher values in the PV-TE-SAH (32 C) than in the reference SAH (26 C), an increase by 6 C (Fig. 2.17B). The PV module received solar radiation, converted it into electricity, which was channeled through the junctions of the TE heat pumps to pump heat from the absorber plate and reject at the heat sinks at the hot side. As ambient air flowed through the collector, it acquired more useful heat as it exchanges heat with the finned surface of the heat sinks. The amount of heat pumped depends on the power input to the TECs, i.e., the power output of the PV module. Thus, during sun peak hours (12e3 PM), when the power output of the PV module reached its maximum values, the heat collection of the PVTE-SAH was higher than that of the reference SAH as shown in Fig. 2.18. For the duration of the tests, the cumulative thermal energy gain was 2.62 and 2.11 MJ with and

FIGURE 2.17 Irradiance during the outdoor experiments (A) Irradiance; (B) Temperature rise.

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FIGURE 2.18 Heat collection (A) Instantaneous; (B) Cumulative.

without TE heat pumping, respectively, corresponding to an increase of 24.2%. Similarly, the cumulative energy efficiency was higher for the TE-SAH than the conventional SAH during sun peak hours. hcum was 28.2% and 46.7% for the reference SAH and the PV-TE-SAH, respectively, an increase of 65.6%, due to the application of TE heat pumping. The airflow rate also affected the performance of the SAHs in the outdoor setup. Fig. 2.19 compares the airflow rates (natural convection) and the absorber plate temperatures in the two collectors for the outdoor tests. Here also, the flow rate was higher in the PV-TE-SAH than in the reference SAH, which also contributed to the increase in heat collection by the PV-TE-SAH.

FIGURE 2.19 Estimated heat loss coefficient and heat losses.

64 PART | I Solar thermal energy

Furthermore, the values of the airflow rate in the outdoor setup were higher than in the indoor setup, and then, was enough to lower the temperature of the absorber plate in the PV-TE-SAH, compared to the conventional SAH. Furthermore, the heat loss coefficient was also estimated for the two collectors in the outdoor setup. The average value of Uloss was 5.38 W/m2K in the conventional SAH, higher than 3.36 W/m2K obtained in the PV-TE-SAH. Consequently, the heat losses were also reduced in the PV-TE-SAH compared to the conventional SAH. For the duration of the tests, the cumulative energy losses in the PV-TE-SAH were 1.33 MJ, 57.6% less than in the conventional SAH (3.13 MJ). Those values were lower than in the indoor setup due to the increased airflow rate in the outdoor tests. Also, the heat removal factor was enhanced from 0.501 in the conventional SAH to 0.594 in the PV-TE-SAH, quite similar to what was obtained in the indoor setting. Finally, the power output of the PV module was used to power the TE heat pumps, and thus, increment of the PV output could improve the overall performance of the system.

4. Conclusions In this study, TE heat pumping, powered by a PV module, was integrated into a SAH to increase heat collection and energy conversion efficiency. Different performance parameters of the TE-SAH were compared with those of a conventional SAH. In an indoor setup, simulated irradiance was used to control the energy input to the system. The heat collection and the energy efficiency were improved by 45.9% and 13%, respectively, due to the application of TE heat pumping. However, it was also found that the airflow rate was also an important factor in the improvement of the SAH’s performance. The natural air convection (0.001e0.008 kg/s) in the indoor setup was not enough to properly evacuate the heat rejected on the TE hot side, causing the ineffective lowering of the absorber plate temperature. The increased airflow rate (0.004e0.015 kg/s) obtained in the outdoor setup, with the lowering of Tplate, confirmed that improving the airflow rate was necessary for proper cooling of the absorber plate. As a consequence, the heat collection and the energy efficiency were also increased by 24.2% and 65.6%, respectively, and the heat losses were significantly reduced, by up to 56.7%. Also, the heat removal factor of the TE SAH was estimated at 0.59, higher than that of the conventional SAH. This study proved TE heat pumping as a viable way of improving the thermal performance parameters of SAHs and opens the way for further investigations of the proposed combination for the advancement of solar thermal energy conversion systems.

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References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10]

[11]

[12]

[13] [14] [15]

[16] [17] [18] [19] [20]

A. Sharma, C. Chen, N.V. Lan, Solar-energy drying systems: a review, Renew. Sustain. Energy Rev. 13 (6) (2009) 1185e1210. T.S. Kumar, N. Thakur, A. Kumar, V. Mittal, Use of artificial roughness to enhance heat transfer in solar air heaters-a review, J. Energy South Afr. 21 (1) (2010) 35e51. R. Kumar, M.A. Rosen, A critical review of photovoltaicethermal solar collectors for air heating, Appl. Energy 88 (11) (2011) 3603e3614. A. Fudholi, M. Zohri, I. Taslim, F. Aliyah, A.G. Koto, Heat transfer and efficiency of dual channel PVT air collector: a review, Int. J. Power Electron. Drive Syst. 10 (4) (2019) 2037. P. Saini, D.V. Patil, S. Powar, Review on integration of solar air heaters with thermal energy storage, in: Applications of Solar Energy, Springer, 2018, pp. 163e186. R. Bakari, R.J. Minja, K.N. Njau, Effect of glass thickness on performance of flat plate solar collectors for fruits drying, J. Energy 2014 (2014). J.A. Duffie, W.A. Beckman, N. Blair, Solar Engineering of Thermal Processes, Photovoltaics and Wind, fifth ed., John Wiley & Sons, 2020. A. Eggers-Lura, Solar Energy in Developing Countries. An Overview and Buyers’ Guide for Solar Scientists and Engineers, vol. 79, Pergamon Press, Oxford, 1979. M.M. Alkilani, K. Sopian, M. Alghoul, M. Sohif, M. Ruslan, Review of solar air collectors with thermal storage units, Renew. Sustain. Energy Rev. 15 (3) (2011) 1476e1490. A. El Khadraoui, S. Bouadila, S. Kooli, A. Farhat, A. Guizani, Solar air heater with phase change material: an energy analysis and a comparative study, Appl. Therm. Eng. 107 (2016) 1057e1064. A. El Khadraoui, S. Bouadila, S. Kooli, A. Farhat, A. Guizani, Thermal behavior of indirect solar dryer: nocturnal usage of solar air collector with PCM, J. Clean. Prod. 148 (2017) 37e48. A. Kabeel, A. Khalil, S. Shalaby, M. Zayed, Experimental investigation of thermal performance of flat and v-corrugated plate solar air heaters with and without PCM as thermal energy storage, Energy Convers. Manag. 113 (2016) 264e272. F. Chabane, N. Moummi, S. Benramache, Experimental study of heat transfer and thermal performance with longitudinal fins of solar air heater, J. Adv. Res. 5 (2) (2014) 183e192. F. Bayrak, H.F. Oztop, A. Hepbasli, Energy and exergy analyses of porous baffles inserted solar air heaters for building applications, Energy Build. 57 (2013) 338e345. C.-D. Ho, H. Chang, R.-C. Wang, C.-S. Lin, Performance improvement of a double-pass solar air heater with fins and baffles under recycling operation, Appl. Energy 100 (2012) 155e163. A. Kumar, R. Saini, J. Saini, A review of thermohydraulic performance of artificially roughened solar air heaters, Renew. Sustain. Energy Rev. 37 (2014) 100e122. R.K. Srivastava, A.K. Rai, A review on performance enhancement of solar air heater, Int. J. Mech. Prod. Eng. Res. Dev. 7 (5) (2017) 279e288. A. Fudholi, K. Sopian, Review on exergy and energy analysis of solar air heater, Int. J. Power Electron. Drive Syst. 9 (1) (2018) 420e426. A. Fudholi, K. Sopian, A review of solar air flat plate collector for drying application, Renew. Sustain. Energy Rev. 102 (2019) 333e345. D. Zenh€ausern, E. Bamberger, A. Baggenstos, A. H€aberle, PVT Wrap-Up: Energy Systems with Photovoltaic-Thermal Solar Collectors, 2017. Technical report.

66 PART | I Solar thermal energy [21] V. Oner, M. Yesilyurt, E.C. Yilmaz, G. Omeroglu, Photovoltaic thermal (PVT) solar panels, Int. J. New Technol. Res. 2 (2016) 13e16. [22] A. Fudholi, M.F. Musthafa, A. Ridwan, R. Yendra, A.P. Desvina, R. Rahmadeni, T. Suyono, K. Sopian, Energy and exergy analysis of air based photovoltaic thermal (PV/T) collector: a review, Int. J. Electr. Comput. Eng. 9 (1) (2019) 109e117. [23] T. Chow, A review on photovoltaic/thermal hybrid solar technology, Appl. Energy 87 (2) (2010) 365e379. [24] N. Boulfaf, J. Chaoufi, A. Ghafiri, A. Elorf, Thermal study of hybrid photovoltaic thermal (PV-T) solar air collector using finite element method, Int. J. Renew. Energy Resour. 6 (1) (2016) 171e182. [25] A. Tiwari, M. Sodha, Parametric study of various configurations of hybrid PV/T air collector: experimental validation of theoretical model, Sol. Energy Mater. Sol. Cell. 91 (1) (2007) 17e28. [26] A.A. Hegazy, Comparative study of the performances of four photovoltaic/thermal solar air collectors, Energy Convers. Manag. 41 (8) (2000) 861e881. [27] K. Sopian, K. Yigit, H. Liu, S. Kakac, T. Veziroglu, Performance analysis of photovoltaic thermal air heaters, Energy Convers. Manag. 37 (11) (1996) 1657e1670. [28] R. Kumar, M.A. Rosen, Performance evaluation of a double pass PV/T solar air heater with and without fins, Appl. Therm. Eng. 31 (8) (2011) 1402e1410. [29] F. Sarhaddi, S. Farahat, H. Ajam, A. Behzadmehr, M.M. Adeli, An improved thermal and electrical model for a solar photovoltaic thermal (PV/T) air collector, Appl. Energy 87 (7) (2010) 2328e2339. [30] K. Moradi, M.A. Ebadian, C.-X. Lin, A review of PVT technologies: effects of control parameters, Int. J. Heat Mass Tran. 64 (2013) 483e500. [31] N.S. Nazri, A. Fudholi, M.H. Ruslan, K. Sopian, Mathematical modeling of photovoltaic thermal-thermoelectric (PVT-TE) air collector, Int. J. Power Electron. Drive Syst. 9 (2) (2018) 795. [32] N.S. Nazri, A. Fudholi, M.H. Ruslan, K. Sopian, Experimental study of photovoltaic thermal-thermoelectric (PVT-TE) air collector, Int. J. Power Electron. Drive Syst. 9 (3) (2018) 1390. [33] N.S. Nazri, A. Fudholi, B. Bakhtyar, C.H. Yen, A. Ibrahim, M.H. Ruslan, S. Mat, K. Sopian, Energy economic analysis of photovoltaicethermal-thermoelectric (PVTTE) air collectors, Renew. Sustain. Energy Rev. 92 (2018) 187e197. [34] E. Velmre, Thomas Johann Seebeck (17701831), Estonian J. Eng. 13 (4) (2007). [35] T.M. Tritt, M. Subramanian, Thermoelectric materials, phenomena, and applications: a bird’s eye view, MRS Bull. 31 (3) (2006) 188e198. [36] C.A. Mgbemene, J. Duffy, H. Sun, R.O. Onyegegbu, Electricity generation from a compound parabolic concentrator coupled to a thermoelectric module, J. Sol. Energy Eng. 132 (3) (2010). [37] D. Kraemer, B. Poudel, H.-P. Feng, J.C. Caylor, B. Yu, X. Yan, Y. Ma, X. Wang, D. Wang, A. Muto, et al., High-performance flat-panel solar thermoelectric generators with high thermal concentration, Nat. Mater. 10 (7) (2011) 532e538. [38] R.M. Atta, Solar water condensation using thermoelectric coolers, Int. J. Water Resour. Arid Environ. 1 (2) (2011) 142e145. [39] N. Calderon-Henao, O.J. Venturini, E.H.M. Franco, E. Eduardo Silva Lora, H.F. Scherer, D.M.Y. Maya, O.H. Ando Junior, Numericaleexperimental performance assessment of a non-concentrating solar thermoelectric generator (STEG) operating in the southern hemisphere, Energies 13 (10) (2020) 2666.

Solar air heater performance improvement Chapter | 2 [40]

[41] [42] [43] [44] [45]

[46] [47] [48] [49]

[50]

[51] [52] [53]

[54] [55] [56]

[57]

67

R. Bjørk, K.K. Nielsen, The maximum theoretical performance of unconcentrated solar photovoltaic and thermoelectric generator systems, Energy Convers. Manag. 156 (2018) 264e268. K.A. Ejenakevwe, C.A. Mgbemene, H.O. Njoku, O.V. Ekechukwu, Parametric optimization of exergy efficiency in solar thermoelectric generators, J. Electron. Mater. 1e9 (2020). W. Van Sark, Feasibility of photovoltaice thermoelectric hybrid modules, Appl. Energy 88 (8) (2011) 2785e2790. R. Bjørk, K.K. Nielsen, The performance of a combined solar photovoltaic (PV) and thermoelectric generator (TEG) system, Sol. Energy 120 (2015) 187e194. G. Li, S. Shittu, T.M. Diallo, M. Yu, X. Zhao, J. Ji, A review of solar photovoltaicthermoelectric hybrid system for electricity generation, Energy 158 (2018) 41e58. S. Diwania, S. Agrawal, A.S. Siddiqui, S. Singh, Photovoltaicethermal (PV/T) technology: a comprehensive review on applications and its advancement, Int. J. Energy Environ. Eng. 11 (1) (2020) 33e54. S. Verma, S. Mohapatra, S. Chowdhury, G. Dwivedi, Cooling techniques of the PV module: a review, Mater. Today Proc. 38 (2021) 253e258. G. Slack, D. Rowe, Thermoelectrics Handbook: Macro to Nano, 1995. I. Sarbu, C. Sebarchievici, A comprehensive review of thermal energy storage, Sustainability 10 (1) (2018) 191. Y. Luo, L. Zhang, Z. Liu, J. Wu, Y. Zhang, Z. Wu, X. He, Performance analysis of a selfadaptive building integrated photovoltaic thermoelectric wall system in hot summer and cold winter zone of China, Energy 140 (2017) 584e600. M. Ibaneez-Puy, C. Martın-Gomez, J. BermejoBusto, J.A. Sacristan, E. Ibaneez-Puy, Ventilated active thermoelectric envelope (VATE): analysis of its energy performance when integrated in a building, Energy Build. 158 (2018) 1586e1592. K. Ong, Review of solar, heat pipe and thermoelectric hybrid systems for power generation and heating, Int. J. Low Carbon Technol. 11 (4) (2016) 460e465. D. Enescu, F. Spertino, Applications of hybrid photovoltaic modules with thermoelectric cooling, Energy Proc. 111 (2017) 904e913. Y. Cai, D.-D. Zhang, D. Liu, F.-Y. Zhao, H.-Q. Wang, Air source thermoelectric heat pump for simultaneous cold air delivery and hot water supply: full modeling and performance evaluation, Renew. Energy 130 (2019) 968e981. H. Moshfegh, M. Eslami, A. Hosseini, Thermoelectric cooling of a photovoltaic panel, in: The Role of Exergy in Energy and the Environment, Springer, 2018, pp. 625e634. S.O. Enibe, Performance of a natural circulation solar air heating system with phase change material energy storage, Renew. Energy 27 (1) (2002) 69e86. C. Mgbemene, I. Jacobs, C. Agbo, S. Nwanya, C. Ozoegwu, Experimental investigation on the performance of a solar air heater with the absorber plate made of aluminium soda cans, in: Nigeria beyond Recession: Unlocking the Potentials of Solar Energy for Economic Recovery, Solar Energy Society of Nigeria, Abuja, 2017. J.A. Duffie, W.A. Beckman, Solar Engineering of Thermal Processes, Wiley, New York, 1991.

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Part II

Solar photovoltaic energy

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Chapter 3

A grid connected PV system based on a reduced delta inverter Asma Ben Rhouma Universite´ de Sousse, Ecole Nationale d’Inge´nieurs de Sousse, LATIS- Laboratory of Advanced Technology and Intelligent Systems, Sousse, Tunisia

1. Introduction The continuous depletion of fossil fuels and the growth in electricity demand have highlighted the great need of electric power generation by sustainable energy resources. The solar energy, wind energy, and geothermal energy are one of the most used sources of renewable energy for the electrical energy production. Actually, the solar energy has emerged as the most attractive natural source in terms of its clean nature, nongreenhouse gas emissions, noiseless, nonpolluting, and its availability especially in the desert zone [1e4]. Using the photovoltaic (PV) panels, the PV system converts the solar energy to the electricity. These PV systems can be operated as standalone or grid connected [5,6]. In the case of the second category, the connection of the PV system to the grid is performed essentially by a voltage source DC/AC inverter, used to convert DC power obtained from PV panels into AC power integrated into the grid [6e8]. The grid connected PV systems may include also a DC/DC boost converter to boost and regulate the output voltage of the PV panel and to extract the maximum solar power through the research of the maximum power point of the PV module [9,10]. In fact, different topologies of the grid connected PV systems have been considered in the literature [11e15]. In terms of isolation, it can be classified into the transformer and the transformless topologies. However, many investigations have shown that the operation with transformer isolation suffers from many disadvantages such as high cost, large size,

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and low efficacy. For these reasons, the topology of the transformless connected PV system is the most required [16e18]. In terms of efficiency, the performances of the grid connected PV systems are deeply depend on the DC/AC inverter efficiency. To increase this later, many topologies of the PV inverter were evolved such as the multilevel inverter which can decrease the total harmonic distortion (THD), the electromagnetic interference, and increase the quality output voltage waveform [19e22]. Conversely, such topologies increase also the cost and the size of the connected PV systems by increasing the number of switching devices of the PV inverter. Unfortunately, this increase can be presented as a handicap to reach a competitive grid connected PV system compared to the conventional electricity distribution, especially with the reduction of the PV panel cost, and the increase of the large-scale PV systems. To overcome these drawbacks, the reduced inverters can be considered as a solution to improve cost-effectiveness and volume-compactness of the DC/AC inverter. Therefore, the reduced semiconductor number minimizes failure rates and maintenance costs. Significant reductions in both switching and conduction losses can be also registered [20,23e26]. All these advantages allow the increase in the reliability with the reduction of the manufacturing cost of the PV inverter. These benefits are usually recommended, especially for a large-scale grid connected PV systems. In the literature, two reduced three phase inverter topologies have been presented: the four-switch inverter and the delta inverter [27e29]. The first structure consists of two legs with two power semiconductor switches per leg. The third phase of the load is connected to the middle point of the DC-bus voltage [25,29]. For the second reduced topology, the delta inverter consists of three leg delta connected. Each leg has only one power switch in series with the third of conventional value of the conventional DC voltage. The delta inverter is the most reduced structure, even the use of only three power switches instead of six in the conventional full bridge DC/AC inverter [30e32]. Both reduced topologies have been considered suitable for motor drive control [28e30,32]. However, the structure of the delta inverter has been limited to battery fed application where the problem of DC voltage is discarded, such as the electric drive [28,32]. In the PV field, the delta inverter can be also implicated since PV panels are inherently independent DC sources. Many researches have been involved the four switch inverter as the three phase PV inverter [33e35]. Obtained results have shown this reduced topology is very promising for PV power applications. Considering the delta inverter, the integration of this reduced topology in the PV field is proposed only by Sandoval et al. [26]. According to this research, two configurations of a grid-connected delta inverter system for

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large-scale PV power systems are discussed: (a) a large-scale grid connected delta inverter with the use of a DC/DC boost for each phase, (b) PV field connected to a flyback converter with high-frequency isolation, followed by a delta inverter system interfaced to the utility grid. Simulation results have confirmed the operation and the feasibility of both configurations under a high-power factor and low THD. In this work, the integration of the delta inverter in the PV field considering the first configuration is also adopted. A proposed control strategy for the grid connected PV system is developed to perform in addition to the main role of the DC/AC conversion power, the control of both reactive and active power, the power factor control, the voltage, and the current regulation. This paper is organized as follows. In the next section, the structure of the PV system and its control are developed. Simulation results of the PV system are presented. The model of the conventional DC/AC inverter connected to the grid as well as its conventional control strategy is explained in Section 3. In Section 4, the model of the grid connected PV system using a delta inverter is presented. To emulate the conventional control strategy operation, a dedicated control strategy for the delta inverter connected to the grid is proposed. Next section provides simulation results of the grid connected delta inverter. In Section 6, some preliminary experimental results of the delta inverter fed three-phase R-L load are presented. Finally, concluding remarks are given.

2. PV system 2.1 Description of the PV system The first stage of the grid connected PV system is composed of a solar PV module and a DC/DC boost converter. This later is used to increase and regulate the output voltage of the PV array and to implement maximum power point tracking (MPPT). The basic power circuit of the DC/DC boost converter is considered. The structure of the PV system and its control is presented in Fig. 3.1.

FIGURE 3.1 Structure of the PV system and its control.

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2.2 Description of the PV panel In this chapter, the model of the PV panel has been done considering one diode model of a PV cell. The electrical equivalent circuit of a PV cell corresponds to a current Iph generator connected in parallel with a diode. Two parasitic resistances are introduced as shown in Fig. 3.2. The basic equations used for modeling the solar cell are adopted as follows [14,15]: I ¼ Iph  Id  IRsh  o  q ðV þ Rs IÞ  1 Id ¼ Is exp AkT

(3.1)

n

IRsh ¼

V þ Rs I Rsh

  S  Iph ¼ ICC þ Kl T  Tref 1000   3

 T qEGO 1 1 Is ¼ Ir exp  Tref Bk Tref T

(3.2) (3.3) (3.4) (3.5)

where l l

l l

l

l l l l

I; V: cell Output Current and voltage, Iph and ICC : photon current and cell short circuit current at STC (Standard Test Conditions), Is : reverse saturation current of the diode, S, T, Tref : irradiation, cell operating temperature and Reference temperature(298 K), k: Boltzmann’s constant (1; 38  1023 J/ K)) and q is the charge of the electron (1; 6  1019 C), Kl : temperature coefficient of the short-circuit current, EGO : Energy forbidden band of the semiconductor, Ir : cell reverse saturation current of PV panel at the temperature Tref , Rsh ; Rs : Intrinsic parallel and series resistance.

FIGURE 3.2 Equivalent circuit of the ideal photovoltaic cell.

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The manufacturers of the PV panels provide only some experimental technical parameters such as the open circuit voltage VOC, short-circuit current ICC, the maximum voltage of the power point Vm, the maximum current of the power point Im, and the maximum power Pm. For this reason, the ideal PV model must be simplified so that it corresponds with the parameters provided by the industry as below: sI Normally, Rsh is between 100 and 10,000U, then VþR can be ignored Rsh with respect to the photon current Iph. For T ¼ Tref and S ¼ 1000W m2 , the Is and Iph current can be equal to: Is ¼ Ir and Iph ¼ Icc

(3.6)

In an open circuit condition, the output current I is equal to zero and the output voltage V is equal to VOC, which translates to rewriting Eq. (3.1) as follows:   q   VOC  1 0 ¼ I ¼ Icc Ir exp (3.7) AkT Then the Is current is expressed following this equation: Is ¼ Ir ¼

I  q cc  VOC  1 exp AkT

(3.8)

2.3 DC/DC boost converter The DC/DC converters provide a variable DC voltage from a fixed input DC voltage. Depending on the structure, it can be step-down (buck) or step-up (boost) and, under certain conditions, return energy to the power supply. In the PV application, a boost DCeDC converter is needed to extract a high voltage value delivered by the PV panel and then the possibility of injecting power into the grid can be achieved. Referring to Fig. 3.1, the main components of this DC/DC boost converter are -

An inductor L to smooth the current, A transistor T which is a controllable power switch, A Diode D: to ensure the continuity of the current in the inductor, Two filter capacitors C1 and C2 placed at the input and the output of the converter.

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This type of converter is based on the charging and discharging of the inductor L. These two phases correspond to the closing and opening of the power switch T. Therefore, there are two operating sequences: ➢ Sequence 1: the power switch T is closed, and the diode D is equivalent to an open circuit. In this case, the inductor is in a charging mode, ➢ Sequence 2: the power switch T is turned OFF. The output stage receives energy from the input source and from the inductor L which is during this sequence in a discharging mode.

2.4 MPPT controls for DC/DC converters In this part, the control of the DC/DC inverter is presented. In fact, this control is based on the research for the maximum power point “MPP” of the PV module which is performed by the control method MPPT. The MPPT command places the PV system at the point of maximum operation Vppm , Ippm whatever the temperature and the irradiation values. In the literature, there are many MPPT command: In this work, the MPPT system based on the “perturb and observe (P&O)” method is adopted, thanks to its simplicity and its low implementation cost when only a voltage sensor is necessary to use [36,37]. The flowchart of the “perturb and observe (P&O)” algorithm is presented in Fig. 3.3, where the MPPT control having as inputs the voltage and current (Ipv and Vpv ) for PV module. Based on this method, the voltage Vpv and current Ipv of the PV module are measured at each cycle in order to calculate the PV power Ppv(n). The value of this Ppv(n) power is compared to the Ppv (n1) value calculated in the previous cycle. The Ppv power increases following a Vpv voltage disturbance, which is repeated until the power decreases. In this case, the direction of the disturbance is reversed to turn to the MPP.

2.5 Simulation results of the PV system The simulation is carried out using MATLAB/Simulink software. The parameters of the PV cell as well as of the DC/DC boost converter are resumed in Tables 3.1 and 3.2. Simulation results of the PV cell are shown in Figs. 3.4e3.7. Fig. 3.4 presents the IeV and the PeV characteristics of the PV cell where MPP corresponds to the maximum power fixed for this panel cell to 174.24 W.

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FIGURE 3.3 Flowchart of the “perturb and observe (P&O)” algorithm.

As it shown also, we confirm that, for an open circuit voltage equal to 44.2V, the current and the power of the PV cell are equal to zero. Fig. 3.5 illustrates the influence of the temperature on the IeV characteristic. As it shown, the increase of the temperature decreases the open circuit voltage. Consequently, the maximum power of the panel is reduced. Fig. 3.6 shows the variation of the power delivered by the photovoltaic panel as a function of the voltage for different temperature values. This figure

78 PART | II Solar photovoltaic energy

TABLE 3.1 PV cell parameters. PV cell parameters

Values

Solar irradiation: E

1000W=m2

Reference solar irradiation: Eref

1000W=m2

PV cell temperature: T

25 degrees

Reference PV cell temperature: Tref

25 degrees

Open circuit voltage: VOC

44.2 V

Short-circuit current: ISC

5.2 A

Voltage at MPP: Vmpp

35.2 V

Current at MPP: Impp

4.95 A

Maximum power: Pm

174.24 W

Serial resistor: Rs

0.217U

TABLE 3.2 DC/DC boost converter parameters. DC/DC boost converter parameters

Values

Capacitors C1¼C2

2200 mF

Inductor L

0.01H

Load resistor

70U

FIGURE 3.4 Characteristics IeV and PeV of the PV cell.

A grid connected PV system based on a reduced delta inverter Chapter | 3

25°C

Current (A)

40°C

79

Voltage (V)

Power (W)

FIGURE 3.5 Influence of the temperature on the IeV characteristic.

40°C

25°C

Voltage (V)

FIGURE 3.6 Influence of the temperature on the PeV characteristic.

confirms the reduction of the power when the increase of the temperature is registered. Fig. 3.7 shows the influence of the solar irradiation value on the IeV and PeV characteristics of the PV cell. The efficiency of a photovoltaic cell depends on the solar irradiation. The greater the irradiation, the higher the efficiency of the cell in terms of current, voltage, and power. Figs. 3.8 and 3.9 show, respectively, the output power of the PV module and the DC output voltage Vout . Referring to Fig. 3.8, it can be noted that the PV module output power reaches the value of 174.24W which is equal to the maximum power of the PV panel. This result confirms the feasibility of the implemented MPPT control.

80 PART | II Solar photovoltaic energy

FIGURE 3.7 Influence of the irradiation on the IeV and PeV characteristics.

FIGURE 3.8 PV module output power.Ppv

FIGURE 3.9 DC output voltage.Vout

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Fig. 3.9 shows that, corresponding to this maximum power, the output voltage of the DC/DC boost converter stabilizes at a DC voltage equal to 100V. This voltage will be considered as a reference DC voltage for the second stage of the grid connected PV system, which is composed essentially on a DC/AC inverter.

3. Modeling of the conventional DC/AC inverter connected to the grid 3.1 Structure In this section, the second stage of the grid connected PV system is developed. This stage is based on the use of a three-phase conventional DC-AC inverter, which contain two IGBTs in each arm. The three arms are connected to threephase grid power through an RL low-pass filter which should remove the highfrequency harmonics of the current line [38e40]. The power circuit of the PV conventional DC/AC inverter connected to the grid is presented in Fig. 3.10.

3.2 Mathematic model of the grid The grid is modeled by three sinusoidal voltages Va, Vb, and Vc, having the same frequency and same RMS voltage equal, respectively, to 50 Hz and 220 V. These three voltages are shifted between them by 120 degrees. Referring to Fig. 3.10, the dynamic model of the grid line currents ia, ib, and ic in the three-phase (abc) frame can be described by the following equations [41,42]: 8 d R 1 > > ia ¼  ia þ ðVa  Van Þ > > > dt L L > > < d R 1 (3.9) ib ¼  ib þ ðVb  Vbn Þ > dt L L > > > > > d R 1 > : ic ¼  ic þ ðVc  Vcn Þ dt L L

FIGURE 3.10 Power circuit of the conventional three phase DC/AC inverter connected to the grid.

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where Van, Vbn, and Vcn are the phase voltages of the inverter. R and L are the filter RL parameters. The active and reactive powers of the grid are determined as follows [42]: P ¼ ReðVabc ðiabc Þ Þ and Q ¼ ImðVabc ðiabc Þ Þ

(3.10)

where 10

0

1

Vabc ðiabc Þ ¼ @va þ vb ej 3 þ vc ej 3 A@ia þ ib ej 3 þ ic ej 3 A 2p

4p

2p

4p

1 ¼ va ia þ vb ib þ vc ic þ j pffiffiffi ðva ðic  ib Þ þ vb ðia  ic Þ þ vc ðib  ia ÞÞ 3 (3.11) Then, the active and reactive powers of the grid can be deducted as follows: 1 P ¼ va ia þ vb ib þ vc ic and Q ¼ pffiffiffi ðva ðic  ib Þ þ vb ðia  ic Þ þ vc ðib  ia ÞÞ 3 (3.12) Applying the Park transformation to Eq. (3.9), the state model describing the dynamic behavior of the grid line currents can be expressed in the referential (d,q) as follows: 8 d R 1 > > < id ¼  id þ wiq þ ðVd  Vdn Þ dt L L (3.13) >d   R 1 > : iq ¼  iq wid þ Vq  Vqn dt L L with id iq , Vd ; Vq ; Vdn and Vqn are, respectively, the direct and quadrature components of the grid line current, the grid voltages, and the phase voltages of the inverter. Then, the active and reactive power in the (d,q) frame can be rewritten as follows [42,43]: 8  3     3  > > ¼ Vd i d þ Vq i q < P ¼ Re Vdq idq 2 2 (3.14)       > > : Q ¼ 3 Im Vdq idq  ¼ 3 Vd id  Vq iq 2 2 Consequently, the input power for the inverter can be expressed as follows:  d 3 Cdc Vdc Vdc ¼ Vd id þ Vq iq dt 2 where Cdc is the DC bus capacitor.

(3.15)

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83

3.3 Conventional control strategy The objectives of the control strategy applied for the conventional inverter connected to the grid are focused on the: ref ➢ Regulation of the DC bus voltage Vdc to a reference voltage Vdc , ➢ Regulation of the reactive current iq injected into the grid to zero by  ¼ 0 , imposing a null reactive current reference (iref q

➢ Unitary power factor (cos(f) ¼ 1).

3.3.1 Reactive current iq regulation To eliminate the reactive power injected to  the grid, the reactive current must be adjusted to null reference

iref q ¼ 0 . For this reason, a control loop

regulation must be developed [41,44]. In fact, according to the second part of Eq. (3.13), a quadrature voltage Viq can be defined as follows:

Where

d R 1 iq ¼  iq þ Viq dt L L

(3.16)

  Viq ¼ Lwid þ Vq  Vqn

(3.17)

Hence, a transfer function can be deducted as descripted above: GðsÞ ¼

iq ðsÞ 1 1 1 ¼  ¼ L Viq ðsÞ ðLs þ RÞ R 1þ s R

(3.18)

Using a PI controller, the control law Viq ; allowing the tracking of iref q ; can i i be obtained as presented in Fig. 3.11, where KP and Ki are the proportional and the integral gains of the quadrature current PI regulator.

FIGURE 3.11 Current control loop of the quadrature current iq .

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The closed loop control system that enables following the reference current iref q is described as follows: Fcl ðsÞ ¼

iq iref q

¼

Fo ðsÞGðsÞ 1 þ Fo ðsÞGðsÞ

(3.19)

where Fo ðsÞ is PI controller transfer function in the form of: Fo ðsÞ ¼ KPi þ

Kii s

(3.20)

The closed loop transfer control system can be expressed as follows:  i  KP s þ Kii  i  KP s þ Kii L (3.21) Fcl ðsÞ ¼ ¼ i ðR þ LsÞs þ KPi s þ Kii K þ R Ki P sþ i s2 þ L L The closed loop transfer system exhibits a typical second-order system with a natural frequency un and a damping ration x calculated as follows: sffiffiffiffiffi 8 i > > un ¼ K i > > > L < (3.22) KPi þ R 1 > > ffiffiffiffiffi r >x ¼ > > 2L : K ii L Consequently, the proportional and integral gains of the quadrature current PI controller can be obtained as: ( i KP ¼ 2xLun  R (3.23) Kii ¼ Lu2n

3.3.2 DC bus voltage V dc regulation The DC bus voltage regulation is achieved through two cascaded linear controllers. The voltage controller is an outer loop, while the direct current loop is an inner loop which determines the reference direct current iref d according to the ref target value of Vdc This loop control is defined by the following equation [44,45]:   1 vdc  ref vdc K iref ¼ K þ (3.24) Vdc  Vdc P I d s where KPvdc and KIvdc are the proportional and integral gains of the DC bus voltage PI regulator.

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85

The current control loop of the direct current is developed considering just the first part of Eq. (3.13) and the same procedure used for the quadrature current control loop is adopted. Referring to Eq. (3.15), and in the case of unity power factor operation, the direct current can be expressed as follows: Vdc ¼

id Cdc s

(3.25)

The cascade control loop is represented in Fig. 3.12. To determine the control parameters for the Vdc voltage, and according to Fig. 3.12, the loop transfer function can be written as follows: Vdc ref Vdc

¼

1 Cdc

ðKPvdc s þ Kivdc Þ K vdc K vdc s2 þ P s þ i Cdc Cdc

(3.26)

The natural frequency un and the damping ration x can be expressed as follows: sffiffiffiffiffiffiffiffi 8 K vi dc > > u ¼ > n > > Cdc < (3.27) vdc KP 1 > > ffiffiffiffiffiffiffiffi r x ¼ > > > 2Cdc K vi dc : Cdc Therefore, the proportional and integral gains of the DC bus voltage PI controller can be calculated as above: ( vdc KP ¼ 2xCdc un (3.28) Kivdc ¼ u2n Cdc Based on both current control loops, Vid and Viq voltages can be produced. Then, considering Eq. (3.15) and its similar for the direct components, the Vdn and Vqn voltages can be generated. Finally, these voltages are transformed into the three-phase (abc) frame using the Park inverse transformation.

FIGURE 3.12 The cascade control loop of the DC bus voltage Vdc .

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Fig. 3.13 shows the block diagram of the developed control applied to the conventional inverter connected to the grid. The voltage and current measurements are installed in the electrical network for measuring the Vabc threephase voltages and the iabc three-phase grid currents. The voltage regulation of the DC bus and reactive current are performed by the developed PI controllers. The regulation of the Vdc voltage loop is used by two cascaded loops for controlling the reference current iref d . The regulation of reactive current iq is performed by imposing a null reactive current reference iref q ¼ 0. The control signals of the three IGBTs constituting the inverter are generated using the conventional SPWM technique.

4. Modeling of the delta inverter connected to the grid 4.1 Structure of the delta inverter The delta inverter is a three-phase DC-AC inverter which uses only three power switches instead of six in the case of a conventional three-phase one. This reduction in the number of switching devices contributes to a higher power density for the energy conversion of PV systems, with an increase of the reliability, lifetime of the inverter. The proposed architecture is a delta-shaped inverter. It consists of three arms containing each a continuous voltage source equal to the third of the

FIGURE 3.13 Block diagram of the conventional control strategy.

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87

conventional DC bus voltage V3c in serial with an IGBT with an antiparallel connected diode. The summit of the three delta connected arms is used to supply the three output phases [28,30,32]. Fig. 3.14 shows the topology of the delta inverter connected to the three phases load [27,31]. The delta inverter proposed for PV applications has the advantage of using three powers switches which results in the use of fewer components in the entire system. This leads to greater reliability by reducing the number of power devices. Then, a long life of the inverter and low maintenance cost can be obtained.

4.2 Photovoltaic delta inverter configuration The disadvantage of the delta inverter is the requirement of the use of three DC sources input voltages. This disadvantage does not affect some applications especially in large PV installations. The PV delta inverter employs three DC voltages sources which consist of a series-parallel combination of PV solar modules [26]. To work properly with sinusoidal voltages, it is necessary that only two switches must be closed at any particular moment. If the three switches are closed, there will be a short circuit across the source of continuous voltage. If only two switches are closed, there are three possible states, which are shown in Fig. 3.15. In all cycles, the sum of the three switching functions is always equal to 2 [28]. The output phase to phase voltages that are generated in each of the different states are given in Table 3.3. In each state, the sum of the three voltages is equal to zero and the output phase to phase voltage is balanced between 2V3 c and V3c .

K2 K1

K3 Delta inverter

Load

FIGURE 3.14 Delta inverter connected to the load.

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FIGURE 3.15 The three possible states of delta inverter operation.

TABLE 3.3 Output phase to phase voltages for the three switching states. State

Vab

Vbc

Vca

1

2 V3c

V3c

V3c

2

V3c

2 V3c

V3c

3

V3c

V3c

2 V3c

4.3 Photovoltaic delta inverter connected to the grid The delta inverter proposed for the PV system connected to the grid uses as a DC source the boost DCeDC converter for each phase that tracks the MPPT. The three power switches (K1, K2, K3) are controlled by the SPWM control signals. The output of the inverter is connected to an RL filter which is connected to three-phase of the grid as shown in Fig. 3.16.

4.4 Dedicated control strategy for the photovoltaic delta inverter connected to the grid The objectives of the dedicated control strategy for the delta inverter are the same of the conventional control one. Then, this proposed control strategy will be developed as an emulation to the functionality of the conventional strategy. However, compared to this later, the unconventional topology of this reduced inverter forced the creation of some different blocks such as the development of the control loop for each of the three DC bus voltage of the delta inverter as well as some difference in the SPWM control technique.

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89

FIGURE 3.16 Photovoltaic delta inverter connected to the grid.

4.4.1 DC bus voltage regulation This control loop is used to regulate the voltages of the three DC continuous buses of the delta inverter. In addition, it determines the reference current iref d and iref q according to the regulated currents of DC voltage regulation loops. One of the particularities of the delta inverter is that each IGBT can feed two phases. For this reason, the regulation of the currents will be more robust by the regulation of the current arms. i1;2;3 : The three DC voltages control loops are determined by the following three equations:   8 1 vdca  ref ref vdca > i K ¼ K þ Vdca  Vdca > 1 P I > S > > > >  <  1 vdcb  ref ref vdcb i2 ¼ KP þ KI (3.29) Vdcb  Vdcb > S > > >   >  > > : iref ¼ K vdcc þ 1K vdcc V ref  V dcc P I 3 dcc S Unlike the conventional DC bus voltage control loop, in the case of the delta inverter, this control loop is achieved with only one linear controller based on this system:

90 PART | II Solar photovoltaic energy

8 3 > > > Vdca ¼ i1 > > Cdc s > > > < 3 i2 Vdcb ¼ > C dc s > > > > > 3 > > i3 : Vdcc ¼ Cdc s

(3.30)

With the same calculation applied for Eq. (3.29), the control loop parameters for each DC bus regulator are the same and equal to: 8 2 vdc a vdc b vdc c > > < KP ¼ KP ¼ KP ¼ xCdc un 3 (3.31) > vdca > : Ki ¼ Kivdcb ¼ Kivdcc ¼ 1u2n Cdc 3 The three reference phase currents iref a;b;c are generated from the three reference currents arms iref 1;2;3 as given by the following equations: 8  1  ref > ref ref > i ¼  i i > 2 a > > 3 1 > > <   1 ref iref ¼ i2  iref 3 b > 3 > > >   > > > iref ¼ 1 iref  iref : 3 1 c 3

(3.32)

Finally, to find the references currents iref d in the (dq) referential, it must be applying the Park transformation to the three reference phase currents iref a;b;c determined from the control loop of DC voltages. The reactive reference   current is usually adjusted to null reference iref q ¼0 .

4.4.2 Reactive current control The same procedure adopted in the development of the conventional current loop regulator is considered. Based on currents coupling terms wiq ,  wid and the grid voltages in the (d,q) frame, the PI regulators perform the tracking of ref the currents references iref d and iq . Then, the Vdn and Vqn control law can be determined as follows:   8 1 i  ref i > V K ¼ Lwi þ V L K þ id  id > q d P I < dn S (3.33)    > > : Vqn ¼ Lwid þ Vq L K i þ 1K i iref  iq P q S I

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91

4.4.3 SPWM control technique applied to the delta inverter As it shown previously, the sum of the three binary states of the switches is equal to two must be satisfied at all times. In fact, there is two SPWM commands developed for the delta inverter giving balanced three-phase currents and voltages: the SPWM proposed by Sandoval et al. [26] and the own proposed SPWM strategy dedicated to the delta inverter. The principle of each strategy is presented as below: 4.4.3.1 Sandoval SPWM strategy for the delta inverter The principle of the Sandoval sinusoidal pulse width modulation SPWM strategy is based on a comparison between a triangular carrier and a modulated sinusoidal signal to generate the PWM signal of the switch. This technique is applied only when the switch is ON. The sum of the produced PWM signal of the switch K1 and the NAND logic function of PWMs signals produced by the switch K2 and K3 generate the control signal “S1” of the IGBT “K1.” This method ensures that only two switches must be closed during each cycle. The same procedure is developed to generate the control signal “S2” and “S3” of the IGBTs, respectively, “K2” and “K3.” The objective of this SPWM technique is to ensure that two switches of the inverter are ON at all times by applying the second control strategy detailed in the third section. To generate the reference voltages Va , Vb , and Vc , the control law voltages Vdn and Vqn determined in Eq. (3.33) are transformed in the (abc) frame by applying the park inverse transformation. The reference voltages Va , Vb , and Vc are compared to triangular waves. Finally, the logic function NAND is applied to insure that at any time one of the three switches of the inverter is OFF. 4.4.3.2 Own proposed SPWM strategy for the delta inverter The principle of the own proposed sinusoidal modulation technique dedicated to the reduced delta inverter is based on the regeneration of these gate signals of the three power switches consisting the inverter from a comparison between a triangular carrier and the modulating functions [46]. The expressions of the modulating functions are different from one sector to another. In fact, referring to Table 3.3, the three states can provide three active vectors (V 1 , V 2 , and V 3 ) as it shown in Table 3.4. The representation of these three vectors subdivide the (a, b) plane into three sectors equally shifted by 2p/3 as presented in Fig. 3.17. The control signals waveforms of the three power switches in each sector under this proposed SPWM algorithm are inspired from those developed already in a proposed SVPWM control approach for the same reduced

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TABLE 3.4 Phase to neutral and phase to phase voltages of the three states and their corresponding active vectors. K1 K2 K3

Van

Vbn

Vcn

Vab

Vbc

Vca

Va

Vb

Vi

101

Vc 3

V3c

0

2Vc 3

V3c

V3c

Vc 3

V1

110

0

Vc 3

V3c

V3c

2Vc 3

V3c

0

011

V3c

0

Vc 3

V3c

V3c

V3c

V3c

 Vpcffiffi 3 3 2V pcffiffi 3 3 3Vpcffiffi3

V2 V3

FIGURE 3.17 Representation of the three generated active vectors of the delta inverter in the (a, b) plane.

inverter [47]. The expressions of the modulating functions for each power switch can be summarized in Table 3.5. 4.4.3.3 Comparative study between the two SPWM strategies To compare the performances of the two SPWM strategies dedicated to the delta inverter, some preliminary simulation results are registered. Fig. 3.18 presents the three phase currents of the R-L load as well as their THD under each SPWM algorithm. Referring to this figure, an unbalanced and distorted current waveform considering the SPWM algorithm proposed by Sandoval et al are registered compared to a perfect sinusoidal one when the new SPWM method is applied. These results are reflected, as it shown in Fig. 3.18 (b), on the current THD rate which is equal to 8.99% for the SPWM proposed by Sandoval et al. and it is reduced to 1.74% by considering the proposed SPWM, with almost the same maximum amplitude of the fundamental current.

Sector1

Sector2

Sector3

Power switch S1 MOD1

2 3

MOD2

1

 m 34 cosq þ m

pffiffi 3 4 sinq

1 3

 m 34 cosq  m pffiffi 2  m 3 sinq 2 3

pffiffi 3 4 sinq

0 pffiffi 3 4 sinq

1 3

þ m 34 cosq  m

1 3

  pffiffi m 34 cos q 2p m 43 sin q 2p 3 3

2 3

m

2 3

  pffiffi 3 2p m 34 cos q þ2p sin q þ þ m 4 3 3

Power switch S2 MOD1 MOD2

0

2 3

1 3

  pffiffi 3 2p þ m 34 cos q 2p sin q  m 4 3 3

1

1 3

  pffiffi 3 2p m 34 cos q þ2p sin q þ m 4 3 3

0

2 3

m

  pffiffi m 34 cos q 2p þ m 43 sin q 2p 3 3



pffiffi 3 2 sin

q 2p 3



Power switch S3 MOD1 MOD2



pffiffi 3 2 sin

q þ2p 3

1 3

  pffiffi þ m 34 cos q þ2p m 43 sin q þ2p 3 3

1

A grid connected PV system based on a reduced delta inverter Chapter | 3

TABLE 3.5 Expressions of the modulating functions during each sector.

93

94 PART | II Solar photovoltaic energy

FIGURE 3.18 Simulation results of the load currents and their THD using the own proposed SPWM algorithm (Subscript “1”) and Sandoval SPWM algorithm (Subscript “2”). Legend: (A) load currents and (B) current THD.

This comparative study proves the greater performances of the own proposed SPWM technique. For this reason, the own proposed strategy will be considered for the PV application where the delta inverter will be connected to the grid. The block diagram of the dedicated control strategy for the delta inverter connected to the grid is presented in Fig. 3.19.

5. Simulation results The simulation parameters used to test the control laws of the delta inverter connected to the electrical network are resumed in Table 3.6. The DC bus voltage Vdc of each arm of the delta inverter is controlled ref that is equal to V3c ¼ 100 V as shown in perfectly to the reference value Vdc Fig. 3.20. It is to be noted that this DC bus voltage regulation is applied to each voltage arm, and the same results are registered on the output of the three DC regulation blocks.

A grid connected PV system based on a reduced delta inverter Chapter | 3

95

FIGURE 3.19 Block diagram of the dedicated control strategy.

TABLE 3.6 Simulation parameters. Simulation parameters

Values

RMS network voltage Reference DC bus voltage

220 V ref Vdc

100 V

DC bus capacitor Cdc ¼ C2

2200 mF

Switching frequency

5 Khz

Filter inductor: L

75 mH

Filter resistance: R

0.4 U

Current regulator parameter:

KPi

500

Current regulator parameter:

KIi

1000

Voltage regulator parameter:

KIvdc

10

Voltage regulator parameter:

KPvdc

100

Power PV panels Ppv

174.24W

Fig. 3.21 shows the active and reactive power of this model. As it shown in this figure, the active power Pa is equal to the PV panel reference Ppv and the reactive power is regulated to zero. This regulation is necessary for the grid connection systems where only the active power is transmitted.

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Vdc (V)

100 80 60 40 20 0 0

0.1

0.2

0.3 T (s)

0.4

0.5

0.6

FIGURE 3.20 DC bus voltage.Vdc

250

Active power Pa Reactive power Q

Pa (W) , Q (VAR)

200 150 100 50 0 -50 -100 0

0.1

0.2

0.3 T(s)

0.4

0.5

0.6

FIGURE 3.21 Active and reactive power (Pa and Q).

Fig. 3.22 shows the nulls reactive current iq in the two cases of grid connected to delta inverter and the conventional one. As it is shown, the main goal of this regulation is achieved. Also, it is to be noted that compared to conventional structure of the inverter, the delta inverter can be considered as a reduced structure which can reach the performances and the functionality of the classic PV one with the reduction of the number of the power switches to the half. It is to be noted that the regulation of the power in the converter must be extended to the study of the quality of the current injected to the grid. For this reason, the waveforms and the THD of the current for each inverter have been cheeked.

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97

3

2

iq(A)

1

0

-1

-2

-3 0

0.1

0.2

0.3 T (s)

0.4

0.5

0.6

(a)

(b) FIGURE 3.22 Reactive current iq injected into the grid connected to: (A) the delta inverter and (B) the conventional inverter.

Fig. 3.23 shows that the current ia and the output voltage Va of the grid are in phase in the two cases. This means that the DC-AC converter operates with unity power factor (cos(f) ¼ 1), and then the reactive power consumed is equal to zero. Based on the FFT analysis of the supply current waveforms in the grid connected to the delta inverter and the conventional inverter presented, respectively, in Figs. 3.24 and 3.25, the rate of harmonics current using delta inverter is equal to 1.12%, which is accepted for a grid connection (less than 5%). However, compared to the conventional one, the delta inverter represents lower fundamental current amplitude. Referring to these results, the conventional inverter presents the greater performances. But in terms of cost-effectiveness and compactness, which considered as an important parameter especially for the large-scale production of the PV systems, the structure of the reduced inverter presents a solution and a good candidate for this kind of installation.

98 PART | II Solar photovoltaic energy 30 ia Va/10

Va/10 (V), ia(A)

20 10 0 -10 -20 -30 0.2

0.22

0.24

0.26

0.28

0.3

T (s)

(a) 30 Va/10 ia

Va/10 (V), ia (A)

20

10

0

-10

-20

-30 0,2

0,22

0,24

0,26

0,28

0.3 0,3

T (s)

(b) FIGURE 3.23 Va voltage and ia current of the phase (A) into the grid connected to: (a) the delta inverter and (b) the conventional inverter.

In fact, the quality of the current provided by the reduced inverter, even if it is less efficient to those offered by of the conventional one, it is considered reliable and it respects the conditions to a grid connection.

6. Experimental results An experimental test bench built around a laboratory prototype of the delta inverter using MOSFET transistors IRF460 is developed. The three DC voltage supplies were used as three batteries voltages equal in each arm to 12 V. To verify the operation of this reduced topology, some preliminary tests

A grid connected PV system based on a reduced delta inverter Chapter | 3

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Fondamental (50 Hz) = 8.54, THD = 1.12%

8

7

Ia (A)

6

5

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2

1

0

2

4

6

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14

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18

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Order of Harmonic

FIGURE 3.24 Harmonics distribution of the grid current of the phase (A) connected to the delta inverter.

Fundamental (50 Hz) = 9.1, THD= 0.7% 9

8

7

Ia (A)

6

5

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0

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FIGURE 3.25 Harmonics distribution of the grid current of the phase (A) connected to the conventional inverter.

of the delta inverter under the SPWM strategy have been realized. In this case, the inverter is feeding a three-phase R-L load (2U-10mH). The switching frequency is fixed to 5 kHz, and the output frequency is equal to 50 Hz. The own proposed SPWM control technique applied to the

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delta inverter is implemented on the DSP TMS320F28335 from Texas Instruments. The microcontroller is managed by an environment called: “Code Composer Studio” which allows the program to be entered in “C” language. The process of generating and implementing ANSI C/C þþ runtime code from the MATLB Simulink program is developed by the Simulink coder. An Embedded Coder is used to optimize and customize the code generated by MATLAB Coder and Simulink Coder for use in production. After compiling the program, it is subsequently implemented on the DSP. The process of generating and implementing runtime code from the Simulink model is shown in Fig. 3.26. The program developed for the generation of the control signals of the three switches constituting the delta inverter is essentially based on ePWM blocks, as shown in Fig. 3.27. A photo of the experimental test bench is represented in Fig. 3.28. Fig. 3.29 shows the three-phase currents iabc of the R-L load. Referring to this figure, a sinusoidal waveform of these currents with a maximum amplitude and a fundamental frequency equal, respectively, to 1.2A and 50Hz is registered. Figs. 3.30 and 3.31 show, respectively, the phase to phase and the phase to neutral output voltages and their zoom. Based on Fig. 3.18, for example,  when the phase to phase output voltage Vab (first waveform) is equal to 24V 2 V3c ;  the others phase to phase voltages Vbc and Vca are equal both to 12V V3c which confirm the theoretical study resumed in Table 3.3. As concern the phase to neutral voltage, it can be seen that,  when the phase voltage Van (first waveform) is modulated between 12V

Vc 3

and zero, the

Matlab/Simulink diagram

Simulink embedded coder

Code composer studio

DSP TMS320F28335 FIGURE 3.26 Simulink model runtime code generation and implementation process.

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FIGURE 3.27 Diagram of the SPWM generated by code composer studio environment.

 phase voltage Vbn is varying, respectively, between 12V

V3c

while the

third phase voltage satisfy at each time that the sum of the three-phase output voltage is equal to zero.

FIGURE 3.28 The developed test bench of the delta inverter feeding an RL load.

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FIGURE 3.29 Waveforms of the R-L load currents iabc

FIGURE 3.30

Waveforms of the phase-to-phase output voltage Vab, Vbc and Vca and their zoom.

FIGURE 3.31 Waveforms of the phase to neutral output voltage Van, Vbn and Vcn and their zoom.

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7. Conclusion In this paper, a PV system connected to the grid based on a reduced PV inverter was developed. This reduced inverter called “delta inverter” or “Three Switch three Phase inverter (TSTPI)” consists of three legs delta connected. Each leg contains only one power switch in series with the PV panel. The summit of the delta inverter is connected to the grid. Thanks to this reduced structure, the cost of the PV inverter can be reduced to the half. This reduction is deeply interesting especially for the large PV installation system. Before the development of the dedicated control of the PV delta inverter connected to the electric network, the development of the conventional control one is treated. The dedicated control of the TSTPI has allowed the regulation of the three DC bus voltages as well as the reactive current injected to the grid. The different loops controller was developed. An SPWM control strategy was applied to the delta inverter. Simulation results have clearly registered the three sinusoidal balanced outputs phases and currents with unity power factor. These improve the high performances of the PV delta inverter connected to the grid under the dedicated control strategy. Finally, a laboratory prototype of the delta inverter feeding an R-L load is built. Some preliminary experimental tests carried out using this prototype under the SPWM strategy and implemented on a DSP TMS320F28335 are presented.

References [1]

[2] [3] [4] [5] [6] [7]

[8]

A. Chauhan, R.P. Saini, A review on Integrated Renewable Energy System based power generation for stand-alone applications configurations storage options sizing methodologies and control, Renew. Sustain. Energy Rev. 38 (2014) 99. PVPS, IEA, Pvps ReporteA Snapshot of Global Pve1992-2012, 2013. Report IEA-PVPS T1-22. 2013. V. Devabhaktuni, M. Alam, S.R. Depuru, R.C. Green, D. Nims, C. Near, Solar energy: trends and enabling technologies, Renew. Sustain. Energy Rev. 19 (2013) 555. V.V.S. Eftekharnejad, G. Heydt, Impact of increased penetration of photovoltaic generation on power systems, IEEE Trans. Power Syst. 28 (2013) 893. P. Mohanty, T. Muneer, M. Kolhe (Eds.), Solar Photovoltaic System Applications: A Guidebook for Off-Grid Electrification, Springer, 2015. I. Patrao, G. Garcera´, E. Figueres, et al., Grid-tie inverter topology with maximum power extraction from two photovoltaic arrays, IET Renew. Power Gener. 8 (2014) 638. A.Y. Mohammed, F.I. Mohammed, M.Y. Ibrahim, Grid connected photovoltaic system, in: 2017 International Conference on Communication, Control, Computing and Electronics Engineering (ICCCCEE), IEEE, 2017, pp. 1e5. K.N. Nwaigwe, P. Mutabilwa, E. Dintwa, An Overview of Solar Power (PV Systems) Integration into Electricity Grids, Materials Science for Energy Technologies, 2019.

104 PART | II Solar photovoltaic energy [9] L. Shaowu, L. Honghua, Y. Hailing, et al., A MPPT strategy with variable weather parameters through analyzing the effect of the DC/DC converter to the MPP of PV system, Sol. Energy 144 (2017) 175. [10] V. Sumathi, R. Jayapragash, A. Bakshi, P.K. Akella, Solar tracking methods to maximize PV system outputeA review of the methods adopted in recent decade, Renew. Sustain. Energy Rev. 74 (2017) 130. [11] S. Kouro, J. I Leon, D. Vinnikov, et al., Grid-connected photovoltaic systems: an overview of recent research and emerging PV converter technology, IEEE Ind. Electron. Mag. 9 (2015) 47. [12] D.M. Tobnaghi, A review on impacts of grid-connected PV system on distribution network, Int. J. Electr. Comput. Eng. 10 (2016). [13] S. Saridakis, E. Koutroulis, F. Blaabjerg, Optimal design of modern transformerless PV inverter topologies, IEEE Trans. Energy Convers. 28 (2013) 394. [14] E. Romero-Cadaval, G. Spagnuolo, L.G. Franquelo, C.A. Ramos-Paja, T. Suntio, W.M. Xiao, Grid-connected photovoltaic generation plants: components and operation, IEEE Ind. Electron. Mag. 7 (2013) 6. [15] M. Kasper, D. Bortis, J.W. Kolar, Classification and comparative evaluation of PV panelintegrated DCeDC converter concepts, IEEE Trans. Power Electron. 29 (2014) 2511. [16] B. Yang, W. Li, Y. Gu, et al., Improved transformerless inverter with common-mode leakage current elimination for a photovoltaic grid-connected power system, IEEE Trans. Power Electron. 27 (2011) 752. [17] Y. Tang, W. Yao, P.C. Loh, Highly reliable transformerless photovoltaic inverters with leakage current and pulsating power elimination, IEEE Trans. Ind. Electron. 63 (2016) 1016. [18] X. Guo, Y. Yang, T. Zhu, ESI: a novel three-phase inverter with leakage current attenuation for transformerless PV systems, IEEE Trans. Ind. Electron. 65 (2018) 2967. [19] G. Akalya, K. Aswini, K. Nandhini, et al., Modelling and analysis of multilevel inverter for photovoltaic system, Int. J. Adv. Res. Methodol. Eng. Technol. 1 (2017) 36. [20] S.R. Nandhini, G. Akalya, K. Aswini, et al., A new topology of H-bridge based multilevel inverter for PV system with reduced switches, Int. J. Emerg. Trends Eng. Res. 5 (2017) 60. [21] G.V. Krishnan, M.V. Rajkumar, C. Hemalatha, Modeling and simulation of 13-level cascaded hybrid multilevel inverter with less number of switches, Int. J. Innovat. Stud. Sci. Eng. Technol. 2 (2016) 43. [22] A.M. Noman, A.A. Al-Shamma’a., K. E Addoweesh, et al., A survey on two level and cascaded multilevel inverter topologies for grid connected PV system, in: IECON 2017-43rd Annual Conference of the IEEE Industrial Electronics Society, IEEE, 2017, pp. 2369e2376. [23] M.K. Das, K. C Jana, A. Sinha, Performance evaluation of an asymmetrical reduced switched multi-level inverter for a grid-connected PV system, IET Renew. Power Gener. 12 (2017) 252. [24] I. Sefa, H. Komurcugil, S. Demirbas, et al., Three-phase three-level inverter with reduced number of switches for stand-alone PV systems, in: 2017 IEEE 6th International Conference on Renewable Energy Research and Applications (ICRERA), IEEE, 2017, pp. 1119e1124. [25] M. Salimi, Low-cost grid connected photovoltaic System, in: International Conference on Environmental Science and Technology, 2011 v1-141. [26] J.J. Sandoval, J. Ramos-Ruiz, M. Daniel, S. Essakiappan, P. Enjeti, A new delta inverter system for grid integration of large scale photovoltaic power plants, in: IEEE Applied Power Electronics Conference and Exposition APEC 2014, 2014, pp. 1255e1262.

A grid connected PV system based on a reduced delta inverter Chapter | 3 [27]

[28]

[29]

[30]

[31] [32] [33] [34] [35]

[36]

[37]

[38]

[39]

[40]

[41]

[42]

[43]

105

B. Elbadsi, A. Ben Rhouma, A. Driss, A. Guermazi, A. Masmoudi, On the potentialities of reduced structure inverters integrated in automotive electric motor drives, in: Advanced Electromechanical Motion Systems and Electric Drives Joint Symposium, ELECTROMOTION, 8th International Symposium on, IEEE, 2009, pp. 1e6. A. Alouane, A. Ben Rhouma, M.H.A. Khedher, Efficient FPGA-based real-time implementation of an SVPWM algorithm for a delta inverter, IET Power Electron. 11 (2018) 1611. A. Ouarda, B. El Badsi, A. Masmoudi, Direct RFOC strategies aimed to symmetrical twophase IM drives: comparison between B4-and B6-inverters in the stator, IEEE Trans. Power Electron. 33 (2018) 9772. A. Alouane, A. Ben Rhouma, A. Khedher, FPGA implementation of a new DTC strategy dedicated to delta inverter-fed BLDC motor drives, Elec. Power Compon. Syst. 45 (2018) 688. A.M. Elantably, A. Ben Rhouma, A. Masmoudi, A. Holmes, Control device for driving a brushless DC motor, US Patent (2010), 7643733. A.M. Trzynadlowski, S. Legowsksi, Characteristics of the delta inverter with vector pulse width modulation, Int. J. Electron. 76 (1994) 1205. Y. Huang, M. Shen, F.Z. Peng, et al., Z-source inverter for residential photovoltaic systems, IEEE Trans. Power Electron. 21 (2006) 1776. M.S. Diab, A. Elserougi, A.M. Massoud, et al., A four-switch three-phase SEPIC-based inverter, IEEE Trans. Power Electron. 30 (2014) 4891. S. Dasgupta, S.N. Mohan, S.K. Sahoo, et al., Application of four-switch-based three-phase grid-connected inverter to connect renewable energy source to a generalized unbalanced microgrid system, IEEE Trans. Ind. Electron. 60 (2012) 1215. A. Loukriz, M. Haddadi, S. Messalti, Simulation and experimental design of a new advanced variable step size Incremental Conductance MPPT algorithm for PV systems, ISA Trans. 62 (2016) 30. C. Hemalatha, M.V. Rajkumar, G.V. Krishnan, Simulation and Analysis for MPPT Control with Modified firefly algorithm for photovoltaic system, Int. J. Innovat. Stud. Sci. Eng. Technol. 2 (2016) 48. M.G. Villalva, M.F. Espindola, T.G.D. Siqueira, E. Ruppert, Modeling and control of a three-phase isolated grid-connected converter for photovoltaic applications, Sba Controle Automac¸a˜o Sociedade Brasileira Autom. 22 (2011) 215. A. Hintz, U.R. Prasanna, K. Rajashekara, Comparative study of the three-phase gridconnected inverter sharing unbalanced three-phase and/or single-phase systems, IEEE Trans. Ind. Appl. 52 (2016) 5156. S. Wodyk, G. Iwanski, Control of three-phase power electronic converter with power controllers in stationary frame, in: Fourteenth International Conference on Ecological Vehicles and Renewable Energies (EVER) vols. 1e7, IEEE, 2019. F.E. Lahouar, J.B.H. Slama, M. Hamouda, F. Mustapha, Comparative study between two and three-level topologies of grid connected photovoltaic converters, in: 2014 5th International Renewable Energy Congress (IREC) vols. 1e6, IEEE, 2014. S. Dhar, P.K.A. Dash, A new backstepping finite time sliding mode control of grid connected PV system using multivariable dynamic VSC model, Int. J. Electr. Power Energy Syst. 82 (2016) 314. R.K. Varma, E.M. Siavashi, PV-STATCOM: a new smart inverter for voltage control in distribution systems, IEEE Trans. Sustain. Energy 9 (2018) 1681.

106 PART | II Solar photovoltaic energy [44] S. Haghbin, Integrated Motor Drives and Battery Chargers for Electric or Plug-In Hybrid Electric Vehicles, Chalmers University of Technology, 2013. [45] H. Choi, M. Ciobotaru, M. Jang, V.G. Agelidis, Performance of medium-voltage DC-bus PV system architecture utilizing high-gain DCeDC converter, IEEE Trans. Sustain. Energy 6 (2015) 464. [46] A. Ben Rhouma, M. Hamouda, DSP implementation of a novel SPWM algorithm dedicated to the delta inverter, in: 20th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), IEEE, 2020, pp. 195e200. [47] A. Alouane, A. Ben Rhouma, M. Hamouda, A. Khedher, Efficient FPGA-based real-time implementation of an SVPWM algorithm for a delta inverter, IET Power Electron. 11 (9) (2018) 1611e1619. August.

Chapter 4

An experimental test bench for emulating the standard characteristics of photovoltaic (PV) systems Intissar Moussa and Adel Khedher Universite´ de Sousse, Ecole Nationale d’Inge´nieurs de Sousse, LATIS- Laboratory of Advanced Technology and Intelligent Systems, Sousse, Tunisie

1. Introduction According to recent scientific researches [1e3], the intensive use of renewable energy sources (RES) is due to the global growth demand for conventional energy, the fossil fuel resources finite reserves, and the ever-increasing impact of energy technologies on the environment. RES can be defined as “energy flows which are regenerated at the same rate as they are used” or as “energy obtained from the continuous currents on energy recurring in the natural environment,” produced from solar radiation which can be converted directly or indirectly into energy using various technologies. Thanks to the allocation simplicity, the high reliability, the low maintenance, and lack of noise and the manufacturing-technology scale improvements and economies, photovoltaic (PV) generation is playing a crucial role as a solar-based RES application. A photovoltaic system (PVS) can be installed as a stand-alone system or as a grid-connected generator [4]. A stand-alone system, frequently used in low power scale, requires a battery bank for storing the energy obtained from the PV generator. A grid-connected PV system, frequently used in high power application, does not require the integration of battery energy storage system [5]. Hence, depending on materials and structure development, the 39 main goal consists always of the extraction of maximum power with minimum cost. For PV systems, field tests are developed to ensure and to guarantee the final product quality performance. However, this method is expensive and time consuming. It presents some risks, such as the PV modules direct use for

Renewable Energy Production and Distribution. https://doi.org/10.1016/B978-0-323-91892-3.00011-X Copyright © 2022 Elsevier Inc. All rights reserved.

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prototype testing can damage the source. In addition, the major drawback associated with PV source is the stochastic and unpredictable weather behavior. Even if it is considered as a part of a new technology for generating electricity, it affects the efficiency of the PV panel, the efficiency of the static power converter and its control, and the efficiency of the maximum power point tracking (MPPT) algorithm [6,7]. Consequently, the development of a real-time PV emulator (PVE) is fully recommended in laboratory in the first phase of experimentation in order to improve the PV systems behavior and to extend their life time by reproducing their output characteristics [8e10]. Meanwhile, giving an accurate forecasting of the PV outputs behavior has been always a real issue related to their nonlinearity. Two operating modes must be considered in PV emulation, namely, the static mode 50 in which the obtained model is characterized and validated for fixed atmospheric conditions, and the dynamic one 51 where the validation is carried out using variable weather conditions. A wide range of PV emulators have been investigated, proposed, and carried out by researchers during last decades [11e13]. It could be classified according to the controller type such as static, semidynamic, or dynamic one [14]. Moreover, some emulators are based on structures with low-frequency transformer or high-frequency transformer, without galvanic isolation. These emulators have been controlled by pulse width modulation (PWM) technique to avoid electro-magnetic compatibility interferences. Power converters like buck, boost, and SEPIC-based emulator design are also proved to be robust, reliable, and efficient method for their suitability for emulating IeV and PeV curves with convenience: a discrete values table is previously stored in a memory and the points can be interpolated using mathematical models of curves [15]. PV cell is considered the most important component that affects the simulation accuracy and directly depends on the technology. Since the efficiency of a PV 61 system is mainly influenced by the PV cell, the PV emulator should also take into account the diode approximation techniques for representing the corresponding PV model equivalent circuits [16]. This chapter deals with the study, development, and implementation of PV emulator which is controlled in real time using FPGA board. Thus, a general overview including the recent topologies, technologies, and types of PV system has been presented. Modeling and analysis of PV cell/module are detailed by a judicious choice of equivalent electrical circuits as well as mathematical equations. Two models are considered, namely, the one-diode model and the two-diode model. For these models, a numerical simulation using Xilinx System Generator (XSG) tools to illustrate the global performance of the closed-loop PV emulator is performed. In order to test the robustness of such architectures, the phenomenon of partial shading is introduced for both models. Implementation results of the PV emulator control are validated by a cosimulation. A test bench based on the proposed PV simulator, the buck converter, and the FPGA board has been installed in laboratory. Experimental validation is subsequently presented.

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2. PVS general overview PV energy is the energy produced by converting photonic energy directly into electrical one through PV cells, which are sensors designed by sensitive materials at visible wavelengths. Their association in series and/or in parallel, as depicted in Fig. 4.1, constitutes a PVS characterized by two nonlinear static curves IeV and PeV. For load variation from open circuit to short circuit, process, a maximum power point (MPP) depending on temperature and irradiation is recorded.

FIGURE 4.1 Association of PV cells: (A) series connection (SC), (B) parallel connection (PC), (C) mixed series/parallel connection (SPC).

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FIGURE 4.2 PV panel configuration structures: (A) TCT, (B) BL, (C) HeC. These connections types constitute the basis of the studies carried out on the PV systems.

Other interconnection structures, as mentioned in Fig. 4.2, are also developed in several research studies [17], namely, the total cross tied (TCT) connection, bridge link (BL) connection, and the honey-comb connection (HeC). All these structures output characteristics have been analyzed and discussed through simulation and validated by experiment [18].

2.1 PV cells technologies PV cells are capable of transforming photonic energy into electrical energy, which are able to operate durably in outdoor conditions. This conversion efficiency measurement is normalized in order to compare the different existing PV cell technologies. Three technology generations are used in the solar cells production. The first is reserved for crystalline silicon cells, while the second contains thin film and amorphous silicon cells. The third generation includes concentrated PV cells, dye-sensitized solar cells, and organic PV cells and perovskite cells. Regardless of the generation type, the PV components must have the following characteristics: (i) low price, (ii) high efficiency, (iii) long life span, (iv) no material supply constraints, (v) prospects for further cost reduction.

2.1.1 First generation: crystalline silicon Silicon is one of the most abundant elements on earth, perfectly stable and nontoxic. The so-called first-generation crystalline silicon PV cells are the commercial PV modules basis acting as the semiconductor material with a thickness of about 200 mm. Two types of cells are distinguished as illustrated by Fig. 4.3. The mono-crystalline silicon cells have a perfectly arranged crystalline structure with a dark gray color. They are the purest, take up less space and last for longer time. Obtaining mono-crystalline silicon requires several complementary chemical and physical operations. The poly-crystalline silicon cells are made from the electronics industry residues in the axially

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FIGURE 4.3 Crystalline silicon PV cells: (A) c-Si mono cell, (B) c-Si poly cell.

cooled ingots form which are then cut into thin wafers. They are optimized for commercial use and have a shorter life span as they are affected by high temperatures. This generation, which currently has an efficiency between 16% and 22%, is progressing in the PV field [19].

2.1.2 Second generation: inorganic thin film cells and amorphous silicon PV cells The second-generation technology contains the inorganic thin film silicon and amorphous silicon PV cells. The manufacturing principle is based on the use of an absorber material with a higher optical absorption coefficient than crystalline silicon. They are usually deposited on very low cost substrates such as glass, polymer or metal, allowing the production cost reduction by using cheaper manufacturing processes. In addition, they have the smaller efficiency drop with temperature, which is advantageous for areas with high solar radiation intensity. These technologies may also be used in building integrated PV applications since they are used on flexible substrates as presented in Fig. 4.4.

FIGURE 4.4 Insertion of the inorganic PV cells: (A) Thin film PV cells, (B) Amorphous silicon PV cells.

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This generation type is easy to produce and takes a lot of space for installation. But, it uses a triple layered technology and it carries shorter warranties because his lifespan is shorter than mono and poly-crystalline [20]. However, due to their manufacturing complexity and the toxic materials use, these technologies have not yet reached maturity, unlike the first generation. The proportion of thin-film modules as a share of total production currently is about 15%. The proportion of amorphous silicon is about 9%. Hence, this has led to the emergence of a solar cells third generation [20].

2.1.3 Third generation: future cells This generation responds to an economic need to reduce the price per kWh by improving efficiency or by reducing manufacturing costs. Various concepts are implemented, namely, the multijunction cells in concentrator systems, the dyes or photosensitive pigments cells, the organic cells, and the perovskite solar cells. Concentrating PV cells involve collecting the sun’s radiation through an optics pavement (lens or mirror) and concentrating it on a much smaller surface area to place a small, high-performance PV cell. This type has the highest module efficiency [19]. Dyes or photosensitive pigments PV cells are similar to a photo-electrochemical system inspired by plant photosynthesis. Organic cells are composed of molecular materials or semiconducting polymers. Their manufacturing processes are based on petro chemistry. Recently developed, perovskite PV cells are organiceinorganic hybrid cells based on metal halides. Perovskite solar cells have a great potential to become one of the leading technologies in the PV industry due to their high efficiency (about 20% on laboratory cell samples) and low manufacturing costs [20]. This generation is still in the experimental development stage and further improvements to cost and service life will be important for reaching competitiveness. Some PV systems of this generation are shown in Fig. 4.5.

FIGURE 4.5 Third generation PV cells: (A) Organic PV cells, (B) Concentrated PV cells, (C) Perovskite PV cells.

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2.2 PV systems topologies and types 2.2.1 PV systems topologies For a long time, most solar systems used are fixed or static solar systems. Now, with the technologies advancement and by solar tracking systems, the efficiency of solar systems is being increased since the sun position has been permanently followed according to the season and day time. Although fixed shelving can easily adapt to harsher environmental conditions, tracking systems, being a more complex system, require additional trenches for cabling, additional earthworks and more site preparations, improve the energy extraction efficiency and optimize the energy conversion process. For these reasons, solar tracking systems have been subject of many investigations. They can be classified based on the control strategies, the freedom degree basis of the movement exhibited by the system, the tracking methods and the drives. Fig. 4.6 summarizes the different methods applied for each category. 2.2.2 PV systems types PV systems are classified, based on the global energy conversion chain, into three types, namely, grid direct PV system, off grid PV system, and gridinteraction system with energy storage. The grid tied system consists of an ordinary solar installation using a standard grid-connected inverter and does not have a storage device (battery bank) allowing the electricity production and use during the day only. Generally, PV panels produce more electricity than the load requires. This excess energy can therefore be fed back into the

FIGURE 4.6 Classification of solar tracking systems.

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grid instead of being stored in the batteries and additional income can be generated by selling it. Even though grid-direct system is simple to design, very cost-effective, requires less maintenance and easily manageable, it can be used only during the day time. The standalone PV system is an autonomous system that has batteries for energy storage and hence it is used during day time, in future, during any emergency case (like a cloudy day) and during night. In addition, for this system type, back-up generators are needed especially if sun does not appear for some continuous days. Despite off grid system gives sufficient energy to a household for example which is far away from the grid, it has more components making it comparatively more expensive than grid tied system. Consequently, grid interactive system is recommended which combines the advantages of both systems mentioned above. It is already connected to the grid and has a battery backup. In particular, through widespread incentives, it serves to lower the utility bills. A general structure including the three PV system types is depicted in Fig. 4.7.

2.3 PV models Whatever the topology, technology or type of PV system, its study requires mathematical development and representation of the considered model to simulate, to test and to validate theoretically and then practically the obtained results as well as the interaction between the different systems parameters.

FIGURE 4.7 General structure including grid tied PV system, off grid PV system, and grid interactive PV system types.

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PVS modeling requires a judicious choice of equivalent electrical circuits. Thus, it is important to understand the physical relationship between its constituent elements. According to this approach, several mathematical models have been developed and are diversified by the parameters number choice as well as the mathematical procedures involved in the PV current and PV voltage computing based on single exponential model known as singlediode model or double exponential model known as two-diode model. These models also differ in the parameter extraction method or the applied algorithm.

2.3.1 Single exponential real model (SERM) Known by a single-diode model, the SERM is described by the standard structure consisting essentially of a 203 photo-generator current source, a diode and two resistors. Based on the electrical approach, the general model is 204 illustrated by Fig. 4.8. It presents a mixed group formed by Ns cells in series and Np cells in parallel. From this electrical representation, the output PV current which is obtained to describe the current and voltage evolution is expressed as:     2 0 1 3 Ns Ns V þ Vpv þ Rs Ipv Rs Ipv 6 B pv C 7 Np Np B C  17    Ipv ¼ Np Iph Np I0 6 exp (4.1) 4 @ A 5 Ns AVt Ns Rp Np where Ipv is the output current of the panel, Vpv is the output voltage of the panel, Iph is the current generated by the light incidence, I0 is the reverse saturation current of diode D due to the diffusion and recombination, A is the diode

FIGURE 4.8 Electrical model of a general single-diode representation.

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ideality factor, Vt is the PV thermal voltage of the diode, Rs is the serial resistance, and Rp is the parallel resistance. Diode saturation current I0 is expressed as a function of the nominal shunt current Iscn , nominal open circuit voltage Vocn : I0 ¼

I þ Ki ðT  Tn Þ  scn  Vocn þ Kv ðT  Tn Þ exp 1 AVt

(4.2)

where Ki is the coefficient temperature/short-circuit current, Kv is the coefficient temperature/open circuit voltage, and T is the cells temperature. Some parameters will be identified in the static study while others will be determined in the dynamic study.

2.3.2 Double exponential real model (DERM) Two diodes are used to represent the polarization phenomenon of the PN junction. The general equivalent representation of two-diode model is shown in Fig. 4.9. By applying nodes law, the output current is expressed now as a function of the photo generation current and two diode currents, namely, Id1 and Id2.   Nss Vpv þ Rs Ipv Npp   Ipv ¼ Npp Iph  Npp Id1  Npp Id2  (4.3) Nss Rp Npp

FIGURE 4.9 Electrical model of a general two-diode representation.

Emulating standard characteristics of PV systems Chapter | 4

The Id1 and Id2 are given by the following equations:   2 0 1 3 Nss Vpv þ Rs Ipv 6 B C 7 Npp B C  17 Id1 ¼ I01 6 4exp@ A 5 a1 Vt Nss 2

0

6 B B Id2 ¼ I02 6 4exp@

117

(4.4)



 1 3 Nss Rs Ipv C 7 Npp C  17 A 5 a2 Vt Nss

Vpv þ

(4.5)

where I01 and I02 are, respectively, the reverse saturation currents of Diode 1 and Diode 2 resulted from the diffusion and recombination, a1 and a2 are respectively the ideality factors of Diode 1 and Diode 2. The DERM has been widely adopted in the literature [21,22] when partial shading effect is considered. Indeed, when the irradiation level decreases, the two-diode model shows a better PV characteristics prediction compared to the one-diode model close to the open circuit voltage.

2.3.3 Sandia model Given by SANDIA National Laboratories [23], this model can be destined for any technology and ensures an accurate dynamic forecast for PV cell/module. It requires measurements to be made after the PVS installation by describing thermal, electrical, and optical characteristics. David L. et al. have developed a model allowing to test cells and estimate their productivity. The equations describing this model are as follows: Isc ¼

G f1 ðAMÞf2 ðbÞðIscn þ Ki ðT  Tn ÞÞ Gn

Voc ¼ Vocn þ Ns dðTÞlnðGe Þ þ Kv ðT  Tn Þ   Im ¼ Imn C0 Ge þ C1 G2e ð1 þ Kim ðT  Tn ÞÞ Vm ¼ Vmn þ C2 Ns dðTÞlnðGe Þ þ C3 Ns ½dðTÞlnðGe Þ2 Kvm ðT  Tn Þ where, dðTÞ ¼ Ge ¼

  Ak ðT þ 273:15Þ q

Isc ðG; T ¼ Tn ; AM; bÞ Iscn

(4.6) (4.7) (4.8) (4.9)

(4.10) (4.11)

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b is the incidence angle between direct sunlight and the normal to the PV cell plane, f1 and f2 are, respectively, function related to the air mass number and function related to the b angle, Ge is the effective irradiation, d(T) is the thermal voltage, Imn and Vmn are, respectively, the current and voltage in the MPP under standard 268 test condition, Kvm and Kim are, respectively, the temperature dependence coefficients of the voltage Vmn and 269 current Imn , C0, C1, C2 and C3 are the empirical parameters which are experimentally determined, K is the Boltzmann 270 constant, q is the electron charge.

2.3.4 Cenerg model Cenerg’s model is based on one-diode model [24]. An electrical balance of this approach allows to establish a PV current expression as a function of PV voltage as follows:    Eg Ipv ¼ P1 G½1 þ P2 ðG  Gn Þ þ P3 ðT  Tn Þ  P4 T 3 exp  kT  (4.12)     q Vpv þ Rs Ipv Vpv þ Rs Ipv exp 1  ANs kT Rp where Eg is the material gap energy which is 1.12 eV for crystalline silicon and P1, P2, P3, and P4 are experimentally determined parameters.

2.4 Static and dynamic parameters extraction of PVS Numerical stochastic optimization algorithms are used to identify and to extract five parameters in SERM and seven ones in DERM. The static parameters extraction is done for fixed atmospheric conditions in this case. Many algorithms are considered namely the genetic algorithm (GA), which is employed to find an approximate solution to minimize the root mean square error between the measured PV current and the reference one. For the dynamic parameters identification, the process is done by using atmospheric conditions profile measured during 1 day allowing to improve values given by the manufacturer. Moreover, parameters obtained by static method can be adjusted by dynamic identification. Among these methods, an automatic parameters adjustment using Levenberg Marquardt optimization algorithm is employed [25].

2.5 Control methods of PVS For a PV energy conversion system, the real challenge for researcher is to improve the energy efficiency of a given PV cell technology by using MPPT control as one of important technique. Given that, the PeV output curve of PVS shows a single peak under an even irradiation environment and exhibits

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seriously nonlinear multipeak characteristics under partial shading conditions (PSCs), many different MPPT control methods have been developed to adjust the peak power output and to improve the generating efficiency of the PV system in both conditions [26,27]. These methods can be arranged mainly in two families, namely, the MPPT techniques applied under normal conditions, which are subdivided into traditional MPPT and intelligent MPPT and the MPPT techniques considered under PSC. For the first MPPT family, traditional techniques includes direct control algorithms based on sampled data and control methods based on parameter selection. The direct control algorithms in this category are simple to implement in practice, do not rely on any model of the PV and hence are widely used. They consist of tracking the MPP by taking sampled data, such as voltage, current, and power, from a PV array. These methods include perturb and observe (P&O), incremental conductance, parasitic capacitance, ripple correlation control, voltage feedback method, power feedback, and actual measurement, etc. Otherwise, the control algorithms based on parameter selection attempt to achieve the MPPT control by using knowledge of the PV panel defined and measured parameters under its operating conditions, allowing to permit the establishment of an optimized mathematical model [28,29]. The control methods mainly include constant voltage tracking, open-circuit voltage tracking, short-circuit current tracking, look-up table method, current scanning method, curve fitting method, etc [30]. Although these conventional control methods ensure a good accuracy in terms of MPPT, 314 they are sometimes not very reliable and stable and may fail in spite of climatic conditions change. Hence, intelligent 315 MPPT controls have been widely proposed to improve the generation efficiency of the PV system. These methods 316 include fuzzy logic controller, neural network, and also the nonlinear controller such as sliding mode 317 controller (SMC) and external voltage control combined with P&O and adaptive integral sliding mode control [31e37]. For the second family, MPPT control techniques under PSC are used to overcome the output power drop problem due to the multipeak property of the PV system characteristic curve. However, these methods require real-time data measurement, lengthy calculation, and special circuit configurations. Consequently, some more practical and reliable methods for global optimum tracking have become available, as modern control theory and artificial intelligence development. They are classified according to the hardware control methods based on array reconfiguration, the control methods based on artificial intelligence algorithms, and the improved direct control methods based on perturbation selfoptimization. The hardware control methods based on PV array reconfiguration require the switches, sensors, and controllers use to dynamically change the PV array connection structure such as SC, PC, SPC, BL, TCT, HC, etc., for increasing

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the system immunity to PSC. By changing the array connection structure appropriately, it can reduce the shading effect and enhance the power output to some extent. The control methods based on artificial intelligence algorithms are among the most popular at present, which include 331 particle swarm optimization, artificial bee colony algorithm, ant colony optimization, salp swarm algorithm, GA, etc [36]. The enhanced direct control methods based on disturbance selfoptimization refer to a direct control method using sampled data, which is improved to a certain extent according to the needs of the tracking control of the PV system. A hybrid approach combines a phased search algorithm with a traditional direct control algorithm and allows in a phase to narrow the search by moving the work point and in the other phase to search the global MPP by sing a conventional algorithm in a small range [38e41]. Fig. 4.10 summarizes all the mentioned MPPT techniques.

3. Proposed PV emulator design Tests applied directly on a real PV system whatever the technology, the topology, and the type remain impossible, uneconomical and lead to major problems. Consequently, the need for access to an appropriate substitution of this energy source system and the ability to control the factors affecting it is strongly required. Since these systems operation depend on irradiation and temperature under normal or shading conditions, the use of a PV emulator in laboratory could be the best solution. Thus, the PVE is built around an electronic and numerical component which are adapted through control algorithms to reproduce the IeV and PeV characteristics as a real PVS do.

FIGURE 4.10 Classification of the MPPT control techniques applied under both normal and shading conditions.

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Considering the FPGA implementation benefits on the electrical control field, the proposed PV emulator belongs to the semidynamic emulator family which can switch during the test from IeV curve to other ones previously stored in the memory. This emulator consists of a PV simulator based on twodiode model, a PI controller, a buck converter controlled by PWM strategy and a resistive load in order to perfectly reproduce the nonlinear IeV and PeV characteristics of a real PVS in laboratory and to verify the static and dynamic extraction parameters methods.

3.1 PV model choice 3.1.1 Comparative study One-diode model offers a good compromise between simplicity and precision, whereas a developed approach has shown the two-diode model interests mainly under PSCs as illustrated by Fig. 4.11. These conditions reduce the PVS electrical efficiency. The two-diode model use, despite its complexity in terms of increasing the parameters number, allows a more accurate prediction of the PVS performance for both characteristics. The PVS parameters are shown in Appendix. Under Standard Test Conditions (STC), the two models show similar results near to the short circuit current and open circuit voltage while a small increase in the PV characteristics for the two-diode model was marked at maximum power operating area. When the irradiation decreases, the two-diode model ensures a better forecast and robustness despite atmospheric variations. For this reason, we have opted to use the two-diode model as a PV emulator basic structure.

FIGURE 4.11 One-diode and two-diode comparative study under different atmospheric conditions: (A) IeV characteristic, (B) PeV characteristic.

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3.1.2 Matlab/Simulink PV simulator interface Based on the different equations mentioned above, the modeling and software configuration of the PV simulator is given by Fig. 4.12. The temperature and irradiation level effect on the electrical characteristics of the two-diode PVS is shown in Fig. 4.13. 3.2 PV emulator synoptic diagram The synoptic diagram of the proposed PV emulator based on the two-diode model, the PI controller, the PWM generator, and the buck converter is given by Fig. 4.14. The buck converter, as a part of the PVE power stage, has a second-order LC filter in order to overcome the ripples occurring during the different system operations. The minimum low-pass filter parameters are computed according to the following relations: 8 að1  aÞE > > > Lmin ¼ < f Di (4.13) > að1  aÞE > > : Cmin ¼ 8Lf 2 Dv where a is the duty cycle, f is the IGBT switching frequency, Di and Dv are the current and voltage ripples, respectively. The PI controller, as a part of the

FIGURE 4.12 PV simulator Matlab/Simulink design.

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FIGURE 4.13 Simulation results of the proposed PV simulator based on two-diode model: (A) IeV curves for different irradiation levels at constant temperature, (B) PeV curves for different irradiation levels at constant temperature, (C) IeV curves for different temperature values at constant irradiation, (D) PeV curves for different temperature values at constant irradiation.

FIGURE 4.14 Proposed PV emulator synoptic diagram.

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PVE control stage, acts on the PWM pulse generator for providing the gate control signal. The PI controller associated with the buck converter transfer functions are expressed as follows: Gc ðsÞ ¼

E     1 rL 1 þ LC s2 þ s þ RC L LC GC ðsÞ ¼

Kp s þ Ki s

(4.14)

(4.15)

The Kp and Kv controller values are determined by the pole compensation technique allowing to act on the system dynamic and the static error adjustment. Simulation results obtained from the PV emulation chain and compared with reference curves are depicted by Fig. 4.15. Data collection was performed for three different cases as shown in Table 4.1. It presents the considered parameters, the reference output measurement, the PV-simulated outputs, and the relative error which is determined at different areas. To determine the closeness between the reference output and simulator one, relative error is calculated as:   Xsimulator  Xref  εðXÞð%Þ ¼  100 (4.16) Xref In our case, X is Voc, Isc, Vmp and Imp. It is noted that the relative error, computed in all cases, is less than 1% for both PV voltage and PV current under different atmospheric conditions. As a result, the proposed PV simulator circuit can be replaced by the real PV module and can be practically implemented in the laboratory. So, all kinds of atmospheric conditions can be obtained and discussed and simulated.

FIGURE 4.15

Simulation results of the PV emulator Matlab/Simulink design.

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TABLE 4.1 Reference and emulated values of the proposed PV simulator comparative study under different atmospheric conditions.

G [ 1000 W/ m2, T [ 258C

G [ 1000 W/ m2, T [ 508C

G [ 600 W/m , T [ 258C 2

Parameters

Reference output

Output of the PV simulator

Relative error (%)

Voc (V)

21.1

21.09

0.04

Isc (A)

3.8

3.78

0.52

Vmp (V)

17.1

17.2

0.58

Imp (A)

3.5

3.48

0.57

Voc (V)

19

18.9

0.52

Isc (A)

3.872

3.878

0.15

Vmp (V)

15.3

15.23

0.45

Imp (A)

3.477

3.48

0.08

Voc (V)

20.5

20.65

0.73

Isc (A)

2.275

2.29

0.65

Vmp (V)

17.3

17.43

0.75

Imp (A)

2.047

2.034

0.63

where, Vmp and Imp are, respectively, the voltage and current at maximum power.

4. Real-time (RT) digital simulation and hardware-in-theloop (HIL) test of the PVE In power electronic control applications, real-time digital simulation is considered as an efficient method for reproducing accurately the transient and dynamic behaviors of the PVS characteristics compared to a standard offline simulation. The majority of the developed RT simulators are applied in hardware-in-the-loop testing of digital controllers in order to validate them under all operating conditions. For the RT-PV simulator implementation, FPGA-based platform is highly recommended, covering a wide range of system complexities, integrating powerful, and scalable multicore processor boards and operating at high frequency.

4.1 RT PV digital simulation In this part, an intellectual property (IP) module that simulates the PVS to be emulated is described. Thus, this IP and the controller will be both implemented and run altogether in the same FPGA device. To develop an efficient FPGA-based PV simulator, a rigorous methodology for algorithm describing,

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which guarantees the desired performance, is needed. XSG is used for providing an inexpensive and easily accessible platform for an efficient method of designing, reconfiguring, and testing new way of hardware prototyping without HDL knowledge. This tool ensures a rapid prototyping of the IP module to be implemented automatically in FPGA. The two-diode PV RT simulator with XSG components is detailed in Fig. 4.16. For the proposed PVE controller, the PI regulator, the PWM generator, and the ADC communication protocol are also designed based on XSG library as illustrated in Fig. 4.17.

4.2 HIL test and validation of the PVE controller The objective here is to evaluate the performance of the developed RT-PV simulator to be used for testing processor-based controllers. Thus, the architecture is ready to be tested in its experimental environment as shown in Fig. 4.18.

FIGURE 4.16 RT interface configuration of the proposed PV simulator designed using XSG tools.

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FIGURE 4.17 Control stage of the RT-PV simulator using XSG blockset.

FIGURE 4.18 HIL process.

HIL ensures the synthesized control strategy validation by optimizing the total time required to perform the experimental tests. The obtained IeV and PeV curves by the FPGA-based RT simulator compared with those obtained after offline Simulink-based simulation are depicted in Fig. 4.19. We note that the FPGA-based real-time simulation results are similar to those of the Matlab/Simulink ones. Therefore, the good functionality of the FPGA-based RT simulator is validated to control the PWM buck converter for operating the PVE as a real PVS. In addition, the obtained results demonstrate that the developed IP module of PV simulator can be used efficiently for testing PWM buck converter control algorithms and their performance in HIL evaluating. The design flow that summarizes the PV emulator architecture implementation steps is presented in Fig. 4.20.

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FIGURE 4.19 Simulation results of the RT PV simulator Matlab/XSG design compared with offline Simulink ones under various atmospheric conditions: (A) IeV curves, (B) PeV curves.

During the development process, some constraints set must be considered to design the PV simulator that reproduces the actual PV system behaviors in real time and respects the limits inherent to the used low-cost FPGA. The most important constraints for FPGA-based RT simulator are timing constraints, modularity constraints, algorithm constraints, and FPGA implementation constraints. For the timing, it has to be short enough to accurately represent the system and long enough to allow the processing of all model equation for making the RT simulator carefully synchronous with the PV emulator controller. For the modularity, the developed simulator should be optimized as possible to make the design manageable and well structured. Then, the importance of creating an IP library that gathers the developed IP in a multilevel hierarchical decomposition is noted. For the algorithm, the complexity level is related to the details presented in the developed model and its discretization manner. For the FPGA implementation, the architecture development must consider the available hardware resources which are limited by the FPGA target cost. Moreover, to avoid overruns, the computation time, which depends on the used clock frequency, should be less than the RT simulation time step. Considering all the constraints mentioned above, for our PV simulator timing, a minimum period equal to 123.969 ns is obtained, which corresponds to a maximum frequency equal to 8.067 MHz. An estimation of the used resources for the PV emulator control implementation over FPGA is presented in Table 4.2.

Emulating standard characteristics of PV systems Chapter | 4

FIGURE 4.20 Flowchart of the FPGA implementation steps based on XSG.

129

130 PART | II Solar photovoltaic energy

TABLE 4.2 Resource estimation of the RT PV simulator. Resources type

Used resources

Percent (%)

Slices

2906

40

Registers

4376

15

Flip flops

10,187

Luts

9797

34

DSP48Es

42

87

IOBs

34

7

BUFG/BUFGCTRLs

1

3

5. Experimental test bench and results In order to experimentally validate the transient and dynamic behaviors of the PV emulator for reproducing the electrical characteristics under static and dynamic conditions, an FPGA-based test bench was built around the RT-PV simulator based on two-diode model and the PI controller, the buck converter, the A/D converter, the acquisition board, the power load, and the FPGA. The synoptic diagram of this device is shown by Fig. 4.21. The PV emulation, in a closed loop mode, begins by entering the basic PVS characteristics and parameters to be emulated into the Matlab/XSG software interface. A series of software and/or hardware validations have been done to generate the corresponding bitstream configuration file. Once the FPGA implementation is complete, the switching signal drive the IGBT of the buck converter which feeding a power resistive load. For each load change, the measured PV current and PV voltage, trough, respectively, LA25NP and LV25P sensors, will be digitally converted via A/D converters to determine the corresponding duty cycle. In this case, the recovered electrical characteristics perfectly emulate the standard IeV and PeV curves of the actual PVS as described by Fig. 4.22. Experimental results compared with manufacture ones are illustrated by Fig. 4.23. The experiment series are validated under STC conditions. It is noted that they are in good agreement with simulation results proving the high performance and accuracy of the digital control method for the proposed PV emulator. The current limitation observed in the experimental results is explained by the used power source which supports 3 A. The relative errors recorded on the PV current and the PV power curves are less than 3% and 2.5%, respectively. These results prove the robustness of the adopted FPGA-based digital control of the PV emulator.

FIGURE 4.21 PV emulator experimental test bench including acquisition, treatment, and control parts.

FIGURE 4.22 Real hardware platform of the proposed PV emulator.

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FIGURE 4.23 Experimental results of the proposed RT emulator closed loop control under STC compared with reference results: (A) IeV curves, (B) PeV curves.

This device could be explored by industrial in general purpose and researchers in particular in order to apply their tests, to analyze, to develop and to improve control strategies as well as the energy optimization of PV energy conversion systems under static and dynamic study cases. For example, under non-STCs, profiles of both temperature and irradiation are introduced by a constant or variable XSG profiles that defines their levels. In this case, the new reference values of the short circuit current and open circuit voltage are recomputed, and the correspondent architecture is implemented again to control the PV emulator in different way.

6. Conclusion This chapter presents a detailed study and conception of a PV emulator operation beginning by the model representation choice, the design, the simulation, the optimization, and the implementation methodology to repeat the IeV and PeV curves in laboratory regardless the atmospheric conditions. A general overview of the PV systems topology, technology, and type was described. The proposed PVE was mainly based on two-diode model, buck converter, and FPGA target. Thus, a real-time PV simulator was developed and prototyped through XSG tools to verify the PVS output characteristics for rapid implementation. Moreover, the RT-PV simulator ability for ensuring the service continuity and the digital buck converter control maintain was approved via a closed loop HIL testing. An experimental test bench was built to validate the theoretical prediction. The comparison between reference results and experimental ones has shown a low error rate proving the efficiency and accuracy of the numerical control strategy for PV characteristics emulation.

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A series of measurements and experiments can be applied on this device to highlight and analyze both static and dynamic behaviors of many PVS topologies under constant or variable conditions and whatever the parameters identification methods. In addition, it allows considering some PVS problems and try to solve them by applying fault detection mode.

Appendix Parameters of the proposed two diode PV simulator based on the MSX60 solar array datasheet: l l l l l l l l

Short circuit current, Isc ¼ 3.8 A; Open circuit voltage, Voc ¼ 21.1 V; Maximum power current, Imp ¼ 3.5 A; Maximum power voltage, Vmp ¼ 17.1 V; Ki ¼ 0.0032 (A/K); Kv ¼ 80e-3 (V/K); Rp ¼ 164.585,828 U; Rs ¼ 0.34 U; The values of Rs and Rp are calculated by using MXS60.m file.

Acknowledgments This work was supported by the Tunisian Ministry of Higher Education and Scientific Research under Laboratory of Advanced Technology and Intelligent Systems (LATISENISo).

References [1]

[2] [3]

[4]

[5]

P. Ganguly, A. Kalam, A. Zayegh, Solarewind hybrid renewable energy system: current status of research on configurations, control, and sizing methodologies, in: HybridRenewable Energy Systems in Microgrids, Elsevier, 2018, pp. 219e248. Woodhead Publishing. P.S. Sikder, N. Pal, Modeling of an intelligent battery controller for standalone solar-wind hybrid distributed generation system, J. King Saud Univ. Eng. Sci. 32 (6) (2020) 368e377. B. Sharma, R. Dahiya, J. Nakka, Effective grid connected power injection scheme using multilevel inverter based hybrid wind solar energy conversion system, Elec. Power Syst. Res. 171 (2019) 1e14. S.M. Lawan, W.A.W.Z. Abidin, A Review of Hybrid Renewable Energy Systems Based on Wind and Solar Energy: Modeling, Design and Optimization. Wind Solar Hybrid Renewable Energy System, IntechOpen, 2020. R.M. Ferdous, A.W. Reza, M.F. Siddiqui, Renewable energy harvesting for wireless sensors using passive RFID technology: a review, Renew. Sustain. Energy Rev. 58 (2016) 1114e1128.

134 PART | II Solar photovoltaic energy [6] N. Diaz, J. Herna´ndez, O. Duarte, Fuzzy maximum power point tracking techniques applied to a grid-connected photovoltaic system, in: Fuzzy Controllers, Theory and Applications, Lucian Grigorie, 2011. [7] D. Vinnikov, A. Chub, O. Korkh, E. Liivik, F. Blaabjerg, S. Kouro, MPPT performance enhancement of low-cost PV microconverters, Sol. Energy 187 (2019) 156e166. [8] I. Moussa, A. Khedher, A. Bouallegue, Design of a low-cost PV emulator applied for PVECS, Electronics 8 (2) (2019) 232. [9] D. Abbes, A. Martinez, G. Champenois, B. Robyns, Real time supervision for a hybrid renewable power system emulator, Simulat. Model. Pract. Theor. 42 (2014) 53e72. [10] R. Ayop, C.W. Tan, A novel photovoltaic emulator based on current-resistor model using binary search computation, Sol. Energy 160 (2018) 186e199. [11] J. Chavarria, D. Biel, F. Guinjoan, A. Poveda, F. Masana, E. Alarcon, FPGA-based design of a step-up photovoltaic array emulator for the test of PV grid-connected inverters, in: IEEE International Symposium on Industrial Electronics (ISIE’23), IEEE, June 2014, pp. 485e490. [12] S. Gadelovits, M. Sitbon, A. Kuperman, Rapid prototyping of a low-cost solar array simulator using an off-the-shelf DC power supply, IEEE Trans. Power Electron. 29 (10) (2014) 5278e5284. [13] M. Balato, L. Costanzo, D. Gallo, C. Landi, M. Luiso, M. Vitelli, Design and implementation of a dynamic FPAA based photovoltaic emulator, Sol. Energy 123 (2016) 102e115. [14] J.R. Prasanth, H. Manghani, D.S. Pillai, T.S. Babu, M. Myatake, N. Rajasekar, Analysis on solar PV emulators: a review, Renew. Sustain. Energy Rev. 81 (2018) 149e160. [15] G.M. Tornez-Xavier, F. Gomez-Castaneda, J.A. Moreno-Cadenas, L.M. Flores-Nava, September). FGPA development and implementation of a solar panel emulator, in: Proceedings of the IEEE International Conference on Electrical Engineering, Computing Science and Automatic Control (ICEECSA’11), IEEE, 2013, pp. 467e472. [16] A.M. Humada, S.Y. Darweesh, K.G. Mohammed, M. Kamil, S.F. Mohammed, N.K. Kasim, S. Tahseen TA Awad OI Mekhilef, Modeling of PV system and parameter extraction based on experimental data: review and investigation, Sol. Energy 199 (2020) 742e760. [17] K.G. Sai, T. Moger, Reconfiguration strategies for reducing partial shading effects in photovoltaic arrays: state of the art, Sol. Energy 182 (2019) 429e452. [18] J.D. Bastidas-Rodriguez, C.A. Ramos-Paja, A.J. Saavedra-Montes, Reconfiguration analysis of photovoltaic arrays based on parameters estimation, Simulat. Model. Pract. Theor. 35 (2013) 50e68.  ´ , PV cells and moduleseState of the art, limits and trends, Heliyon 6 [19] V. Benda, L. Cerna (2020) 12e05666. [20] A. Awasthi, A.K. Shukla, M.M. SR, C. Dondariya, K.N. Shukla, D. Porwal, G. Richhariya, Review on sun tracking technology in solar PV system, Energy Rep. 6 (2020) 392e405. [21] A. Yahya-Khotbehsara, A. Shahhoseini, A fast modeling of the double-diode model for PV modules using combined analytical and numerical approach, Sol. Energy 162 (2018) 403e409. [22] I. Moussa, A. Khedher, March). Photovoltaic simulator interface based on two-diode equivalent circuit model, in: IEEE International Renewable Energy Congress (IREC’10), IEEE, 2019, pp. 1e6. [23] D. King, W.E. Boyson, J.A. Kratochvill, Photovoltaic array performance model; Sandia Report: SAND2004-3535, in: USA, 2004, https://doi.org/10.2172/919131. [24] W.I. Bower, PHANTASM: Photovoltaic Analysis and Transient Simulation Method, Solar Energy Laboratory, University of Wisconsin, Madison, USA, 1999.

Emulating standard characteristics of PV systems Chapter | 4 [25]

[26]

[27] [28]

[29] [30]

[31]

[32] [33] [34]

[35]

[36]

[37]

[38]

[39]

[40]

[41]

135

S.A. Blaifi, B. aghezouit, Static and dynamic photovoltaic cell/module parameters identification, in: Advanced Statistical Modeling, Forecasting, and Fault Detection, Renewable Energy Systems. IntechOpen., 2020. M. Lasheen, A.A. Rahman, M. Abdel-Salam, S. Ookawara, Adaptive reference voltage based MPPT technique for PV applications, IET Renew. Power Gener. 11 (5) (2017) 715e722. R. Alik, A. Jusoh, An enhanced P&O checking algorithm MPPT for high tracking efficiency of partially shaded PV module, Sol. Energy 163 (2018) 570e580. A. Ghamrawi, J.P. Gaubert, D. Mehdi, A new dual-mode maximum power point tracking algorithm based on the perturb and observe algorithm used on solar energy system, Sol. Energy 174 (2018) 508e514. P.A. Kumari, P. Geethanjali, Parameter estimation for photovoltaic system under normal and partial shading conditions: a survey, Renew. Sustain. Energy Rev. 84 (2018) 1e11. T.H. Wu, W.C. Liu, C.S. Moo, H.L. Cheng, Y.N. Chang, June). An electric circuit model of photovoltaic panel with power electronic converter, in: Proceedings of the 17th Workshop on Control and Modeling for Power Electronics (COMPEL), IEEE, 2016. X. Li, Q. Wang, H. Wen, W. Xiao, Comprehensive studies on operational principles for maximum power point tracking in photovoltaic systems, IEEE Access 7 (2019) 121407e121420. X. Li, H. Wen, Y. Hu, L. Jiang, A novel beta parameter based fuzzy-logic controller for photovoltaic MPPT application, Renew. Energy 130 (2019) 416e427. X. Li, H. Wen, Y. Hu, et al., Modified beta algorithm for GMPPT and partial shading detection in photovoltaic systems, IEEE Trans. Power Electron. 33 (3) (2018) 2172e2186. X. Li, H. Wen, Y. Zhu, L. Jiang, Y. Hu, W. Xiao, A novel sensorless photovoltaic power reserve control with simple real-time MPP estimation, IEEE Trans. Power Electron. 34 (8) (2019) 7521e7531. H. Li, D. Yang, W. Su, W. Lu, X. Yu, An overall distribution particle swarm optimization MPPT algorithm for photovoltaic system under partial shading, IEEE Trans. Ind. Electron. 66 (1) (2019) 265e275. D. Pilakkat, S. Kanthalakshmi, An improved p & o algorithm integratedwith artificial bee colony for photovoltaic systems under partial shading conditions, Sol. Energy 178 (2019) 37e47. Y. Cui, Z. Yi, J. Duan, D. Shi, Z. wang, A Rprop-neural-network-based PV maximum power point tracking algorithm with short-circuit current limitation, in: Proceedings of the Power and Energy Society Innovative Smart Grid Technologies Conference (ISGT), IEEE, 2019. February. H. Hamdi, C. Ben Regaya, A. Zaafouri, Real-time study of a photovoltaic system with boost converter using the PSO-RBF neural network algorithms in a MyRio controller, Sol. Energy 183 (2019) 1e16. A. Kihal, F. Krim, A. Laib, B. Talbi, H. Afghoul, An improved MPPT scheme employing adaptive integral derivative sliding mode control for photovoltaic systems under fast irradiation changes, ISA Trans. 87 (2019) 297e306. M. Mao, L. Cui, Q. Zhang, K. Guo, L. Zhou, H. Huang, Classification and summarization of solar photovoltaic MPPT techniques: a review based on traditional and intelligent control strategies, Energy Rep. 6 (2020) 1312e1327. M.A. Danandeh, G.S.M. Mousavi, A new architecture of INC-fuzzy hybrid method for tracking maximum power point in PV cells, Sol. Energy 171 (2018) 692e703.

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Part III

Bioenergy production

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Chapter 5

Green pellets production and applications in energy sector Mejdi Jeguirim1 and Besma Khiari2 1 The Institute of Materials Science of Mulhouse (IS2M), University of Haute Alsace, University of Strasbourg, CNRS, Mulhouse, France; 2Wastewaters and Environment Laboratory, Water Research and Technologies Center (CERTE), Technopark Borj Cedria, University of Carthage, Tunisia

1. Introduction The depletion of fossil fuels and the marked climate change due to the increasing greenhouse emissions have favored the utilization of biomass for heat, steam, and electricity generation worldwide [1]. In contrast to other renewable energy sources (wind, solar) that depend on weather and seasonal change, biomass resources are permanently available, used when needed and could be easily implemented in existing infrastructures, especially when cofired in coal-based power plants [2,3]. One of the major factors limiting the biomass use for heat and electricity production is its low bulk density (40e200 kg/m3) and therefore energy density (0.8e3.5 GJ/m3) [4e6]. Furthermore, the distances between biomass production sites, such as forest and agricultural land to the energy production sites (industrial or residential areas), require significant logistics for transportation and storage [7]. Fortunately, these constraints can be overcome with pelletization process that increases the biomass bulk and energy densities to about 700e900 kg/m3and 12e18 GJ/m3, respectively [8]. Furthermore, beyond of density increase and its benefit on the reduction of storage and transportation costs, pelletization offers a uniform granulometry with controlled moisture content that is advantageous for feeding automation into boiler systems and therefore large-scale utilization [9,10]. During the last decades, biomass pelletization (resources and technology) has received increasing attention. Generally, wood pellets are the most used due to their high-quality products, such as low ash contents and high heating values that the current standard requirements characteristics [11]. However, the increase in pellets demand and the limited availability of wood resources have emphasized the need to widen the raw material used for pellets Renewable Energy Production and Distribution. https://doi.org/10.1016/B978-0-323-91892-3.00007-8 Copyright © 2022 Elsevier Inc. All rights reserved.

139

140 PART | III Bioenergy production

production. In particular, several agriculture and food processing industry residues, such as Miscanthus [12], date palm residues [13], olive mill waste [14], spent coffee ground [15], grape marc, tomato wastes [16], straw, maize, wheat bran, vineyard pruning, and Sorghum [17] have been used for pellets production. Biomass pellets can be converted thermally into useable forms (energy, biofuels) via different thermochemical conversion techniques such as gasification, pyrolysis, and combustion [18e20]. The selection of process will mainly depend upon type and quantity of biomass available resources, environmental standards, economical condition, and other factors. In gasification process, biomass is converted into gaseous fuel by applying a partial oxidation at a higher temperature. Hence, this technique is adapted for converting different wastes and residues to biofuels and can be used for heat generation. However, the main disadvantage of gasification is the requirement of separation techniques for the different products and the ash slag formation at high temperature [21]. Pyrolysis is the thermal decomposition of organic matters in the absence of oxygen. This technique is relatively a slow chemical reaction which is occurred at low temperature to convert biomass into gaseous (syngas), liquid (bio-oil) and solid (char) products [22,23]. These generated products can be used in various environmental, energetic, and agricultural applications. Pyrolysis depends strongly on the operating conditions including temperature, heating rate, particle size, and catalyst presence. The heterogeneity of biomass resources lead to some difficulties to adapt this technique at large scale [24]. In terms of the level of technology, combustion is the most developed and widely applied process used for conversion of solid biomass into thermal and electric energy [25,26]. It is a complex phenomenon implicating homogeneous and heterogeneous reactions. Biomass combustion occurs via series of simultaneous and successive phases including, drying, devolatilization, and volatiles and char oxidation. The drying phase occurs at low temperatures (below 100
C) due to the vaporization of the water in the fuel. In the devolatilization phase, the thermal degradation of the carbonaceous particle leads to the emission of gaseous components such as H2O, CO, H2, CO2, CH4, and tars [27]. The concentration of these components is strongly affected by the operating conditions (heating rate, particle size, etc.). The last step involves the oxidation of volatile species released during the devolatilization step, occurring in the homogeneous phase. It also includes the oxidation of residual chars left after the volatiles departure [28]. Fig. 5.1 diagrammatically presents the example of wood combustion process [29]. Different biomass combustion technologies are available for domestic use and for industrial applications. These technologies include burning biomass in fluidized beds (FB) and grates [30]. Grates were the first combustion system used for solid fuel. It has four components: the fuel supply, the grate, the primary and secondary air feeder, and the ash discharger. FB combustion

Green pellets production and applications in energy sector Chapter | 5

141

FIGURE 5.1 Wood combustion characteristics [29].

equipment is constituted by two distinct regions, one where the concentration of solids is high, called the bed, and a second region where the solid concentration is much lower, called the free space above the bed (freeboard) [31]. This chapter summarizes the recent investigations on the production of pellets from different biomass resources. It includes the pellets production procedure and their physicochemical properties with respect to international standards. These pellets performance during combustion tests at domestic and industrial scales in terms of thermal efficiency and gaseous emissions are also examined.

2. Biomass pellets production 2.1 Biomass raw materials: types, composition, and characterization Several feedstock types have been converted into pellets to be used for energy production. For example, different olive mill wastes were characterized and used for pellets production [4,8,32,33]. Pellets from tomato waste and grape marc were investigated by Kraiem et al. [5]. Grape pomace mixed with

142 PART | III Bioenergy production

Pyrenean oak for pellets production were also experimented by Miranda et al. [34]. Woody biomass, agro-residues including rice husk, coconut fiber, coconut shell [35] and sugar cane bagasse, sunflower husk (SFH), Brazil nut (BN) shells [36] were converted in to pellets and tested in domestic combustor. The physiochemical characteristics of pellets made up seven agricultural raw materials: straw from wheat (Triticum aestivum), Miscanthus (Miscanthus giganteus), maize (Zea mays), vineyard pruning (from Vitis vinifera), wheat bran, hay, and Sorghum (Sorghum bicolor) [17] were also evaluated. Another study was also conducted by Elmay et al. where the physical properties and combustion performance of pellets produced from date palm residues were compared to values of date stones [13]. Even sewage sludge was examined as a possible raw material for pellets production [37]. Other examples of biomass feedstock, which may be utilized for pellets production comprise energy crops (Willow, Miscanthus, etc.) [12,38], cereals straws (Wheat, Barley), food processing residues (spent coffee ground, coffee husk, etc.) [15], were also characterized. Table 5.1 regrouped different feedstock, found in the literature that could be used for pellets production [39]. Furthermore, the characterization of these raw materials is presented through proximate and ultimate analysis techniques. The proximate analysis includes the moisture (MC), volatile matter (VM), fixed carbon (FC), and ash contents of the raw material. On the other hand, ultimate analysis determines carbon (C), hydrogen (H), sulfur (S), nitrogen (N), and oxygen (O) elements. These both techniques are required to easily predict the physical and the chemical properties of pellets produced from a given biomass feedstock. Following the various results reported from studies that performed ultimate analysis for biomass feedstock characterization (Table 5.1), it is observed that the main component of biomass raw material is carbon ranging from 44.4 wt% to 61.6 wt%. The second element is oxygen that is usually determined by difference. The oxygen content is ranging from 33 wt% to 49.3 wt%. Hydrogen content ranges from 5.2 wt% to 7.2 wt%. Nitrogen is usually present in relatively small quantities ranging from 0.2% to 2%. Sulfur is generally below 0.2 wt% and not usually quantified during the biomass ultimate analysis determination. Concerning the proximate analysis for biomass raw materials, Table 5.1 shows that the volatile matter content was the highest, with values ranging from 50 wt% and 85.3 wt% while ash content was the lowest in many of the cases, with values ranging from 0.4 wt% and 18.3 wt%. Moreover, the ash content will vary significantly, depending on the type of biomass raw material. For instance, woody biomass resources were found to be associated with ash contents that are below 0.5%, while biomass derived from cereal straws is often associated with higher ash content values, typically 15% and above.

TABLE 5.1 Proximate and ultimate analysis of different biomass feedstock. Green pellets production and applications in energy sector Chapter | 5

Proximate analysis (wt%)a

Ultimate analysis (wt%)b

Woody species

Ash

VM

FC

C

H

Oc

N

Mallee wood

0.9

80.9

18.2

48.2

6.1

45.5

0.2

Rubber wood

2.3

72.6

25.1

44.4

7.0

46.3

0.4

Pine

0.2

83.3

16.5

50.6

5.9

43.1

0.4

Cypress wood

0.6

80.3

19.1

51.6

6.4

41.8

0.2

Holm oak

2.3

80.8

16.9

48.0

5.9

45.6

0.5

Mapple wood

1.0

e

e

53.4

6.8

39.8

0.0

Silver fir

0.4

78.7

20.9

51.2

6.4

42.2

0.2

Pyrenean oak

2.4

80.5

17.1

48.5

5.9

45.1

0.5

Hornbeam

0.4

78.1

21.5

45.2

6.6

48.2

e

Reed

3.2

80.3

16.5

49.1

5.9

44.5

0.5

Stone pine

0.7

82.1

17.2

50.4

6.0

43.3

0.3

Beech wood

0.5

84.3

15.2

49.4

5.7

44.7

0.2

Sawdust

0.5

75

14.5

51.3

6.4

41.6

6.2

4.8

85.3

9.9

49.9

6.2

43.2

0.5

Agriculture residues Rapeseed stalk

143

Continued

Proximate analysis (wt%)a

Ultimate analysis (wt%)b

Woody species

Ash

VM

FC

C

H

Oc

N

Rice husk

18.3

65.6

16.1

50.5

6.9

42.1

0.6

Paddy straw

22.5

60.8

16.7

48.8

6.0

43.3

2.0

Date palm trunk

5.4

70.8

24.8

44.9

6.1

48.6

0.2

Pomegranate peel

3.5

68.7

27.8

46.0

5.5

39.0

e

Maize stalk

6.0

80.8

13.2

49.3

6.5

42.6

1.6

Rapeseed

7.3

78.7

14

44.7

5.8

48.1

0.8

Coco peat

5.8

62.2

32.0

61.6

4.4

33.0

1.0

Sugarcane bagasse

2.4

81.8

15.8

51.7

5.3

42.7

0.3

Red canary grass

6.0

76.9

17.1

50.0

7.0

40.9

1.3

Palm kernel shell

7.9

66.0

16.1

55.9

-

41.2

-

Sunflower

8.3

74.5

17.2

43.6

5.8

49.3

1.0

Corn straw

5.2

e

e

45.0

5.2

48.9

0.9

Rice straw

15.0

70.7

14.3

47.5

6.5

44.9

1.1

Cotton straw

2.9

80.9

16.2

49.4

6.3

43.5

0.8

Miscanthus

2.7

78.8

8.5

44.6

5.9

43.2

0.2

144 PART | III Bioenergy production

TABLE 5.1 Proximate and ultimate analysis of different biomass feedstock.dcont’d

5.6

73.6

8.3

39.8

5.7

53.0

0.19

Date palm stones

0.8

74.1

17.5

51.2

6.4

40.9

0.73

Olive mill solid waste

4

66.6

23.4

52.1

6.7

41.2

1.4

Spent ground coffee

1.9

69.4

21.2

61.1

9.0

26.6

2.9

Kiwifruit pruning

1.3

79.1

19.5

49.4

5.7

44.4

0.6

Almond shells

1.6

77.7

20.7

58.4

5.2

36.1

0.2

Vineyard pruning

2.9

77.1

20.0

48.3

5.7

45.2

0.7

Grape marc

12

50

28.0

42.2

3.5

39.3

3.0

Tomato residues

8

76

8.0

59.4

7.6

23.4

1.6

Oilseed straw

e

e

e

47.3

5.8

40.4

0.7

Wheat straw

4

59

21

48.5

5.5

45.6

0.3

Coconut fiber

4.1

82.1

13.8

49.4

6.6

42.7

1.2

Coconut shell

1.8

78.8

21.8

40.1

5.2

54.3

0.2

Brazil nut shell

2.1

65.7

21.6

53.5

5.7

37.0

1.6

FC, fixed carbon; VM, volatile matters. a Dry basis. b Dry ash free. c By differencedNot provided.

Green pellets production and applications in energy sector Chapter | 5

Date palm rachis

145

146 PART | III Bioenergy production

2.2 The pelletization process The pellet production process includes different stages in which the biomass is treated, densified, and stored (Fig. 5.2). Several stages affect strongly the overall pellets quality and therefore their performance during energy production. The first stage is milling to obtain material with particles of equal size. In general, greater pellet strength and durability are attributed to the presence of finer particle sizes. However, it is essential to pay attention also to the particle size distribution. The ideal pellet quality is attained when a blend of particle sizes is generated, due to the fact that the interparticle connection, especially mechanical meshing, increases during pelletization. Drying step is also one of the most critical steps since moisture is one of the essential elements in the pellet formation process. In fact, water induces many of the intermolecular forces that are necessary for effective pelletization. However, once the moisture content of biomass raw material exceeds a certain threshold, the resulting pellet quality will decrease, as they become highly prone to degradation. Mixing and conditioning step can be applied after size reduction and drying steps, in order to obtain a consistent and homogeneous material blend. Furthermore, adding suitable binder materials is particularly important to improve the pellets properties. Generally, binding agents can promote durability, increase pelleting efficiency, and decrease energy costs. The binder agents are selected based on the raw pelletized biomass in order to ensure that the most desirable properties of the produced pellets may be attained. Pelletization step is realized in pellet mills, known as pellet presses or extruders (Fig. 5.3). Pellet mills work by creating a high pressure in order to guide the raw material through the die openings. When the pressure increases, the friction increases, and the temperature of the raw material also rises. This

FIGURE 5.2 Stages of the pelletization process.

Green pellets production and applications in energy sector Chapter | 5

147

FIGURE 5.3 Pellet mill system [40].

results in a moisture content decrease, lignin softening and the fiber reshaping into pellet form.

2.3 Pellets characterization In order to rationally and efficiently use biomass pellets as solid biofuel, it is necessary to determine their physical, mechanical, combustion, thermal, and chemical characteristics.

2.3.1 Physical properties Physical properties include mainly bulk density, particle distribution, and water/resistance/porosity. The bulk density and particle distribution are generally evaluated for the initial feedstock. Bulk density influences the economics of storage collection and transportation. It is calculated by the mass material contained in a standard container volume for the milled material. Particle distribution is determined by performing sieve analysis. It influences the heat diffusion, flowability, bonding, and reaction time. The water resistance/porosity index is the quantity of water the fuel will be able to absorb when exposed to a humid environment. Porosity affects the heat and mass transfer, air flow velocity, which in turn influences the heat conductivity, conversion efficiency, emissions, and burning rate. It is calculated according to the following expression: PI ¼

MW  100; MF

where MW is the mass of water absorbed while MF is the mass.

2.3.2 Mechanical properties Mechanical properties include mainly compressive strength, durability (Shatter index [SI]), and abrasive resistance. The compressive strength

148 PART | III Bioenergy production

measures the resistance of the solid fuel to squeezing and pressing forces. It can be determined using universal testing machine in accordance with established standards. The durability measures the degree of fuel breakage and shattering tendency under sudden forces. It can be determined by performing a drop test. Fuel with known weight and dimensions would be dropped on the concrete floor from a height of 1 m. The SI is calculated after four drops according to: w1  w2 % weight loss ¼ and SI ¼ 100  % weight loss w1 where w1 and w2 are the weight of the fuel before and after shattering, respectively. The abrasive resistance measures the resistance of the solid fuel to impact and grinding forces. A fuel of known weight is placed in a tumbler rotating at about 12 revolutions per minute for about 4 min. After the tumbling process, fuels are taken out and weighed. The expression used for the shatter resistance will be adopted to calculate the abrasive resistance.

2.3.3 Combustion/thermal properties Combustion/thermal properties include proximate analysis, thermogravimetric analysis, calorific values, Energy density/thermal efficiency, ignition time, and combustion rate (CR). The proximate analysis reveals, as shown previously, the feedstock moisture (MC), volatile matter (VM), ash (AC), and fixed carbon (FC) contents. These different contents are determined according to established standards. Thermogravimetric analysis provides information on the thermal breakdown profile of feedstock. Using a themogravimetric analyzer, it measures the fuel percentage weight loss as a function of temperature and presents a peculiar shape as the resulting thermogram for fuel materials. The calorific value reveals the feedstock energy potential. It is determined using bomb calorimeter or calculated from the results of proximate and ultimate analyses according to correlations established in the literature. The energy density describes the amount of energy stored per unit volume. It is calculated through the multiplication of the calorific value by the bulk density. The thermal efficiency is the percentage of fuel energy available for power generation. It is usually measured by performing a water boiling test. Ignition time is the average time taken to achieve steady glowing fire while burning the fuel. It is determined by burning a known quantity of the fuel in a charcoal stove. CR is the time taken to burn a known mass of fuel completely: CR ¼

Total mass of burning sample burning time

Green pellets production and applications in energy sector Chapter | 5

149

2.3.4 Chemical properties Chemical properties include the classical ultimate analysis, the elemental analysis, the surface morphology and rarely, chemical bonds and constituents, and crystalline nature of feedstock. These properties are generally applied for the raw biomass rather than the produced pellets. Ultimate analysis shows, as mentioned previously, the contents of hydrogen, nitrogen, sulfur, chlorine, oxygen, and carbon. Hydrogen, nitrogen, and carbon may be determined using an elemental analyzer, while sulfur may be determined using an atomic emission spectrometer. Surface morphology is used in portraying and distinguishing minerals and material formed together with surface components. Scanning electronic microscopy is used for viewing the surface morphology solid fuel to establish the suitability of fuel for a given application. Elemental analysis is used for quantitative determination of the major (Na, Ca, Mg, Fe, K) and minor elements (As, Cd, Cr, Cu, Hg, Ni, Pb, Zn). It is carried out according to established standards that include a previous digestion of the biomass sample in a closed container, using a mixture of acids and a microwave oven. The mineralization product is then analyzed by inductively coupled plasma mass spectrometry. Recently, X-ray fluorescence is also applied for the elemental analysis. The standard establishment is under progress. Chemical bonds, constituents and crystalline nature of feedstock. It may include acid-insoluble lignin determination according to defined methods. It could also include the oil content determination using Soxhlet extraction with hexane, according to defined standard. It may use Fourier transform spectroscopy or nuclear magnetic resonance spectroscopy to identify some components and chemical bonds in the raw feedstock. Some of these characteristics are given for a number of biomass pellets found in the scientific literature (Table 5.2).

3. Pellets combustion 3.1 Domestic use combustion technologies 3.1.1 Wood pellet stoves Small-scale pellet stoves are implemented in increasing trend due their high efficiency and lower emissions comparing to wood log stoves. In this heating system, the pellets are transported from the storage tank to the combustion chamber through an auger conveyor. The latter controls the pellets feeding rate according to the desired heating power. The primary air is provided through nozzles located in the stove grate bottom while a secondary preheated air is

Volatile matter VM (wt%)

Ash content (wt%)

High heating value, HHV (MJ/kg)

Mechanical durability (%)

Force of break (N)

Length (mm)

Diameter (cm)

Bulk density (kg/m3) wb

Moisture content (wt%)

Empty fruit bunches

22.9

6.1

575

9.05

71.7

5.75

14.18

92.7

563.2

Palm kernel shell

27.1  1.7

6.0

580.16  1.71

3.37

65.41

17.75

14.82

82

e

Oil palm fruit mesocarp

17.3

6.1

596

9.20

72.4

6.24

15.83

92.8

520.1

Sawdust

Al2O3 > activated carbon > ZrO2 > MgO. Generally a high surface area increases the catalytic activity but it may not always lead to a high value. Other properties of the catalyst such as Ni dispersion, Ni crystalline phase, as well as metal-support interaction have more significant influence [107]. The reactor wall can play a catalytic role in the process. For instance, the catalytic effect of the tubular reactor wall in Hastelloy C-276 (composed of Ni, as well as of Mo, Cr, Co, and other metals) have reduced the steam reforming reaction, leading to a decrease in hydrogen [62]. The comparison between Inconel and Hastelloy reactor has shown that the former strongly catalyzes the water gas shift reaction and produces more hydrogen, unlike the latter which has no effect on this reaction [108]. Table 6.4 summarizes the main investigations on the catalytic hydrothermal gasification. The parametric study of five key parameters, temperature (T), residence time (ts), pressure (P), initial biomass (C), and catalyst concentration (KOH) (Cat), has been combined in a single study to treat glycerol by gasification with supercritical water by I. Houcinat et al. [111]. A complete factorial plan has been used. The results are represented by the Pareto graph, a vertical bar graph in which values are plotted in decreasing order of relative frequency from left to right. Indeed, Pareto chart is useful for analyzing the variables having the greatest effect on a given response and allows taking a decision according to the objective of the study. Also, it can classify all the factors and their interaction and show the significant ones using the critical t-value (12.71 for the obtained models), where, the factors with absolute t value greater than this critical one are considered as significant. The results of the Pareto graph (Fig. 6.23) clearly show the important effect of the parameters studied and their interactions on hydrogen production according to the following order: the initial glycerol concentration, temperature, temperature and residence time, catalyst, temperature residence time, and pressure. The individual effect of each parameter is shown in Fig. 6.24 where the temperature and the catalyst had a significant positive effect, while the initial concentration of glycerol had a significant negative effect on the production of hydrogen by hydrothermal gasification.

5. Hydrothermal gasification challenges The main brake for the development of the hydrothermal gasification process at industrial scale is the energy and the security costs of the high temperature and pressure operations. Under supercritical conditions, the gases and minerals from the process can cause corrosion of the reactor building materials [71]. Some solutions have been proposed like a circulating flow reactor to prevent

Type of catalyst Heterogeneous catalyst

Biomass

Reactor type

Operating conditions

Catalysts




Source

Glucose

Batch

575e725 C, 28 MPa

Ni/Char coal

High selectivity for H2 production

[45]

Cellulose

Batch

400
C, 25 MPa, 20 min

Ni

1.2

[104]

Lignin Cellulose Lignin

Homogeneous catalyst

Maximum H2(mmol/g)

Waste water

0.17 Diamond cell Batch

Fluidized bed tubular

350
C, 16.5 MPa 3

600
C, 9 wt%, 0.05 g/cm , 15 min

480e540
C 25 MPa

Ni

74%

[109]

Ni

1

[103]

Cu

0.9

Fe

0.27

No catalyst

9.3

NaOH

12.6

KOH

15.5

K2CO3

14

Na2CO3

11.3

[51]

Fruit waste and food residue

Batch

600
C, 45 min, 23e25 MPa, 1: 10 biomass to water ratio

K2CO3

4.8 for coconuts

[47]

Fructose

Continuous reactor

700
C, 25 MPa, 60 s et 4 wt%

In absence of catalyst

3.26 mol/mol

[110]

KOH

10.67 mol/mol

NaOH

9.86 mol/mol

216 PART | IV Hydrogen production

TABLE 6.4 Different investigations on the catalytic hydrothermal gasification of biomass.

Hydrogen production by supercritical water gasification Chapter | 6

217

Pareto Chart of the Standardized Effects (response is H2, Alpha = 0,05)

Term

12.71 C A AB E ABD DE B ABC BCE BD CDE AE BE ABCE BCDE BCD ABCD ADE D CE ABE ACD BC ACDE AC AD ABDE BDE CD ACE

FactorName AT Bts CCi DP ECat

0

10

20 30 Standardized Effect

40

FIGURE 6.23 Pareto chart of the standardized effects for hydrogen production [111].

Main Effects Plot for H2 Fitted Means T(°C)

0.60

ts(min)

Ci(wt%)

0.55 0.50

Mean

0.45 0.40 458

542 P(MPa)

0.60

40

90

10

19

Cat(wt%)

0.55 0.50 0.45 0.40 23

27

0,06022

1,47500

FIGURE 6.24 Effect of the operating parameters on the hydrogen production (main effects plot) [111].

218 PART | IV Hydrogen production

corrosive species from reaching a solid surface, reducing temperature, or using other types of corrosion control methods such as coatings that reduce heat transfer [112]. The precipitation of inorganic salts produced or used as homogeneous catalysts can cause a modification of the chemical potentials of the medium and prevent the formation of a protective oxide, thus increasing the corrosion rate. On the other hand, the presence of mineral salts in a supercritical installation can generate local hydraulic disturbances [3]. However, Kruse et al. [113] have developed a salt water system as salt collectors to capture other salts and avoid reactor clogging. This phase has succeeded in capturing sodium and other alkaline salts that could be used to produce the fertilizers. A second alternative concerns the reactor design. The solutions proposed for supercritical installations are often standard materials such as stainless steel 316. These materials have the advantage of being affordable and easily manipulated as far as machinery is concerned. In areas with higher temperature and pressure conditions, more sophisticated materials are used such as nickel-based materials (Hastelloy C-276, Inconel 625) [114,115]. Each reactor has its operating constraints, and when it comes to a continuous process, the dry matter content of the biomass suspension must not exceed the pumping limits due to a possible pump clogging. On the other hand, high dry matter content leads to higher gas production, which increases the energy efficiency and the process profitability [71]. Data from the literature show that the process of converting biomass into supercritical water has significant development potential. It will be able to ensure a more complex recovery of the inputs by simultaneously producing more hydrogen. Numerous research programs are still necessary to ensure a good level of maturity in these processes and to open them to their large-scale application. Without neglecting the hydrogen separation phase at the outlet of the reactors which should be treated more deeply. The new reactor design should allow the control of the very rapid rise to the supercritical state, homogenization, good heat transfer, and a residence time long enough to refine the reactions, etc.

6. Conclusion The supercritical water gasification is a promising technique for producing recoverable gases (H2, CH4, CO2, CO, etc.) from different biomasses that have been treated in different types of reactors to produce hydrogen. Mainly most of the studies are carried out on a laboratory scale, exceeding by far the number of works developed on a pilot plant scale. Despite the large number of studies carried out in hydrothermal gasification, no industrial-scale reactor design has been carried out until today. This difficulty is due to the constraints linked to the physicochemical properties of water and the high temperatures and pressures operating conditions. In the

Hydrogen production by supercritical water gasification Chapter | 6

219

other hand, the high concentrations of biomass and catalysts increase the salts deposition of certain aggressive species on the wall of the reactor. In the long term, all these constraints cause the reactor corrosion. However, the high temperature reached in hydrothermal gasification remains low compared to other thermochemical processes such as conventional gasification, pyrolysis, and combustion, while using wet biomass, which makes the process economically more advantageous by eliminating the drying step. The literature clearly shows that the hydrogen production using gasification process in supercritical water is strongly influenced by several parameters such as the type of reactor and the biomass. The operating conditions also have a great influence on the yields of the gases produced and the efficiency of the operation such as temperature, residence time, pressure, biomass concentration, presence, and catalyst type.

References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10]

[11] [12] [13] [14] [15]

J. Yanik, S. Ebale, A. Kruse, Biomass gasification in supercritical water: part 1. Effect of the nature of biomass, Fuel 86 (15) (2007) 2410e2415. A.M.D. Douette, S.Q. Turn, W. Wang, V.I. Keffer, Experimental investigation of hydrogen production from glycerin reforming, Energy Fuels 21 (6) (2007) 3499e3504. A. Bahadar, M. Bilal Khan, Progress in energy from microalgae: a review, Renew. Sustain. Energy Rev. 27 (2013) 128e148. D.B. Levin, L. Pitt, M. Love, Biohydrogen production: prospects and limitations to practical application, Int. J. Hydrogen Energy 29 (2) (2003) 173e185. K. Nath, D. Das, Hydrogen from biomass, Curr. Sci. 85 (3) (2003) 265e271. L.R. Berg, P.H. Raven, D.M. Hassenzahl, Environnement, De Boeck Supe´rieur, 2009. D. Ballerini, Les biocarburants: re´pondre aux de´fis e´nerge´tiques et environnementaux des transports, Editions Technip, 2011. R. Moletta, Le traitement des de´chets, Editions Tec & Doc Lavoisier, 2009. A. Kumar, D. Jones, M. Hanna, Thermochemical biomass gasification: a review of the current status of the technology, Energies 2 (3) (2009) 556e581. A. Kruse, A. Gawlik, Biomass conversion in water at 330410 C and 3050 MPa, Identification of key compounds for indicating different chemical reaction pathways, Ind. Eng. Chem. Res. 42 (2) (2003) 267e279. J.C. Ruiz, O. Boutin, Gaze´ification de biomasse en eau supercritique [Biomass gasification in supercritical water], Technique de l’inge´nieur, 2013. www.scholar.google.com (advanced research using “allintitle: Hydrogen production supercritical gasification”, 01/04/2020). F. Zhen, Rapid Production of Micro-and Nano-Particles Using Supercritical Water, Springer Science & Business Media, 2010. C. Le´cuyer, L’eau sur la terre: proprie´te´s physicochimiques et fonctions biologiques, ISTE Group, 2014. L.D. Landau, E.M. Lifshitz, Fluid Mechanics. Fluid Mechanics, second ed., Pergamon, Oxford, 1987, 1987.

220 PART | IV Hydrogen production [16] Y. Cui, S.V. Olesik, High-performance liquid chromatography using mobile phases with enhanced fluidity, Anal. Chem. 63 (17) (1991) 1812e1819. [17] https://upload.wikimedia.org/wikipedia/commons/3/34/Phase-diag2.svg. [18] V. Anikeev, M. Fan, Supercritical Fluid Technology for Energy and Environmental Applications, Newnes, 2013. [19] R.V. Eldik, C.D. Hubbard, Chemistry under extreme or non-classical conditions, J. Chem. Educ. 74 (1997) 764. [20] R.F. Susanti, B. Veriansyah, J.D. Kim, Continuous supercritical water gasification of isooctane: a promising reactor design, Int. J. Hydrogen Energy 35 (5) (1970) 1957e1970. [21] M. Osada, O. Sato, M. Watanabe, Water density effect on lignin gasification over supported noble metal catalysts in supercritical water, Energy Fuels 20 (3) (2006) 930e935. [22] A. LoppinetSerani, C. Aymonier, F. Cansell, Current and foreseeable applications of supercritical water for energy and the environment, ChemSusChem 1 (6) (2008) 486e503. Chemistry & Sustainability Energy & Materials. [23] S.H. Townsend, S.M.A. Abraham, G.L. Huppert, Solvent effects during reactions in supercritical water, Ind. Eng. Chem. Res. 27 (1) (1988) 143e149. [24] M. Hodes, P.A. Marrone, G.T. Hong, Salt precipitation and scale control in supercritical water oxidationdPart A: fundamentals and research, J. Supercrit. Fluids 29 (3) (2004) 265e288. [25] H. Weinga¨rtner, E.U. Franck, Supercritical water as a solvent, Angew. Chem. Int. Ed. 44 (18) (2005) 2672e2692. [26] P. Krammer, H. Vogel, Hydrolysis of esters in subcritical and supercritical water, J. Supercrit. Fluids 16 (3) (2000) 189e206. [27] W. Yu, M. Qian, Etude de proce´de´s de conversion de biomasse en eau supercritique pour l’obtention d’hydroge`ne. Application au glucose, glycerolet bio-glycerol, The`se de doctorat, 2012. [28] G. Brunner, Hydrothermal and Supercritical Water Processes, Elsevier, 2014. [29] N. Benmakhlouf, N. Outili, A.-H. Meniai, Modeling and optimization of phenol hydrothermal oxidation in supercritical water, Int. J. Hydrogen Energy 42 (17) (2017) 12926e12932. [30] W. Wagner, H.-J. Kretzschmar, International Steam Tables-Properties of Water and Steam Based on the Industrial Formulation IAPWS-IF97: Tables, Algorithms, Diagrams, and CDROM Electronic Steam Tables-All of the Equations of IAPWS-IF97 Including a Complete Set of Supplementary Backward Equations for Fast Calculations of Heat Cycles, Boilers, and Steam Turbines, Springer Science & Business Media, 2007. [31] M. Modell, Gasification and liquefaction of forest products in supercritical water, in: Fundamentals of Thermochemical Biomass Conversion, Springer, Dordrecht, 1985, pp. 95e119. [32] T. Minowa, T. Ogi, Hydrogen production from cellulose using a reduced nickel catalyst, Catal. Today 45 (1e4) (1998) 411e416. [33] S. Guo, L.J. Guo, C. Cao, Hydrogen production from glycerol by supercritical water gasification in a continuous flow tubular reactor, Int. J. Hydrogen Energy 37 (7) (2012) 5559e5568. [34] S. Guo, L.J. Guo, J. Yin, Supercritical water gasification of glycerol: intermediates and kinetics, J. Supercrit. Fluids 78 (2013) 95e102. [35] I. Houcinat, N. Outili, A.-H. Meniai, E. Weiss-Hortala, Supercritical water gasification of glycerol for Hydrogen production using response surface methodology, in: 10th

Hydrogen production by supercritical water gasification Chapter | 6

[36] [37] [38]

[39] [40]

[41]

[42] [43] [44] [45] [46] [47] [48] [49] [50]

[51]

[52]

[53]

221

International Renewable Energy Congress, March 2019, Sousse, Tunisia, IREC, 2019, pp. 1e6, https://doi.org/10.1109/IREC.2019.8754520. L. Qadariyah, S. Machmudah, M. Sasaki, Degradation of glycerol using hydrothermal process, Bioresour. Technol. 102 (19) (2011) 9267e9271. A. Kruse, Supercritical water gasification, Biofuels Bioprod. Biorefining 2 (5) (2008) 415e437. Innovation for a sustainable economy. A. Loppinet-Serani, C. Aymonier, F. Cansell, Current and foreseeable applications of supercritical water for energy and the environment, ChemSusChem 1 (6) (2008) 486e503. Chemistry & Sustainability Energy & Materials. D. Pouzet, Production durable de biomasse-La lignocellulose des poace´es, E´ditions Quae, 2011. H. Panda, Handbook on Coal, Lignin, Wood and Rosin Processing: Biodegradation of Cellulose, Biodegradation of Hemicellulose, Biodegradation of Lignin, Business Guidance for Coal and Lignin Processing, Business Guidance for Wood and Rosin Processing, Business Guidance to Clients, Business Plan for a Startup Business, Business Start-Up, Chemical Composition of Rosin, Chemical Modification of Wood Fiber, NIIR Project Consultancy Services, 2016. I. Didderen, J. Destain, P. Thonart, Le bioe´thanol de seconde ge´ne´ration: la production d’e´thanol a` partir de biomasse lignocellulosique, Presses agronomiques de Gembloux, 2008. F.G. Calvo-Flores, J.A. Dobado, J. Isac-Garcı´aet al., Lignin and Lignans as Renewable Raw Materials: Chemistry, Technology and Applications, John Wiley & Sons, 2015. M. Rai, S.S. DaSilva (Eds.), Nanotechnology for Bioenergy and Biofuel Production, Springer, 2017. S.S. Alves, J.L. Figueiredo, Pyrolysis kinetics of lignocellulosic materials by multistage isothermal thermogravimetry, J. Anal. Appl. Pyrol. 13 (1e2) (1988) 123e134. T. Yoshida, Y. Matsumura, Gasification of cellulose, Xylan, and Lignin mixtures in supercritical water, Ind. Eng. Chem. Res. 40 (23) (2001) 5469e5474. A. Demirbas, Hydrogen-rich gas from fruit shells via supercritical water extraction, Int. J. Hydrogen Energy 29 (12) (2004) 1237e1243. S. Nanda, J. Isen, A.K. Dalai, J.A. Kozinski, Gasification of fruit wastes and agro-food residues in supercritical water, Energy Convers. Manag. 110 (2016) 296e306. E. Demirel, N. Ayas, Hydrogen production by supercritical water gasification of fruit pulp in the presence of Ru/C, Int. J. Hydrogen Energy 41 (19) (2016) 8073e8083. N. Ding, R. Azargohar, A.K. Dalai, et al., Catalytic gasification of cellulose and pinewood to H2 in supercritical water, Fuel 118 (2014) 416e425. F. Safari, N. Javani, Z. Yumurtaci, Hydrogen production via supercritical water gasification of almond shell over algal and agricultural hydrochars as catalysts, Int. J. Hydrogen Energy 43 (2) (2018) 1071e1080. Y. Chen, L.J. Guo, W. Cao, Hydrogen production by sewage sludge gasification in supercritical water with a fluidized bed reactor, Int. J. Hydrogen Energy 38 (29) (2013) 12991e12999. K. Kang, R. Azargohar, A.K. Dalai, et al., Noncatalytic gasification of lignin in supercritical water using a batch reactor for hydrogen production: an experimental and modeling study, Energy Fuels 29 (3) (2015) 1776e1784. R. Abdul, J. Guozhao, M. Asif, Catalytic gasification of algal biomass for hydrogen-rich gas production: parametric optimization via central composite design, Energy Convers. Manag. 158 (2018) 235e245.

222 PART | IV Hydrogen production [54] F.L. Pacheco de Resende, Supercritical Water Gasification of biomass.ProQuest, Ann Arbor, PhD dissertation, University of Michigan, USA, 2009. [55] R.R. Aulus, B. Marija, Catalytic Steam Reforming of Ethanol for Hydrogen Production: Brief Status, Chemical Industry & Chemical Engineering Quarterly, 2016. [56] W. Gong, Z. Zhou, Y. Liu, et al., Hydrogen production and phosphorus recovery via supercritical water gasification of sewage sludge in a batch reactor, Waste Manag. 96 (2019) 198e205. [57] J. Zhu, C.L. Xiaoyan, et al., Catalytic supercritical water gasification of glucose with insitu generated nickel nanoparticles for hydrogen production, Int. J. Hydrogen Energy 44 (38) (2019) 21020e21029. [58] W.A. Bassett, A.H. Shen, M. Bucknum, A new diamond anvil cell for hydrothermal studies to 2.5 GPa and from 190 to 1200
C, Rev. Sci. Instrum. 64 (8) (1993) 2340e2345. [59] Y. Graz, S. Bostyn, T. Richard, Hydrothermal conversion of Ulva macro algae in supercritical water, J. Supercrit. Fluids 107 (2016) 182e188. [60] R. Hashaikeh, I.S. Butler, J.A. Kozinski, Selective promotion of catalytic reactions during biomass gasification to hydrogen, Energy Fuels 20 (6) (2006) 2743e2747. [61] B.R. Pinkard, D.J. Gorman, K. Tiwari, E.S. Rasmussen, J.C. Kramlich, P.G. Reinhall, I.V. Novosselov, Supercritical water gasification: practical design strategies and operational challenges for lab-scale, continuous flow reactors, Heliyon 5 (2) (2019) 01269. [62] P. Basu, V. Mettanant, Biomass gasification in supercritical water–A review, Int. J. Chem. React. Eng. 7 (1) (2009). [63] A.E.M. EmhemmedYoussef, Supercritical Water Gasification of Biomass & Biomass Model Compounds, PhD Thesis, University of Ontario Canada, 2011. [64] A. Kruse, M. Faquir, Mohamed, Hydrothermal biomass gasificationeeffects of salts, backmixing and their interaction, Chem. Eng. Technol. 30 (6) (2007) 749e754. Industrial Chemistry-Plant Equipment-Process Engineering-Biotechnology. [65] Y.J. Lu, H. Jin, L.J. Guo, Hydrogen production by biomass gasification in supercritical water with a fluidized bed reactor, Int. J. Hydrogen Energy 33 (21) (2008) 6066e6075. [66] A. Kruse, Hydrothermal biomass gasification, J. Supercrit. Fluids 47 (2009) 391e399. [67] Y. Matsumura, T. Minowa, B. Potic, Biomass gasification in near-and super-critical water: status and prospects, Biomass Bioenergy 29 (4) (2005) 269e292. [68] Z. Ge, S. Guo, L.J. Guo, Hydrogen production by non-catalytic partial oxidation of coal in supercritical water: explore the way to complete gasification of lignite and bituminous coal, Int. J. Hydrogen Energy 38 (29) (2013) 12786e12794. [69] Z. Cheng, H. Jin, S. Liu, Hydrogen production by semicoke gasification with a supercritical water fluidized bed reactor, Int. J. Hydrogen Energy 41 (36) (2016) 16055e16063. [70] M.J. Antal, S.G. Allen, D. Schulman, Biomass gasification in supercritical water, Ind. Eng. Chem. Res. 39 (11) (2000) 4040e4053. [71] Z. Ge, S. Guo, L.J. Guo, Hydrogen production by catalytic gasification of coal in supercritical water with alkaline catalysts: explore the way to complete gasification of coal, Int. J. Hydrogen Energy 39 (34) (2014) 19583e19592. [72] F.J.G. Ortiz, P. Ollero, A. Serrera, Thermodynamic study of the supercritical water reforming of glycerol, Int. J. Hydrogen Energy 36 (15) (2011) 8994e9013. [73] L. Ferreira-Pinto, A.C. Feirhrmann, M.L. Corazza, Hydrogen production and TOC reduction from gasification of lactose by supercritical water, Int. J. Hydrogen Energy 40 (36) (2015) 12162e12168. [74] F.L.P. Resende, M.E. Neff, P.E. Savage, Noncatalytic gasification of cellulose in supercritical water, Energy Fuels 21 (6) (2007) 3637e3643.

Hydrogen production by supercritical water gasification Chapter | 6

223

[75] F.L.P. Resende, S.A. Fraley, M.J. Berger, Noncatalytic gasification of lignin in supercritical water, Energy Fuels 22 (2) (2008) 1328e1334. [76] I.G. Lee, M.S. Kim, S.K. Ihm, Gasification of glucose in supercritical water, Ind. Eng. Chem. Res. 41 (5) (2002) 1182e1188. [77] Houcinat, Ibtissem, N. Outili, A.H. Meniai, Optimization of gas production and efficiency of supercritical glycerol gasification using response surface methodology, Biofuels 9 (5) (2018) 625e633. [78] W. Bu¨hler, E. Dinjus, H.J. Ederer, A. Kruse, et C. Mas, Ionic reactions and pyrolysis of glycerol as competing reaction pathways in near- and supercritical water, J. Supercrit. Fluids 22 (1) (2002) 37e53. [79] J.D. Taylor, C.M. Herdman, B.C. Wu, Hydrogen production in a compact supercritical water reformer, Int. J. Hydrogen Energy 28 (11) (2003) 1171e1178. [80] R. Cherad, J.A. Onwudili, P.T. Williams, A parametric study on supercritical water gasification of Laminaria hyperborea: a carbohydrate-rich macroalga, Bioresour. Technol. 169 (2014) 573e580. [81] S. Nanda, S.N. Reddy, D.V.N. Vo, Catalytic gasification of wheat straw in hot compressed (subcritical and supercritical) water for hydrogen production, Energy Sci. Eng. 6 (5) (2018) 448e459. [82] D. Yamaguchi, P.J. Sanderson, S. Lim, Supercritical water gasification of Victorian brown coal: experimental characterization, Int. J. Hydrogen Energy 34 (8) (2009) 3342e3350. [83] A.G. Chakinala, D.W.F. Brilman, W.P.M. Van Swaaij, Catalytic and non-catalytic supercritical water gasification of microalgae and glycerol, Ind. Eng. Chem. Res. 49 (3) (2009) 1113e1122. [84] A.J. Byrd, K.K. Pant, R.B. Gupta, Hydrogen production from glycerol by reforming in supercritical water over Ru/Al2O3 catalyst, Fuel 87 (13e14) (2008) 2956e2960. [85] H. Jin, Y. Chen, Z. Ge, Hydrogen production by Zhundong coal gasification in supercritical water, Int. J. Hydrogen Energy 40 (46) (2015) 16096e16103. [86] C. Cao, L. Guo, J. Yin, Supercritical water gasification of coal with waste black liquor as inexpensive additives, Energy Fuels 29 (1) (2014) 384e391. [87] M.A. Ebrahimi-Nik, M. Almassi, M.J. Sheikhdavoodi, A. Kruse, H. Bahrami, Gasification of sugarcane bagasse in supercritical water: effect of pressure and reaction time, in: The 9th International Energy Conference, Ferdowsi University of Mashhad, Iran, 2013. [88] A. Kruse, P. Maniam, F. Spieler, Influence of proteins on the hydrothermal gasification and liquefaction of biomass. 2. Model compounds, Ind. Eng. Chem. Res. 46 (1) (2007) 87e96. [89] H. Bichat, P. Mathis, La Biomasse, E´nergie d’avenir? Editions Quae, 2013. [90] J.B. Gadhe, R.B. Gupta, Hydrogen production by methanol reforming in supercritical water: suppression of methane formation, Ind. Eng. Chem. Res. 44 (13) (2005) 4577e4585. [91] Q. Yan, L. Guo, Y. Lu, Thermodynamic analysis of hydrogen production from biomass gasification in supercritical water, Energy Convers. Manag. 47 (11e12) (2006) 1515e1528. [92] A.A. Peterson, F. Vogel, R.P. Lachance, Thermochemical biofuel production in hydrothermal media: a review of sub-and supercritical water technologies, Energy Environ. Sci. 1 (1) (2008) 32e65. [93] A. Kruse, D. Meier, P. Rimbrecht, Gasification of pyrocatechol in supercritical water in the presence of potassium hydroxide, Ind. Eng. Chem. Res. 39 (12) (2000) 4842e4848. [94] W. Cao, C. Cao, L. Guo, Gasification of diosgenin solid waste for hydrogen production in supercritical water, Int. J. Hydrogen Energy 42 (15) (2017) 9448e9457.

224 PART | IV Hydrogen production [95] J. Yanik, S. Ebale, A. Kruse, Biomass gasification in supercritical water: II. Effect of catalyst, Int. J. Hydrogen Energy 33 (17) (2008) 4520e4526. [96] F. Xia, S. Tian, P. Ning, Catalytic gasification of lignite with KOH in supercritical water, Can. J. Chem. Eng. 92 (3) (2014) 421e425. [97] R. Muangrat, J.A. Onwudili, P.T. Williams, Alkali-promoted hydrothermal gasification of biomass food processing waste: a parametric study, Int. J. Hydrogen Energy 35 (14) (2010) 7405e7415. [98] F. Yang, M.A. Hanna, D.B. Marx, Optimization of hydrogen production from supercritical water gasification of crude glyceroldbyproduct of biodiesel production, Int. J. Energy Res. 37 (13) (2013) 1600e1609. [99] R. Muangrat, J.A. Onwudili, P.T. Williams, Influence of alkali catalysts on the production of hydrogen-rich gas from the hydrothermal gasification of food processing waste, Appl. Catal. B Environ. 100 (3e4) (2010) 440e449. [100] A. Sinaǧ, A. Kruse, J. Rathert, Influence of the heating rate and the type of catalyst on the formation of key intermediates and on the generation of gases during hydropyrolysis of glucose in supercritical water in a batch reactor, Ind. Eng. Chem. Res. 43 (2) (2004) 502e508. [101] M. Watanabe, H. Inomata, K. Arai, Catalytic hydrogen generation from biomass (glucose and cellulose) with ZrO2 in supercritical water, Biomass Bioenergy 22 (5) (2002) 405e410. [102] G.J. Dileo, M.E. Neff, P.E. Savage, Gasification of guaiacol and phenol in supercritical water, Energy Fuels 21 (4) (2007) 2340e2345. [103] F.L.P. Resende, P.E. Savage, Effect of metals on supercritical water gasification of cellulose and lignin, Ind. Eng. Chem. Res. 49 (6) (2010) 2694e2700. [104] T. Yoshida, Y. Oshima, Y. Matsumura, Gasification of biomass model compounds and real biomass in supercritical water, Biomass Bioenergy 26 (1) (2004) 71e78. [105] D.C. Elliott, Catalytic hydrothermal gasification of biomass, Biofuels Bioprod. Biorefining 2 (3) (2008) 254e265. [106] B.F. Tapah, Processing of Organic Waste by Catalytic Supercritical Water Gasification, PhD Thesis, University of Birmingham Great Britain, 2014. [107] K. Kang, Hydrogen Production from Supercritical Water Gasification of Lignin, Cellulose, and Other Biomass Residues, PhD Thesis, University of Saskatchewan, Saskatoon, SK, Canada, 2016. [108] D. Yu, M. Aihara, M.J. Antal Jr., Hydrogen production by steam reforming glucose in supercritical water, Energy Fuels (5) (1993) 574e577. [109] Z. Fang, T. Minowa, R.L. Smith, Liquefaction and gasification of cellulose with Na2CO3 and Ni in subcritical water at 350
C, Ind. Eng. Chem. Res. 43 (10) (2004) 2454e2463. [110] S. Nanda, S.N. Reddy, A.K. Dalai, Subcritical and supercritical water gasification of lignocellulosic biomass impregnated with nickel nanocatalyst for hydrogen production, Int. J. Hydrogen Energy 41 (9) (2016) 4907e4921. [111] I. Houcinat, N. Outili, E. Weiss-Hortala, A.H. Meniai, Parametric study via full factorial design for glycerol supercritical gasification, Biofuels (2019) 1e14. [112] P.A. Marrone, G.T. Hong, Corrosion control methods in supercritical water oxidation and gasification processes, J. Supercrit. Fluids 51 (2009) 83e103.

Hydrogen production by supercritical water gasification Chapter | 6

225

[113] A. Kruse, D. Forchheim, M. Gloede, F. Ottinger, J. Zimmermann, Brines in supercritical biomass gasification: 1. Salt extraction by salts and the influence on glucose conversion, J. Supercrit. Fluids 53 (2010) 64e71. [114] D.B. Mitton, J.H. Yoon, J.A. Cline, H.S. Kim, N. Eliaz, R.M. Latanision, Corrosion behaviour of Nickel based alloys in supercritical water oxidation systems, Ind. Eng. Chem. Res. 39 (2000) 4689. [115] D.B. Mitton, J.A. Cline, N. Eliaz, R.M. Latanision, An overview of the current understanding of corrosion in SCWO systems for the destruction of hazardous waste products, Mater. Technol. Adv. Perform. Mater. 16 (2001) 44.

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Part V

Wind energy

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Chapter 7

Wind energy in Jordan and Palestine: current status and future perspectives Adel Juaidi1, Ramez Abdallah1, Osama Ayadi2, 6, Tareq Salameh3, Afif Akel Hasan4 and Ahmad Ramahi5 1

Mechanical & Mechatronics Engineering Department, Faculty of Engineering & Information Technology, An-Najah National University, Nablus, Palestine; 2Mechanical Engineering Department, The University of Jordan, Amman, Jordan; 3Department of Sustainable and Renewable Energy Engineering, College of Engineering, University of Sharjah, Sharjah, United Arab Emirates; 4Mechanical & Mechatronics Engineering Department, Birzeit University, Birzeit, Palestine; 5Industrial Engineering Department, An-Najah National University, Nablus, Palestine; 6 Renewable Energy Technology Department, Applied Science Private University, Amman, Jordan

1. Introduction 1.1 Country overviewdJordan The Hashemite Kingdom of Jordan “Jordan” is located in the Middle East on a cross-road of Asia, Africa, and Europe; it lies at 32
N-latitude and 36
Elongitude [1]. Jordan has 12 governorates; it is bordered by Syria north, Palestine west, Iraq east, and Saudi Arabia north and east as shown in Fig. 7.1 below. Jordan is comparatively a modern country; got its independence in 1946. Jordan has some natural resources such as potash, limestone, phosphate, and marble. Table 7.1 lists some relevant statistics and indicators about Jordan. Jordan is located in the western part of Asia; it has a total area of 89,318 km2 including the Dead Sea, around 75% of the land has a desert climate with annual precipitation not more than 200 mm (average 50 mm), the temperature may reach 40
C summer day, whereas during winter the wind is cold and dry. On the other hand, the climate of the western part of Jordan can be considered Mediterranean climate in general; dry-hot in summer, cool-rainy in winter; the rainy season extends between October to early May. The Hashemite Kingdom has four topographical regions (1) Jordan Valley: has two subregions; the northern part which has the Jordan River and the southern part which contains Renewable Energy Production and Distribution. https://doi.org/10.1016/B978-0-323-91892-3.00006-6 Copyright © 2022 Elsevier Inc. All rights reserved.

229

230 PART | V Wind energy

FIGURE 7.1 Map of Jordan [2].

Araba Valley, while the Dead Sea almost in the middle; the variation in altitude is 32 below sea level (BSL) in the north, the Dead Sea is 392 m BSL, and almost sea level in the south. (2) East Highland: this is a mountainous region stretches north to south, located on the eastern edge of the Jordan Valley, the altitude ranges between 600 and 1500 m above sea level (ASL). (3) Plain Plateau: stretches north to south and lies in the eastern direction of the easthighland. (4) Semi-Arid (Badia) area: it consists of about 87% of the Jordanian land; it occupies the northern and south-eastern territories of the plateau area, the altitude in this region varies from 600 to 900 m ASL [3].

Wind energy in Jordan and Palestine Chapter | 7

231

TABLE 7.1 A list of relevant statistics and indicators for Jordan and Palestine [1,32]. Indicator

Jordan

Palestine

Area (km )

89,318 (2019) [Jordan in Figures Year Book 2019]

6025 [Palestine in Figures, Palestinian central Bureau of Statistics, 2020]

Population

10,554,000 (2019) [Jordan in Figures Year Book 2019]

5,164,173 (2020) [Palestine in Figures, Palestinian Central Bureau of Statistics, 2020]

GDP per capita

4217 $ (2019) [Jordan in Figures Year Book 2019]

3378.3 $ (2019) [Palestine in Figures, Palestinian Central Bureau of Statistics, 2020]

Unemployment rate

19.1 (2019) [Jordan in Figures Year Book 2019]

25.9 (2020) [Palestine in Figures, Palestinian Central Bureau of Statistics, 2020]

Monthly expenditure per capita

298 $ (2019) [Department of statistics, 2019]

240 $ (2017) [Palestinian Central Bureau of Statistics. 2020]

Average household electricity consumption

314 kWh per month (2019) [Jordan in Figures Year Book 2019]

WB:366 KWh per month GS:265 kWh/month (2015) [Palestinian Central Bureau of Statistics. 2020]

Annual global horizon. Irradiation

1400-2300 kWh/m2 [Saad S. et al., Solar radiation map of Jordan governorates]

2000 kWh/m2 [Palestinian Central Bureau of Statistics. 2020]

% of household with solar heater

12.2 (2019) [Jordan in Figures Year Book 2019]

56.2 (2019) [Palestine in Figures, Palestinian Central Bureau of Statistics, 2020]

Total national emissions CO2 eq.

22.74 millions of tons (2016) CO2 emissionsJordan, 2016

4.53 millions of tons (2018) [Palestine in Figures, Palestinian Central Bureau of Statistics, 2020]

2

The direction of the wind in Jordan is in general westerly and southwesterly; however, hot and dry storms loaded with dust usually blow on the southern regions and extends toward the north coming from the south-eastern of Saudi Arabia; such storms exist toward the beginning and the end of summer and may continue for few days. The temperature at Amman, the capital of Jordan, varies from 8 to 26
C, and at Aqabah, in the southern part of Jordan, varies between 16 and 33
C. The average annual rainfall is about

232 PART | V Wind energy

400 mm in the north-western part of the Jordan Valley, and about 355 mm in East Highland where snow occasionally occurs. The annual average relative humidity in Amman is 50.5% and in Aqabah 24% [3e5].

1.2 Country overviewdPalestine Palestine lies on the west coast of Asia on the Mediterranean Sea. It lies between 34
200 and 35
300 east longitude and between 31
100 and 32
300 north latitude [6]. Palestine has two unconnected parts; the West Bank (WB) and Gaza Strip (GS) as shown in Fig. 7.2, it has 16 governorates; 11 governorates in WB (Nablus, Qalqilya, Tubas, Salfit, Tulkarm, Jenin, Jericho, Ramallah and al-Bireh, Bethlehem, Hebron, and Jerusalem) and five governorates in GS (North Gaza, Gaza, Deir al-Balah, Khan Yunis, and Rafah). WB is bordered by Jordan on the east. GS is located directly on the coastline and has around 11km southern borders with Egypt and is separated from WB. The political situation in Palestine is complex; the Palestinian National Authority (PNA) has

FIGURE 7.2 PalestinedWest Bank and Gaza Stripdand governorates [7].

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233

limited selfgovernance of parts of Palestine. According to Oslo Accords, the Palestinian territories (PT) are classified into three unconnected administrative areas with complex geographical distribution; A, B, and C. In area A, which is 17.7% of WB, PNA is responsible for the administration and security; in area B, about 18.3% of WB, PNA is responsible for the civil administration, and the security is partially controlled by PNA. In area C, which is 61% of the WB, PNA is not responsible for both the civil administration and the security; such control over the WB obstacles most development initiatives in Palestine. A list of relevant statistics and indicators about Palestine is given in Table 7.1. Palestine lies in a subtropical area and is much affected by the Mediterranean climate [6,8]. The general characteristic of Palestine climate is hot-dry in summer and cool-rainy in winter. The rainy months are October to early May, while the heavy rain is in December through February. The Palestinian territories have five topographical regions [9]: (1) Jordan Valley: in the east part of WB, the altitude in this area ranges between 200 and 300 m BSL to 100e200 m ASL. This area is approximately flat with mild slopes of less than 3 degrees. (2) Eastern hills: lies along the eastern side of WB and west to the Jordan valley, the altitude in this region is 200e800 m ASL with terrain slope up to more than 15 degrees. (3) Central Highlands: about 120 km south to north; extending from Hebron to Tubas, this area is mountainous; in some places in Nablus, Ramallah, and Hebron the altitude reaches more than 1000 m ASL. It comprises the largest area of WB. (4) Western WB: Comprise Jenin, Tulkarem, and Qalqilya districts, the altitude in this region is 100e300 m ASL and moderate-slope terrain. (5) GS: flat in general, some sand dunes exist close to the coast; the altitude in this area is up to 120 m ASL. The altitude variations in WB result in climatic variations like the average rainfall and wind speed. The average rainfall in WB varies between 15 and 600 mm; this of course affects the diversity of the agricultural modality in the WB [8]. The variation in the average wind speed in the hilly areas in WB is between 4 and 8 m/s [10]. The mountains in WB act as a barrier to the blowing of the western moist air coming from the Mediterranean Sea. The Mediterranean has more influence on the north-western region of WB because there are no mountains to repel the wind; hence, the wind flows easily to the Jordan valley. The sea has an influence on the western of the WB as well but does not penetrate deep into the WB due to the highlands that block the wind. As the distance between the sea and the WB increases in the south, the sea effect becomes less in the southern regions. The climate of the southern region is influenced by the adjacent Negev Desert and the nearby Arabian Desert; storms loaded with sand and dust blow on the southern of the Jordan valley mainly during spring and result in temperature increase, air-humidity decrease, and air pollution. The average daily temperature in WB is 8e23
C, and the relative humidity 51%e83%. However, during some periods in winter the temperature drops to near zero, which requires high heating loads. Similarly, in some periods in

234 PART | V Wind energy

summer the temperature reaches around 37
C, which requires cooling in summer; an exception is the Jordan valley area which only needs cooling in summer. The GS is a coastal plain that lies directly on the eastern coast of the Mediterranean about 41 km along the coastline and 6e12 km wide. Its climate is hot-dry in summer and cold-rainy in winter [10]. The average daily temperature is 13.3e25.4
C, and the relative humidity ranges between 67% and 75% [11,12]. The average wind speed in GS is between 2.5 and 3.5 m/s [10]. The altitude in GS varies between zero and less than 125 m ASL with some dunes exist in the south nearby the coast.

1.3 Energy status and renewable energy in Jordan 1.3.1 Energy status In contrast to many surrounding Arab countries, Jordan has an extreme lack of conventional energy resources. In 2017, 94% of total primary energy resources were imported, which, in fact, is a slight improvement over previous years [13e16]. As proven in recent years, this dependence on imports poses a risk to the security of supply and cost of energy. Furthermore, it made apparent the immediate need for energy security in a historically volatile region. Due to these circumstances, the Ministry of Energy and Mineral Resources, Jordan (MEMR) set an ambitious goal to reach 40% of energy production from domestic resources by 2025 as part of the Updated National Energy Strategy 2015e25 [13,17,18]. In 2017, the vast majority of Total Primary Energy Consumption was supplied by fossil fuels, specifically oil and natural gas. Renewable energy made up only 5% of the mix [19]. When considering only electricity generation the renewable contribution rises to 7%, with 80% being covered by natural gas [19,20]. The electricity generation by fuel for 2019 is shown in Fig. 7.3. The majority of the fossil fuel power plants are combined cycle gas turbine (CCGT) plants with natural gas as the primary fuel and fuel oil as a backup or alternative fuel. A full list of current installed capacity can be found in Table 7.2. The total installed generating capacity is estimated to be 5500 MW. An additional new project, and a major goal of MEMR, is the increasing incorporation of oil shale into the energy mix. Attarat Power Plant is a 470 MW oil shale direct combustion power plant currently under construction, with expected completion in 2021. In that year, oil shale is intended to contribute 15% of the energy mix according to the National Energy Strategy [13]. The National Energy Strategy also aims for a 5% coal contribution to Total Primary Energy by 2025. Currently, only a 30 MW coal-fired power plant exists in the Kingdom and all coal must be imported [22].

Wind energy in Jordan and Palestine Chapter | 7

235

Electrical Energy Production by Fuel (2019) 0.4%

87.9%

11.7%

Heavy fuel 0.4%

Natural Gas 87.9%

Renewable Energy 11.7%

FIGURE 7.3 Electrical energy production by fuel in Jordan (2019). Based on [20].

1.3.2 Renewable energy resources Over the course of several years, studies on Jordan’s renewable energy resources, particularly wind potential, have revealed that the country has vast potential for wind and other renewable energy resources. Accordingly, Jordan has already set plans to have energy generated from renewable energy sources, including wind [6,23]. Jordan has abundant solar resources with an average global solar irradiation of 2.01 MWh/m2/year and 3311 annual sunshine hours [24]. Wind power potential is also significant with wind speeds reaching 7.5 m/s in the north and west, sometimes up to 11.5 m/s in the highlands. According to Ref. [25], in 2015 there were 851 MW of PV and 283 MW of wind connected to the grid, with another 596 MW PV and 334 MW wind under construction. Other renewable energy sources in use or under development include hydropower and biomass. In addition to King Talal Dam, Aqaba Thermal Power Station has 6 MW hydropower turbines incorporated into its seawater cooling system and As-Samra Wastewater Treatment Plant (WWTP) has 4.2 MW total and the inlet and outlet of the plant. Additionally, As Alsamamra has a 9.5 MW biogas electric generator that utilizes biogas produced in-plant from sewage sludge. Together these systems produce energy equal to almost 50% of Jordan’s WWTP demand, thus making As-Samra a positive example for future WWTP development in the Kingdom. There are two landfill gas (LFG) power plants at Al-Ghawabi and Rusaifeh landfills of approximately 5 and 3.5 MW, respectively. LFG has captured biogas from landfills which can then be used in a gas turbine. Al-Ghawabi is planned for expansion to 14 MW by 2027. Concentrating solar power (CSP) has been

236 PART | V Wind energy

TABLE 7.2 Jordan existing generating capacity (2018) [21].

Name

Type

Nominal capacity (MW)

Aqaba thermal power station

Steam

650

Natural gas and heavy fuel oil

Risha gas power station

OCGT

60

Natural gas and diesel oil

Rehab gas turbine power station

CCGT

357

Natural gas and diesel oil

Samar thermal power station

CCGT

1175

Natural gas

Amman east power plant (IPP1)

CCGT

370

Natural gas and distillate FO backup

Al Qatrana power plant (IPP2)

CCGT

373

Natural gas and distillate FO backup

Zarqa power plant

CCGT

485

Natural gas and distillate FO backup

IPP3 Tri-fuel power plant

CEPP

573

Natural gas, heavy fuel oil, and light fuel oil

IPP3 Al Manakher power plant

CEPP

250

Natural gas, heavy fuel oil, and light fuel oil

Manaseer cement power plant

Steam

30

Coal and pet coke

Rusaifeh LFG

SCGT

3.5

LFG and biogas

Al-Ghabawi LFG

SCGT

5

LFG and biogas

As-Alsamamra biogas digester

Anaerobic digester

9.5

Biogas

As-Alsamamra hydro

Hydropower

4.2

Water

Aqaba thermal PP hydro

Hydropower

6

Water

King Talal Dam

Hydropower

6.4

Water

Wind (cumulative)

283

PV (cumulative)

851

Fuel

CEPP, combustion engine power plant; IPP, independent power producer; LFG, landfill gas; OCGT, open cycle gas turbine; PV, photovoltaic; SCGT, simple cycle gas turbine.

Wind energy in Jordan and Palestine Chapter | 7

237

investigated in the Jordanian context but is not currently under development likely due to its higher cost and lower level of maturity. In total, MEMR expects more than 2400 MW of grid-connected renewables by 2021 to bring installed capacity to 30% renewable and production to 20% renewable [26].

1.4 Energy status and renewable resources in Palestine 1.4.1 Energy status As stated before, the Palestinian territories are a very complex area divided into two administrative regions, involving 4.7 million population, that causes different limits to the potential development of infrastructures and the energy sector’s development policies. The energy situation is severe in the Gaza strip and it is improving in the WB. This complex energy situation is due to the high dependence on other countries, the physical separation of Gaza and the WB, high political instability, and insufficient infrastructure [7,27e31]. In 2018, the primary energy consumption in Palestinian territories is about 75,178 TJ. Fuel and gas represent about 58%, imported and generated electricity is about 28% and renewable energy (solar energy, wood, etc.) is about 12% [32,33]. In Gaza, the electrical supply hardly satisfies half of the demand, which frequently leads to a blackout. Although the WB generally has around-theclock electric power, a deficiency appeared during winter and summer. Palestinian territories rely primarily in its electricity needs on the import flow from neighbors countries with costs of energy higher than in neighboring countries. The Gaza Power Plant, with a capacity of 140 MW, is the only large-scale generation capacity in the Palestinian territories. The plant is based on diesel-fired technology, and it is currently facing a continuous interruption because of the siege imposed on GS. The plant is so costly to run that it is usually only operating at half capacity. It has also been damaged repeatedly during armed conflicts, reducing its fuel storage capacity [7,31,34]. In 2018, the Palestinian final energy consumption in the household sector was about 45%, in the transport sector was 38%, while the remaining was going to commercial, industry, and agriculture (As shown in Fig. 7.4). This indicates that the residential and transportation sectors consumed the most total energy. In January 2015, the average household’s electricity use was 306 kWh [7,32]. Due to large losses and poor collection rates, the electrical industry faces operational and financial difficulties. Palestine imports most of its energy needs from other countries. Table 7.3 shows the total imported energy in Palestine by kind of energy for the year 2017 [35]. It is worth noting that about 369 GWh of electricity is locally generated which is about 6.2% of the total electricity demand for the year 2017. A minor amount of electricity is obtained from Jordan to power Jericho, while another percentage is imported from Egypt to power Rafah in Gaza [35].

238 PART | V Wind energy

FIGURE 7.4 Primary energy consumption and final energy consumption in Palestinian territories (PT) [7]. (A) Primary energy consumption in PT in 2018. (B) Final energy consumption in PT by sector in 2018.

1.4.2 Renewable energy resources The average daily solar radiation in Palestine is around 5.4 kWh/m2$day, while average monthly can reach 7.5 kWh/m2$day in summer months. In addition, annual sunshine hours exceed 3000 h. Solar water heating has been used extensively since the 1980s in Palestine employing a thermosiphon type solar heater. Most of the installed systems are made by local manufacturers. Percent of housed employing SWH are declining and become around 56% [32] from 68% in the 1990s. Solar electricity using PV systems are booming according to Khatib et al. [36,37], and there are 30 MWp operational, 92.8 MWp under construction, and 20 MWp proposed PV projects. Renewable energies, in general, and wind energy, in particular, are not efficiently invested in Palestine [8]. The use of wind energy, in particular, is greatly minimized in Palestine for different reasons, including lack of enough lands to install wind energy systems, lack of funds, and lack of trained professional, as well as the restrictions imposed by the occupation authorities on the Palestinian territories [8]. Wind energy has a low to moderate potential in Palestine, and is not utilized yet and; thus wind energy projects are still very limited. Supported by data and topographical characteristics of the WB, Wind energy’s potential appears to be confined to the mountainous areas with elevations of around 700e1000 m ASL [8]. Small amounts of biomass energy (olive cake and wood) are utilized for heating applications [7,35]. 1.5 Objective and scope of the chapter This chapter examines the existing state and future prospects of wind energy in Palestine and Jordan. Hence the objectives of this chapter include 1. Examining the wind speed and wind potentials for both Jordan and Palestine through reviewing published works and wind speed data.

TABLE 7.3 Regions and types of energy imported in Palestine, 2017.

Electricity (MWh)

Gasoline (kL)

Diesel (kL)

Fuel oil (kL)

Kerosene (kL)

LPG (ton)

Bitumen (ton)

Wood and charcoal (tons)

West Bank

4,801,564

274,716

496,146

4769

1279

124,208

35,223

3300

Gaza Strip

775,300

40,049

234,497

671

114

65,329

232

107

Palestine

5,576,864

314,765

730,643

5440

1393

189,537

23,584

3407

Region

Wind energy in Jordan and Palestine Chapter | 7

Type of energy

239

240 PART | V Wind energy

2. Reviewing pilot and commercial wind turbine projects in the two countries. 3. Looking into policies, regulations, and energy strategies to draw the future perspective of such renewable resources in the two countries.

2. Wind energy potentials in Jordan and Palestine 2.1 Wind speed and potentials in Jordan The wind speed map for Jordan and Palestine is shown in Fig. 7.5. It shows the geographical locations and regions of relatively high speed and consequently high wind power. The research done by Refs. [13,39] provided the wind distribution map for all governorates in Jordan. These governorates are Amman, Balqa, Madaba, Zarqa, Mafraq, Irbid, Ajloun, Jarash, Karak, Tafilah, Mann, and Aqaba. The average monthly and annual wind speed for all stations in the governorates of Jordan at a height of 10 m is shown in Table 7.4.

FIGURE 7.5 Wind map for Jordan and Palestine at 50 m height. Map obtained from the “Global Wind Atlas 3.0” [38].

TABLE 7.4 Mean monthly and annual wind speed (m/s) for all governorate stations at 10 m [13]. Station

Balqa

Madaba

Zarqa

Mafraq

Iirbid

Ajloun

Jarash

Karak

Tafilah

Maan

Aqaba

750

820

763

619

700

620

820

763

930

940

1100

6

Lat. N, Long. E

29, 35

32, 35

31, 35

32, 36

31, 36

33, 36

32, 36

32, 36

31, 35

30, 35

30, 35

30, 35

Month

Wind speed

January

3.3

3.2

3

3.1

3.5

2.8

2.78

3

3

2.8

5.6

6

February

3.3

3.2

3.5

3.2

3.6

2.9

2.32

3

3.3

2.9

5.6

6

March

3.3

3.2

3.4

3.3

3.5

2.8

2.33

3.5

3.5

3.06

5.9

7

April

3.2

3.2

3

3.3

3.1

2.7

2.66

3.6

3.1

3

6

7

May

3.3

3.5

3.1

3.1

3.4

3.09

2.51

3.5

3

3.09

6.2

7

June

3.4

4.2

3.5

3.9

4

3.32

2

4

3.8

3.78

7.1

8

July

4.3

4.3

3.7

3.8

4.2

4.1

1.81

4.2

4.2

4.48

7.3

7

August

3.5

3

3

3.4

3.3

3.89

1.57

3.6

3.6

3.89

6

7

September

2.1

2.7

2.3

3.2

3.4

2.6

2.17

3.4

3

3.33

5.8

6.5

October

2.2

1.8

2

3

3.3

2.4

1.66

3.3

3.2

3

5.6

7

November

2.1

1.9

2.8

3

3

2

3.29

3.2

3

2.55

5.6

6

December

2.4

2

2.65

3

3

2

2.96

3.2

3

2.57

5.4

6

Mean speed

3.03

3.02

3

3.28

3.44

2.88

2.34

3.46

3.31

3.2

6.01

6.71

Elevation





Wind energy in Jordan and Palestine Chapter | 7

Amman

241

242 PART | V Wind energy

FIGURE 7.6 Mean power density at three different heights for all governorates/Jordan [13].

The mean power density in W/m2 for all governorates at three different heights 50, 100, and 200 m is shown in Fig. 7.6. The potential wind energy production based on three different sites in Jordan mainly Irbid in the north Madaba in the middle and Aqaba in the south using 10 years of wind speed data for the stations of these sites was investigated by Ref. [40]. The annual mean and cubic wind speed for these sites at 10 m height as well as the wind energy flux are shown in Table 7.5. The method of site effectiveness given by Eq. (7.1) and two models of a wind turbine was used to estimate the wind energy production for the aforementioned cities in Table 7.6. The details of these models based on the speed of the wind turbine used for the wind power curve such as cut-in speed (Vc), rated speed (Vr), furling (cut-out) speed (Vf), operation speed (Vop), and other rotor parameters are shown in Table 7.6. ε¼

E

(7.1)

hmax Ea

where E, Ea, and hmax are the output energy, available energy on the site, and the maximum efficiency of the wind turbine, respectively. The results for Irbid, Madaba, and Aqaba in terms of yearly energy production, energy flux, and site effectiveness are illustrated in Table 7.7.

TABLE 7.5 Annual mean and cubic wind speed and the energy flux in kWh/m2/year [40].

Mean speed 3

Vm (m/s) 2

Eas (kWh/m /year)

Madaba

Irbid

Aqaba

4.8

4.02

5.75

5.43

4.63

6.31

859.03

532.52

1348.03

Eas Annual average wind energy flux, kWh/m2

Model

Pr (MW)

Number of blades

Rotor diameter (m)

Swept area (m2)

Hub height (m)

Vc (m/s)

Vr (m/s)

Vf (m/s)

Vop (m/s)

hr

hmax.

1

0.15

3.00

20.50

330.00

24.00

4.00

14.00

24.00

6.92

0.27

0.40

2

3.00

3.00

112.00

9852.00

84.00

3.00

13.00

25.00

5.19

0.23

0.40

Wind energy in Jordan and Palestine Chapter | 7

TABLE 7.6 Details and operating conditions of the two models of wind turbines [40].

243

244 PART | V Wind energy

TABLE 7.7 Yearly output energy, energy flux, and site effectiveness results for the two turbine models [40]. Model 1

Model 2

City

Output energy (GWh/ year)

Energy flux (kWh/m2)

Site effectiveness

Output energy (GWh/year)

Energy flux (kWh/m2)

Site effectiveness

Irbid

0.06

181.06

0.87

1.83

185.32

0.85

Madaba

0.1

295.51

0.81

2.98

302.38

0.82

Aqaba

0.16

479.9

0.83

4.84

490.68

0.84

Wind energy in Jordan and Palestine Chapter | 7

245

Five different rating wind turbines (EWT-500, EWT-900, Fuhrlander-100, Fuhrlander-1500, and Vestas-3000) were used to assess the power production for the five locations of the wind farm based on the mean monthly wind speed [41]. These locations are Queen Alia Airport, and Aqaba Airport, Ras-Moneef, Azraq south, and Safawi. The rated power for these wind turbines was varied from 100 to 3000 kW, and the probability distribution function based on the Weibull was used to fit the 5-year wind speed data. The eastern desert area was the most economically feasible location for wind farms where the wide plain land available. Therefore, Aqaba and Ras-Moneef have promising sites for high potential of wind energy while Queen Alia Airport has a low potential of wind energy. The annual energy production for the five locations from the fiveturbine types is shown in Fig. 7.7. The average monthly wind speed data for seven locations in Jordan were modeled by the Rayleigh probability function as shown in Fig. 7.8 [42]. The parameters for Rayleigh and Weibull distributions for selected sites and RasMoneef location are shown in Tables 7.8 and 7.9, respectively. The wind at the hub height was determined by a power law with a power exponent equal to one-seventh. Four different commercial turbines (Vestas 3 MW, GE 2.5 MW, Nordex 2.5 MW, and Torres TWE 1.65 MW) were used; the techno-economic performance (cost of energy production and capacity factor) for these seven locations was evaluated. All seven locations show high economic potential

FIGURE 7.7 Yearly energy production for the five locations in Jordan with different five commercial turbine types [41].

246 PART | V Wind energy

FIGURE 7.8 Weibull and Rayleigh distributions for Ras-Moneef in Jordan.

TABLE 7.8 Rayleigh parameters for the selected sites in Jordan [42]. Site

vobs (m/s)

s (m/s)

Vm (m/s)

Hofa (at 45 AGL) above ground level

7.2

8.07

7.2

Ibrahimya (at 60 m AGL)

6.8

7.71

6.8

R. Monief (at 10 m AGL)

6.6

7.49

6.6

Zabdaat (at 50 m AGL)

7.0

7.93

7.0

Tafila 2 (at 45 m AGL)

8.5

9.64

8.5

Fujaij (at 40 m AGL)

6.9

7.76

6.9

Aqaba 5 (at 45 m AGL)

7.2

8.15

7.2

where vobs is the monthly average wind speed observed, s is the Rayleigh scale factor and Vm is the mean of the probability density function f(v). AGL, above ground level.

with a cost of electrical energy (COE) less than 0.044 $/kWh. The location in Tafila has the lowest COE among other locations. Both prediction cost of wind energy and capacity factor for five locations in Jordan were assessed by using eight commercial different types of wind turbines [43]. These locations are R.monif, Irbid, D.alla, Alaqaba, and Amman. The COE for the wind turbines located in R.monif has the lowest values, these values were between 0.0259 and 0.0498 US$/kWh, whereas the highest cost was 0.222 US$/kWh for the wind turbines located in D.alla as shown in Fig. 7.9. Moreover, the theoretical and actual capacity factor for the wind turbine machines is shown in Fig. 7.10. Wind energy potential was estimated for four selected locations (AlSafawi, Al-Hasan, Al-Fjaij, and Ras Moneef) in Jordan by Ref. [44]. A promising wind farm with a 100 MW capacity was set up for these locations to produce electrical power for the Jordanian distribution authority. In this work, the environmental data were used from the local Meteorological department,

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Average

6.86

7.54

7.25

7.82

5.92

7.05

7.06

7.34

4.72

5.18

NA

6.46

6.65

k

1.67

1.41

1.87

1.95

2.04

2.69

3.15

2.61

1.97

1.65

NA

1.58

2.05

c (m/s)

6.8

7.66

7.53

8.66

6.18

7.48

8.28

7.75

4.91

5.12

NA

6.66

7

Vm (m/s)

6.07

6.97

6.69

7.68

5.47

6.65

6.65

6.88

4.06

4.58

NA

5.98

6.15

vobs (m/s)

Wind energy in Jordan and Palestine Chapter | 7

TABLE 7.9 Weibull parameters for the Ras-Moneef sites in Jordan [42].

247

248 PART | V Wind energy

FIGURE 7.9 Cost of energy for all studied wind turbine machines [43].

FIGURE 7.10 (A) Theoretical capacity factor (B) Actual capacity factor and cost of energy [43].

Wind energy in Jordan and Palestine Chapter | 7

249

while the specification of the wind turbine was used from the catalogs of wind turbine manufacturers. The wind farm was designed to produce 136 MW total rated wind power from the four selected sites. The highest-rated power 55 MW was obtained in the Ras Moneef site whereas Al-Fjaij has the lowest rated power 18 MW. In terms of energy production, 18.9  103 GWh was the total energy produced from the four sites, the details of the power, energy, cost, and profit are shown in Table 7.10. The electrical energy production from the wind farm for the four selected sites saved the carbon footprint by 16.2 tons of CO2, which equivalent to increase the temperature by 2.2  106
C. The wind energy potential for both Amman and Azraq south area as a single city in Jordan was studied by Refs. [25,26]. The two parameters of Weibull function was used to evaluate the statistical characteristics of wind data. The meteorological wind speed data for 7 years in Amman capital city of Jordan was used to evaluate the potential of wind energy [26]. The range of the annual mean wind speed and the direction of wind for the 7 years were from 2.2 to 3.02 m/s and between the southwest and the northwest, that is, (135e215 degrees), respectively. The highest and lowest wind power densities were found in June and October, respectively. The shape factor was between 1 and 1.5, while the scale factor between 1.5 m/s and 3.5 m/s, respectively. The results show that small-scale wind turbine for the 7-year data is more suitable for Amman city. The real long-term meteorological wind speed data (1991e2001) at 10 m height was used to assess the potential of wind energy in Azraq south area, a remote location in the Northeast Badia of Jordan [25]. The lowest and highest wind power potentials were found in December and July, respectively. Both shape and scale factors of Weibull distribution were varied over a wide range, the shape factor was varied from 1.05 to 4.2 while the mean

TABLE 7.10 Details of power, energy production, cost, and profit of wind farm in four selected sites in Jordan [44].

Availability factor (%)

Total energy production (GWh)

Cost of energy ($/kWh)

Pay back (year)

Annual net profit ($)

481

99

4277

0.028

11.4

5.1  106

Al Hasan

526

94

4467

0.027

11

5.5  106

Al Fjaij

332

95

2462

0.049

19.9

0.52  106

Ras Moneef

1246

97.5

7722

0.015

6.34

13.5  106

Wind power (kW) Al Safawi

250 PART | V Wind energy

value of scale factor was 4.57 m/s. The results show that the site is not suitable for large-scale electrical production from wind and suitable for off-grid or mechanical applications as in wind generators, agricultural applications, water pumping, and battery charging. Abusamaha et al. have experimentally investigated the main factors affecting the efficiency of a laboratory scale wind turbine at the university of Jordan, these factors included the number of blades, the angle of attack, and the incident angle on the wind energy unit [45]. Ayadi and Alsalhen [46] presented a hybrid wind and concentrated solar power system that provides a firm capacity and improves dispatchability with an interesting financial perspective. The hybrid plant was simulated and optimized using TRNSYS 17 energy simulation software. The optimal configuration of the CSP-wind hybrid system was obtained with a solar field of a 2.6 solar multiple and a 5-h energy storage. The achieved capacity factor was 94%, and the LCOE is lower than those resulted for standalone CSP plants.

2.2 Wind speed and potentials in Palestine Wind speed data that goes back to 1948e57 on the Beaufort scale was analyzed by Ref. [47] for few sites in WB and GS. Weibull distribution function parameters k, and c were estimated and then the annual extractable energy based on Betz limit was estimated. Previous speed data in the Beaufort scale 1948e57 was analyzed by Shabbaneh [48]. They have estimated the Weibull parameters and wind potential at various turbine heights as shown in Table 7.11. The payback period and electricity costs for various locations were calculated. In addition, wind speed from 49 weather stations over the whole of Palestine was used to establish wind potential contours.

TABLE 7.11 Win speed means, Weibull parameters, and wind potentials [48]. Location

Jenin

Jericho

Ramallah

Jerusalem

Gaza

Annul mean speed (m/s)

3.65

3.3

4.80

4.12

2.90

k

1.455

2.421

2.319

1.736

1.455

4.21

3.721

5.405

4.626

3.182

10 m

285

146

407

334

152

20 m

431

286

659

541

201

40 m

626

505

1013

831

261

c (m/s) 2

Potential (kWh/m )

Wind energy in Jordan and Palestine Chapter | 7

251

Odeh [49] has carried out an assessment of the wind resources in Palestine employing a two stages method; the primary one is based on reference stations and the second stage is based on WindPRO software. Author has identified the most potential sites for wind power. Khatib et al. [50] has predicted, using an artificial neural network, the wind speed for two locations, Ramallah and Nablus, in Palestine with good accuracy. Kitaneh et al. [10] have collected wind speed data for four locations in Palestine over 5 years (1997e2001) and analyzed using the Weibull distribution function in order to estimate the wind energy potential power. The highest power density was found for Hebron during July as 37.85 W/m2. Juaidi et al. [12] have investigated the renewable energy potentials in Palestine including wind energy. Wind speed data for five locations as depicted in Fig. 7.11 were analyzed by calculating annual means and energy potentials. They found that mean wind speeds in the hilly regions of WB is 4e8 m/s. Fig. 7.12 shows the box plot for the Monthly wind speed in five locations in WB during 2013. Using numerical weather prediction model WRF De Meij et al. [6] have simulated wind speed over the years (2000e11). Then, they have calculated power density and the generated electric energy per year for the State of Palestine. The results showed that maximum wind speed and energy occur during winter for Gaza with a westerly prevailing wind direction. However, it is not sufficient to be considered for electricity generation. For WB, they have found that the region east of Hebron has the highest wind energy potential. Elnaggar et al. [51] have conducted a simulation study in order to investigate the feasibility of using small wind turbines to reach household electricity

Wind Speed (m/s) for year 2013

7.0

Tubas

Salfeet

6.0 5.0 4.0 Ramallah 3.0 Hebron 2.0 1.0

Avg.

Nov

Oct

Sep

Aug

Jul

Jun

May

Apr

Mar

Feb

Jan

FIGURE 7.11

Dec

Jericho

0.0

Monthly average wind speed in five locations in West Bank during 2013 [12].

252 PART | V Wind energy

FIGURE 7.12 Box plot for the monthly wind speed in five locations in West Bank during 2013 [12].

Speed ( m/s)

selfsufficiency in GS. They have used in their study the WTT 5000S wind turbine produced by WTT GmbH/Germany with the following specifications: Blade diameter ¼ 3.8 m, speed 450 rpm, Power at 15.0 m/s ¼ 5000 W, efficiency ¼ 30.5%, overall weight of the turbine ¼ 74 kg [51]. They have assumed the mounting of the turbine on top of the residential building. The authors have concluded that at a height of 10 m, 2695 kWh can be obtained yearly, while at 20 m an increase of 34% can be achieved, and at 70 m an increase of 118% can be achieved. The effectiveness of the wind system can be improved if integrated with a PV system. According to their results, one wind turbine together with one PV would be enough to fulfill the energy consumption of 3.7 homes. They have calculated the cost of installing one turbine with the stated specifications to be around 9000$; which is considered expensive compared to the living standards in GS. Using hourly time series for the period (2000e15) from the database of Meteoblue AG-Switzerland Nassar et al. [52] have assessed the wind energy for three sites in GS; Jabalia, Deirealbalah, and Rafah. Figs. 7.13 and 7.14 20 18 16 14 12 10 8 6 4 2 0

Wind speed for three locations in Gaza Strip Jabalia

Rafah

Jan

Deir-Albalah

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

FIGURE 7.13 Wind speed for three locations in Gaza strip. Based on [52].

Dec

Wind energy in Jordan and Palestine Chapter | 7

Wind potential for three locations in Gaza Strip

1400

Power density ( W/m2)

1200

253

Jabalia

1000

Deir-Albalah

800 600 400 Rafah

200 0 Jan

Feb Mar Apr May Jun

Jul

Aug Sep

Oct

Nov Dec

FIGURE 7.14 Wind potential for three locations in Gaza strip. Based on [52].

show the mean wind speed and power density for three locations in GS while Figs. 7.15 and 7.16 show the k and c Weibull parameters for the same locations. The analysis indicated that Rafah could be used to build a wind farm since it has the highest wind potential. In addition, Rafah with relatively small population density has the required land to install the turbines. The turbines could be imported through Egypt as it lies on the EgyptianePalestinain borders. Assessment for proposed Gamesa G128e4.5 wind turbine is summarized in Table 7.12.

Weibull parameters C for three locations in Gaza Strip

7.5

Rafah

7

Deir- Albalah

Weibull c m/s

6.5 6 5.5 5 4.5 4

Jabalia 3.5 3 Jan FIGURE 7.15

Feb Mar Apr May Jun

Jul

Aug

Sep

Oct

Nov

Dec

Weibull parameters k and c for three locations in Gaza strip. Based on [52].

254 PART | V Wind energy Weibull parameters k for three locations in Gaza Strip 2.5

Weibull k

2.3

Rafah

2.1 1.9 1.7

Deir-Albalah

1.5

Jabalia 1.3 Jan

Feb Mar Apr May Jun

Jul

Aug

Sep

Oct

Nov

Dec

FIGURE 7.16 Weibull parameters k and c for three locations in Gaza strip. Based on [52].

Wind speed data for the years 2003 and 2007 were analyzed by Badawi [53]. Results have showed a daily average speed of 3.2 m/s for Gaza city and 2.52 m/s for Khan Younis. Badawi et al. [54] have analyzed the wind speed data over the period (1996e2006) for Gaza in order to calculate the wind power density. They found that annual mean wind speed is 4.11 m/s and the power density 74.87 W/m2. They concluded that small-scale turbines can be employed in electricity generation schemes for Gaza. Based on wind speed records Badawi et al. [55] have investigated wind energy for three locations in Palestine; Nablus, Ramallah, and Gaza. Their analysis included fitting data to the Weibull function. The obtained results are summarized in Table 7.13. The highest annual energy generation from wind is found for Ramallah at 2008 kWh/m2. An overview of using wind energy to provide electricity for Palestinian territories was conducted by Albisher et al. [56]. They have investigated previous relevant studies and outlined some of the obstacles. Salem [8] has investigated the wind potential for the WB and Gaza. Author found that the average wind speed in the coastal region is 3e4 m/s and 6e10 m/s in the hilly regions. Then, he has concluded that there is a moderate potential for wind energy production in Palestine. Brik [57] has analyzed wind speed measurements during (2010e11) for eight weather stations scattered over the WB. In addition, he has estimated the power density, annual expected energy generation, and the economic feasibility of installing wind turbines. Table 7.14 shows the stations and wind

Month

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Annual

Annual energy (MWh/year)

1385

1383

1334

1649

1419

1434

1281

1353

1339

1246

1070

1047

15,962

Capacity factor

0.414

0.457

0.398

0.509

0.424

0.443

0.383

0.404

0.413

0.372

0.330

0.313

0.404

Wind energy in Jordan and Palestine Chapter | 7

TABLE 7.12 Proposed Gamesa G128e4.5 MW turbine monthly wind energy for Rafah [52].

255

256 PART | V Wind energy

TABLE 7.13 Annual mean wind speed, Weibull parameters, and power and energy densities in selected sites [55].

k

c (m/s)

Annual energy densityd Weibull, (kWh/m2)

Annual energy densityddata (kWh/m2)

4.346

1.785

4.364

670.13

927.097

2006

5.521

1.9389

4.4173

628.11

2008.0

2004

2.85

e

e

e

160.15

Location

Wind data

Annual mean speed (m/s)

Nablus

2006

Ramallah Gaza

TABLE 7.14 Average wind speed, power density, and generated energy at 32.5 m elevation [57]. Location

Wind speed (m/s)

Power density (W/m2)

Energy from 100 kW turbine (MWh/year)

Hebron

5.6

177

179.1

Jenin

5.6

183

182.7

Kardallah

4.5

147

126.8

Nablus

5.4

166

167.4

Ramallah

6.7

538

272.6

Tulkarem

3.6

51

50.2

Tubas

6

226

222.2

Salfeet

5.7

164

176.5

speed, annual generated energy from 100 kW wind turbine. Author has concluded that the mountains region of central and south WB with annual means 5e7 m/s are the most economical attractive locations. Wind speed data recorded from (2008e18) were analyzed by Alsamamra et al. [58] for east Jerusalem. Data were analyzed using the Weibull function, and then wind power was evaluated for the studied site as shown in Fig. 7.17. Khatib et al. [50] have used the wind data for one city using a cascade forward neural network method in order to predict speed in other four cities with good accuracy.

Wind energy in Jordan and Palestine Chapter | 7

30 Wind speed and power density for Jerusalem 25

4

20

3

15 2 10 1

Power density W/m2( Line)

Speed, c m/s, k (Bars)

5

257

5

0

0

Speed

FIGURE 7.17

k

c

Power density

Wind speed and power density for Jerusalem. Based on [58].

As summarized in Table 7.15, the reviewed available literature on wind energy covers a long period since 1948 and various locations in WB and GS Strip. It reports wind speed at different heights. For the same city, different values are reported for the wind speed as wind speed is site-dependent. Hence, it depends on the location where measurements were made. Wind speed and potentials indicating very low potentials in coastal areas of Gaza and good potential for hilly regions of the WB.

3. Pilot and commercial projects in Jordan and Palestine 3.1 Pilot and commercial projects in Jordan The utilization of wind power in Jordan started early with the Al-Ibrahimyah wind farm establishment in 1989, followed by Hofa wind farm in 1996. However, it takes about 20 years until the technical, economic, and regulatory aspects ranked wind power technology among Jordan’s most attractive power generation options. During the last 5 years, there was a significant increase in the installed capacity of wind power projects. Fig. 7.18 presents the growth of the wind power installed capacity during the period 2010e22, considering the installed projects and projects under construction. As of 2021, there are 10 grid-connected wind power plants in Jordan. Eight of them are already operating, namely, Ibrahimyah, Hofa, Al Fujaij pilot project, Tafila, Maan, Al Rajif, Al Fujaij, and Mass. In addition, two plants are currently under construction: Abour and Daehan. In the following part, a description of each project is presented. The main parameters of these plants

TABLE 7.15 Windspeed and power for Palestine from reviewed literature. Mean speed (m/s)

Power density (W/m2)

Rafah

6.34

331.1

Gaza

Annual energy 2

References

Wind data

[52]

2000e15

2.85

160.15 kWh/m

[54]

2004

2.90

152 kWh/year at 10 m

[48]

1948e57

Deir-albalah

4.41

113.1

[52]

2000e15

Jabalia

3.98

86.7

[52]

2000e15

Hebron

5.6

177

[57]

2010e11

Jerusalem

3.1

[58]

2008e18

334 kWh/year at 10 m

[48]

1948e1957

272.6 MWh/year, from 100 kW turbine

[57]

2010e11

2008.0 kWh/m

[54]

2006

407 kWh/year at 10 m

[48]

1948e57

4.12 Ramallah

6.7 5.521

538 628.11

4.80

179.1 MWh/year, from 100 kW turbine

2

Salfeet

5.7

164

176.5 MWh/year, from 100 kW turbine

[57]

2010e11

Nablus

5.4

166

167.4 MWh/year, from 100 kW turbine

[57]

2010e11

Jenin

2

4.346

670.13

9270.1 kWh/m

[54]

2006

5.6

183

182.7 MWh/year, from 100 kW turbine

[57]

2010e11

285 kWh/year at 10 m

[48]

1948e57

50.2 MWh/year, from 100 kW turbine

[57]

2010e11

146 kWh/year at 10 m

[48]

1948e1957

3.65 Tulkarem

3.6

51

Jericho

3.3

Kardallah

4.5

147

126.8 MWh/year, from 100 kW turbine

[57]

2010e11

Tubas

6

226

222.2 MWh/year, from 100 kW turbine

[57]

2010e11

258 PART | V Wind energy

Location

Wind energy in Jordan and Palestine Chapter | 7

259

800

Wind Power (MW)

700 600 500 400 300 200 100 0 2010

2012

2014

2016

2018

2020

2022

Year Installed Capacity [MW]

Under construction [MW]

FIGURE 7.18 The growth of the wind power installed capacity during the period 2010e22.

are presented in Table 7.16. Furthermore, Fig. 7.19 presents the geographical location of these projects, which are mainly located in Irbid in the north (2 plants), and Al-Tafileh and Ma’an regions in the south of Jordan (8 plants). 1. The first wind farm in Jordan was established in 1988 at Al-Ibrahimyah in the northern city of Irbid. The 320 kW plant consisted of four wind turbines of 80 kW each [59]. This pilot project was successful in terms of technical and economic perspectives: the average annual electricity production is about 650 MWh [60]. 2. The second wind farm was installed in 1996 at Hofa which is also located in the northern city of Irbid. This plant consisted of five wind turbines with a total capacity of 1.125 MW [61]. The average annual generation from this plant is 2.9 GWh [60]. 3. Within the framework of the EU-funded project “Capacity Building in Wind Energy and Concentrating Solar Power (WECSP),” the first Mega scale wind turbine of 1.65 MW capacity was installed in the Al-Fujaij region in the southern part of Jordan in 2013 [62]. 4. The Jordan Wind Power Company (JWPC) developed the first commercial wind farm in Jordan in the Al-Tafileh region. The total cost of the project is 287 $million, it was commissioned in 2015. The plant consisted of 15 V112e3.0 wind turbines (3 MW each), with a total capacity of 117 MW [63]. This plant is the largest wind plant on the national level until now.

Project name

Project size (MW)

1

Al Ibrahimyeeh

0.32

2

Hofa

3

Turbine rated power (MW)

Turbine model

Rotor diameter (m)

Hub height (m)

Year

4

0.08

e

e

e

1988

1.125

5

0.225

VESTAS V27

27

33.5

1996

Al Fujaij wind turbine

1.65

1

1.65

TWT-1.65

77

70

2013

4

Tafila wind farm

117

38

3.075

Vestas V112e3.0

69e94

2015

5

Ma´an wind (I and II)

80

40

2

Siemens Gamesa SG 2-97

97

78

2016

6

Al-Rajif

86.1

41

2.1

Siemens Gamesa SG 2.1e114

114

80

2018

7

Fujeij

89.1

27

3.3

Vestas V126e3.3

126

87e166

2019

8

Mass

100

28

3.6

GE 3.6e137

137

110e164.5

2020

9

Abour

51.75

15

3.45

Vestas V136e3.45

136

82e149

2021

Daehan

51.75

15

3.45

Vestas V136e3.45

136

82e149

2021

Total

578.8 MW

10

# of turbines

112

260 PART | V Wind energy

TABLE 7.16 List of main parameters of the main wind farms in Jordan.

Wind energy in Jordan and Palestine Chapter | 7

261

FIGURE 7.19 Location of wind farms in Jordan.

5. Ma’an wind project was developed in two phases by the Spanish company Elecnor. The project consisted of 40 wind turbines of Siemens Gamesa G97e2.0 (2 MW each). The hub height of the turbines is 78 m [64,65]. 6. Al-Rajef Wind Park with 86.1 MW was commissioned in 2018. This plant consists of a substation and 41 wind turbines manufactured by Siemens Gamesa, each with a rated power of 2.1 MW, and 80 m hub height. The plant cost is 185 $million [66]. 7. Al-Fujeij wind project with an 89 MW was put in operation in 2019 in Al Shobak, Governorate of Ma’an. The total cost of the project is 180 $million. The plant consisted of 27 Vestas (V126e3.3) wind turbines. The project is owned by Korea Electric Power Corporation (KEPCO) [67,68].

262 PART | V Wind energy

8. The second-largest wind plant in Jordan with a capacity of 100 MW is the MASS plant, which is constructed in Al-Tafilah. The plant consisted of 28 wind turbines with a capacity of 3.6 MW each, and turbines are manufactured by the American company GE (GE 3.6e137). Several international players are involved in the development of this project. It has to be mentioned that there are plans to expand the capacity of this project to 150 MW [69]. 9. Abour wind farm is a 52 MW wind park is currently under construction in the Al-Tafileh region. The plant includes 15 Vestas V136e3.45 MW wind turbines. And the project is owned by Saudi Arabia’s company Xenel and Amea power limited [70]. 10. Daehan wind plant is another 52 MW wind park that is currently under construction in the Al-Tafileh region. The plant is similar to the previously mentioned Abour wind park and consisted of 15 units of the V136e3.45 MW turbines [71].

3.2 Wind energy projectsdPalestine In general, Palestine has a moderate potential for wind-generated energy [10,12,72]; which suggests the use of small size wind turbine to produce electricity especially in remote areas with no electric grid. This may explain why commercial wind-generated energy projects have not yet implemented in Palestine. The feasibility of such commercial projects still needs further investigation. Currently, the only initiative in this direction started in 2009 when Al-Ahli Hospital planned to fulfill about 40% of its energy consumption by the renewable energy source to reduce its annual energy expenses. Al-Ahli Hospital is in Hebron located on a hill with altitude 880 m ASL at latitude 31
330 22.4000 and longitude 35
040 58.6300 . The annual mean wind speed in the area is 6.2 m/s. Al-Ahli Wind Energy Project (AWEP) started in 2009 as a 3year project with a budget of 2,600,000 $; 20% of the cost planned to be financed by the hospital, while the rest to be financed by the EU Commission [73]. The AWEP partners: Twente University, the Electric Company in Hebron, and other local partners. The location of the hospital suggests the exploitation of wind energy; therefore the main goal of the project was to save 40% of the energy expenses by installing a wind turbine with the following specifications [74]: Wind Average Speed ¼ 7e10 m/s, HubHeight ¼ 45e55 m, Power ¼ 750 kW, Bottom Tower-Diameter ¼ 2e5 m, Top Tower-Diameter ¼ 1.5e2 m. However, due to site restrictions, the project team recommended a 330 kW wind turbine which makes only 20% saving. To fulfill the target of 40% saving; the team proposed using a thermal solar system for water heating and steam production. During the design phase, the visual and noise impact of the AWEP was also assessed. Unfortunately, the last status of the AWEP is that the solar system is in operation since a few years

Wind energy in Jordan and Palestine Chapter | 7

263

ago, but the wind turbine was not installed because it is financially unfeasible; and not to mention political obstacles [8]. As for residential applications, few initiatives started by some individuals in GS where electricity sources are limited. They have installed small wind turbines on top of their homes to fulfill their own daily consumption of electricity [8]. Unfortunately, there is no assessment or documentation on such individual experiences, or on any pilot projects that may exist.

4. Future perspectives of wind energy in Jordan and Palestine 4.1 Future perspectives for wind energy in Jordan Jordan has many locations where the utilization of wind energy for electrical production is effective. Therefore, using this renewable resource will help the country to meet the energy demand. The southern part of Jordan has a high level of wind speed with acceptable land that make building wind farm one of the alternative solutions to meet the increasing energy demand. The growth of wind and solar energies in the last decade in Jordan was enormous and expected to continue growing. The electrical industry had substantial expansion in the previous decade, with combined cycles installed capacity growing by about 70% and renewable energy installed capacities increasing by roughly 10%. Until 2015, Jordan’s power industry was dominated by conventional energy sources. However, due to the installation of many utility-scale PV and wind projects, renewable energy now accounts for more than 10% of the country’s electricity mix. Jordan has diversified its energy mix in recent years by implementing renewable energy projects such as solar PV and wind, with renewables accounting for 10.7% of total electricity generation in 2018. At the present rate of investment, the National Electric Power Company (NEPCO) anticipates the entire energy mix to reach up to 30% renewable by 2022. Furthermore, by 2023, the nation anticipates renewable energy to account for 35% of the total installed capacity for power generation. Jordan is committed to pursuing a sustainable and dynamic energy strategy by promoting energy efficiency (EE) and expanding renewable energy technologies. The Jordan has revised its previously published Energy Strategy (2007e20) and established the Master Strategy for the Energy Sector 2015e25, which includes high objectives for renewable energy. The three primary goals of the Master Strategy are as follows: 1. Identify low-cost, reliable energy sources; 2. Boost the use of indigenous resources and renewables to enhance supply security; 3. Improve EE to decrease oil imports, minimize necessity production facility investment, and reduce the environmental effect (including GHG emissions).

264 PART | V Wind energy

Jordan has a National Renewable Energy Action Plan (NREAP) in place for the years 2018e23. Renewable energy is expected to account for more than 37.14% of total installed electricity capacity by 2023, according to the NREAP’s stated objective. This translates to between 2.2 and 3.2 GW of electrical capacity, trying to reflect the potential development paths of both large-scale and decentralized projects compared to their 2018 baseline, which includes more than 1 GW of installed renewable energy capacity, including 7 GW solar PV, 3 GW wind, 12 MW hydro, and 3.5 MW biogas.

4.2 Future perspectives for wind energy in Palestine According to the PENRA, the renewable energy strategy of 2012 Renewable Energy Resources (RER) should be at least 10% of the electricity produced locally in 2020, which is 240 GWh [75]. Based on the RER assessment studies conducted by PENRA, the technology required in terms of implementation and investment has been identified as given in Table 7.17 until 2020 [75]. Renewable energy strategy 2012e20 for Palestine aims to produce 4 MW from small wind turbines and 40 MW from large wind turbines [75]. The new Renewable Energy Action Plan NREAP 2020e30 is targeting 500 MW of renewable energy with wind energy being 10% of this capacity. On the other hand regulations and schemes have been set to uptake this 500 MW of RE including feed-in-tariff (FiT), net metering, in addition to investment incentives such as low-interest loans, and tax exemptions [76]. Good wind potentials prevail on the mountains and hilly regions of WB; however, most of the sites are not controlled by the Palestinian authorities. Hence, installing wind turbines on these sites is unlikely in the current

TABLE 7.17 Renewable energy strategy 2012e20 for Palestine [75]. Technology

2020 (MW)

PV system-Grid connected

25

Roof tops PV system (PSI)

20

CSP

20

Biogas from landfills

18

Biogas from manures

3

Small scale wind turbines

4

Large scale wind turbines

40

Total

130

Wind energy in Jordan and Palestine Chapter | 7

265

situations. Once Palestine will be an independent state and controlling the land it will be possible to install wind turbines and achieve the targeted wind capacity by the New Renewable Energy Action Plan NREAP 2020e30.

5. Conclusions Studies on Jordan’s renewable energy resources, notably wind potential, have found that the kingdom has great potential for wind and other renewable energy resources. As a result, Jordan has already established plans to generate electricity from renewable sources, such as wind. A wind atlas has been constructed based on an assessment of available resources, revealing the potential for several hundred megawatts of wind-power projects in Jordan. The south part of Jordan has a high potential for wind resources according to the value of wind power density. Both Rayleigh and Weibull probability density functions were used to estimate wind potential in Jordan. Moreover, Ras moneif, Tafila, and Aqaba cities have the opportunity to install wind farms due to the availability of plane level of topographical area (terrain). These cities have the ability to produce electrical power by using different commercial wind turbine types with competitive COE and capacity factors. Furthermore, the wind potential in Amman, the capital city of Jordan, is suitable for small-scale wind turbines due to the low level of wind speed, whereas the wind potential in Azraq south area is suitable for off-grid mechanical applications. Currently, installed wind capacity is 578 MW; meanwhile, the hundred percent domestic energy scenarios are targeting over 50% as wind energy. The average wind speed in the hilly areas in WB is between 4 and 8 m/s. The altitude in GS varies between zero and less than 125 m ASL, with an average wind speed between 2.5 and 3.5 m/s. Hence, wind potentials in WB are moderate while in Gaza are low. In Palestine, wind energy, in particular, is underinvested. For a variety of reasons, including a noncontrol of land with sufficient wind potentials, and a lack of trained professional capacity, as well as the restrictions imposed on Palestine by the occupation authorities. Commercial wind-generated energy projects have not yet implemented in Palestine, the only initiative in this direction was Al-Ahli Hospital Wind Turbine Energy Project which even was not realized because it is financially unfeasible. Few residential initiatives started by some individuals in WB and GS; but unfortunately, there is no assessment or documentation on such individual experiences.

References [1] [2]

Department of Statistics, Jordan in Figures 2019, Amman, 2019. U.S. Central Intelligence Agency, Maps of Jordan [WWW Document]. Univ. Texas Libr. Jordan (Shaded Reli. 2004), 2004. URL, https://www.ecoi.net/en/file/local/1208759/470_ 1282716906_jordan-rel-2004.jpg.

266 PART | V Wind energy [3] K.S.A. Jaber, I.J. Bickerton, I. Verity Elizabeth, Jordan - Climate. Encyclopedia Britannica, Encyclopedia Britannica, Inc., 2021. In press, https://www.britannica.com/place/Jordan/ Climate. [4] A. Albatayneh, H. Atieh, M. Jaradat, M. Al-Omary, M. Zaquot, A. Juaidi, R. Abdallah, F. Manzano-Agugliaro, The impact of modern artificial lighting on the optimum window-towall ratio of residential buildings in Jordan, Appl. Sci. 11 (2021) 5888. [5] A. Albatayneh, M. Jaradat, M.B. AlKhatib, R. Abdallah, A. Juaidi, F. Manzano-Agugliaro, The significance of the adaptive thermal comfort practice over the structure retrofits to sustain indoor thermal comfort, Energies 14 (2021) 2946. [6] A. De Meij, J.-F. Vinuesa, V. Maupas, J. Waddle, I. Price, B. Yaseen, A. Ismail, Wind energy resource mapping of Palestine, Renew. Sustain. Energy Rev. 56 (2016) 551e562. [7] RCREEE, Country Report on Energy Efficiency and Renewable Energy Investment Climate e Palestinian Territories, RCREEE, 2020 [WWW Document]. meetMED. URL, https://www.rcreee.org/content/country-report-energy-efficiency-and-renewable-energyinvestment-climate-e-palestinian (accessed 6.28.21). [8] H.S. Salem, The potential of wind energy in Palestine with healthcare and residential examples in the West Bank and the Gaza Strip, J. Nat. Sci. Sustain. Technol. 13 (2019) 73e97. [9] GeoModel Solar, Atlas of Solar Resources, State of Palestine, 2014. [10] R. Kitaneh, H. Alsamamra, A. Aljunaidi, Modeling of wind energy in some areas of Palestine, Energy Convers. Manag. 62 (2012) 64e69. [11] R. Abdallah, A. Juaidi, M. Assad, T. Salameh, F. Manzano-Agugliaro, Energy recovery from waste tires using pyrolysis: Palestine as case of study, Energies 13 (2020) 1817. [12] A. Juaidi, F.G. Montoya, I.H. Ibrik, F. Manzano-Agugliaro, An overview of renewable energy potential in Palestine, Renew. Sustain. Energy Rev. 65 (2016) 943e960. [13] S.S. Alrwashdeh, Map of Jordan governorates wind distribution and mean power density, Int. J. Eng. Technol. 7 (2018) 1495e1500. [14] A. Albatayneh, A. Juaidi, R. Abdallah, A. Pen˜a-Ferna´ndez, F. Manzano-Agugliaro, Effect of the subsidised electrical energy tariff on the residential energy consumption in Jordan, Energy Rep. 8 (2022) 893e903. [15] F. AlFaris, A. Juaidi, R. Abdallah, A. Pen˜a-Ferna´ndez, F. Manzano-Agugliaro, Energy performance analytics and behavior prediction during unforeseen circumstances of retrofitted buildings in the arid climate, Energy Rep. 7 (2021) 6182e6195. [16] R. Abdallah, A. Juaidi, T. Salameh, M. Jeguirim, H. C ¸ amur, Y. Kassem, S. Abdala, Estimation of solar irradiation and optimum tilt angles for south-facing surfaces in the United Arab Emirates: a case study using PVGIS and PVWatts, in: Recent Advances in Renewable Energy Technologies, Academic Press, 2022, pp. 3e39. [17] S. Al-Dahidi, O. Ayadi, J. Adeeb, M. Alrbai, R.B. Qawasmeh, Extreme learning machines for solar photovoltaic power predictions, Energies (2018), https://doi.org/10.3390/ en11102725. [18] O. Ayadi, R. Al-Assad, J. Al Asfar, Techno-economic assessment of a grid connected photovoltaic system for the University of Jordan, Sustain. Cities Soc. 39 (2018), https:// doi.org/10.1016/j.scs.2018.02.011. [19] International Energy Agency, Electricity Generation by Fuel - Jordan, 2018 [WWW Document]. URL, https://www.iea.org/data-and-statistics/data-tables? country¼JORDAN&energy¼Electricity&year¼2018 (accessed 5.11.21). [20] National Electric Power Company (NEPCO), Annual Report 2019, Amman, 2019. [21] M. Dabbas, Sustainable Energy Performance in Ministry of Energy & Mineral Resources, 2016.

Wind energy in Jordan and Palestine Chapter | 7 [22] [23]

[24] [25] [26] [27] [28]

[29]

[30]

[31]

[32] [33]

[34]

[35]

[36] [37] [38]

[39] [40]

267

NEPCO, Annual Report, 2018. M. Hindiyeh, A. Albatayneh, R. Tarawneh, S. Suleiman, A. Juaidi, R. Abdallah, M. Jeguirim, Preparedness plan for the water supply infrastructure during water terrorismda case study from Irbid, Jordan, Water 13 (20) (2021) 2887. E.S. Hrayshat, Viability of solar photovoltaics as an electricity generation source for Jordan, Renew. Energy 34 (2009) 2133e2140, https://doi.org/10.1016/j.renene.2009.03.006. O. Al-Nhoud, M. Al-Smairan, Assessment of wind energy potential as a power generation source in the Azraq South, Northeast Badia, Jordan, Mod. Mech. Eng. 5 (2015) 87e96. M. Al-Ghriybah, Z.M. Fadhli, D.D. Hissein, S. Mohd, Wind energy assessment for the capital city of Jordan, Amman, J. Appl. Eng. Sci. 17 (2019) 311e320. R. Abdallah, A. Juaidi, S. Abdel-Fattah, F. Manzano-Agugliaro, Estimating the optimum tilt angles for south-facing surfaces in Palestine, Energies 13 (2020) 623. H. C¸amur, R. Abdallah, Investigation of the Palestinian overall heat transfer coefficient and comparison with International Building Codes, in: 2021 12th International Renewable Engineering Conference (IREC), IEEE, 2021, pp. 1e5. S. Monna, A. Juaidi, R. Abdallah, M. Itma, A comparative assessment for the potential energy production from PV installation on residential buildings, Sustainability 12 (2020) 10344. S. Monna, A. Juaidi, R. Abdallah, T. Salameh, Sustainable energy retrofitting for residential buildings in Palestine, a simulation based approach, in: 2021 12th International Renewable Engineering Conference (IREC), IEEE, 2021, pp. 1e5. W.A. Salah, M. Abuhelwa, M.J.K. Bashir, The key role of sustainable renewable energy technologies in facing shortage of energy supplies in Palestine: current practice and future potential, J. Clean. Prod. 125348 (2020). Palestinian Central Bureau of Statistics, Palestine in Figures 2020, Ramallah, 2021. T. Salamah, A. Ramahi, K. Alamara, A. Juaidi, R. Abdallah, M.A. Abdelkareem, A.G. Olabi, Effect of dust and methods of cleaning on the performance of solar PV module for different climate regions: Comprehensive review, Sci. Total Environ. 154050 (2022). S. Monna, R. Abdallah, A. Juaidi, A. Albatayneh, A.J. Zapata-Sierra, F. Manzano-Agugliaro, Potential electricity production by installing photovoltaic systems on the rooftops of residential buildings in Jordan: an approach to climate change mitigation, Energies 15 (2) (2022) 496. PCBS, Imported Energy in Palestine by Type of Energy and Month, 2019, 2019 [WWW Document]. URL, https://www.pcbs.gov.ps/statisticsIndicatorsTables.aspx?lang¼en&table_ id¼525 (accessed 6.28.21). T. Khatib, A. Bazyan, H. Assi, S. Malhis, Palestine energy policy for photovoltaic generation: current status and what should be next? Sustainability 13 (2021) 2996. A. Juaidi, R. Abdallah, O. Ayadi, T. Salameh, A.A. Hasan, I. Ibrik, Solar cooling research and technology, Recent Advances in Renewable Energy Technologies (2021) 1e44. Global Wind Atlas 3.0, a Free, Web-Based Application Developed, Owned and Operated by the Technical University of Denmark (DTU). The Global Wind Atlas 3.0 is Released in Partnership with the World Bank Group, Utilizing Data provided by Vortex, Using Funding provided by the E.S.M.A.P. (ESMAP). F, 2021 additional information, https:// globalwindatlas.info (Wind map for Jordan and Palestine). MEMR, Wind Map of Jordan, Promising Locations, 2014. S.S. Alrwashdeh, Investigation of wind energy production at different sites in Jordan using the site effectiveness method, Energy Eng. J. Assoc. Energy Eng. 116 (2019) 47e59.

268 PART | V Wind energy [41] H.D. Ammari, S.S. Al-Rwashdeh, M.I. Al-Najideen, Evaluation of wind energy potential and electricity generation at five locations in Jordan, Sustain. Cities Soc. 15 (2015) 135e143. [42] K.M. Bataineh, D. Dalalah, Assessment of wind energy potential for selected areas in Jordan, Renew. Energy 59 (2013) 75e81. [43] A.S.K. Dalabeeh, Techno-economic analysis of wind power generation for selected locations in Jordan, Renew. Energy 101 (2017) 1369e1378. [44] M.A. Alsaad, Wind energy potential in selected areas in Jordan, Energy Convers. Manag. 65 (2013) 704e708. [45] H.M. Abusamaha, F. Dawoud, B. Al-Qalab, O. Ayadi, Experimental and theoretical study on a wind energy unit, J. Ecol. Eng. 20 (2019), https://doi.org/10.12911/22998993/109459. [46] O. Ayadi, I. Alsalhen, Techno-economic assessment of concentrating solar power and wind hybridization in Jordan, J. Ecol. Eng. 19 (2018) 16e23, https://doi.org/10.12911/22998993/ 81239. [47] A. Hasan, Wind energy in west bank and gaza strip, Renew. Energy 2 (1992) 637e639. [48] R. Shabbaneh, A. Hasan, Wind energy potential in Palestine, Renew. Energy 11 (1997) 479e483. [49] Y. Odeh, Wind Power Potential in Palestine: an Investigation Study for the Potential of Wind Power in Palestine, with Emphasis on the Political Obstacles, 2011. [50] T. Khatib, S. Alsadi, Modeling of Wind Speed for palestine Using Artificial Neural Network, 2011. [51] M. Elnaggar, E. Edwan, M. Ritter, Wind energy potential of Gaza using small wind turbines: a feasibility study, Energies 10 (2017) 1229. [52] Y.F. Nassar, S.Y. Alsadi, Wind energy potential in Gaza strip-Palestine state, Sol. Energy Sustain. Dev. 7 (2018) 41e57. [53] A.S. Badawi, An analytical study for establishment of wind farms in Palestine to reach the optimum electrical energy, An Anal. Study Establ. Wind Farms Palest. to Reach Optim. Electr. Energy. (2013). https://iugspace.iugaza.edu.ps/bitstream/handle/20.500.12358/ 18751/file_1.pdf?sequence¼1&isAllowed¼y. [54] A.S.A. Badawi, N.F. Hasbullaha, Y. Yusoff, S. Khan, A. Hashim, A. Zyoud, M. Elamassie, Evaluation of wind power for electrical energy generation in the mediterranean coast of Palestine for 14 years, Int. J. Electr. Comput. Eng. 9 (4) (2019) 2212e2219, https://doi.org/ 10.11591/ijece.v9i4.pp2212-2219. August 2019. [55] A.S.A. Badawi, N.F. Hasbullaha, S.H. Yusoff, A. Hashim, Energy and power estimation for three different locations in Palestine, Indones. J. Electr. Eng. Comput. Sci. 10 (2018). [56] H. Albisher, H. Alsamamra, An overview of wind energy potentials in Palestine, J. Energy Nat. Resour. 8 (2019) 98. [57] I.H. Ibrik, Techno-economic analysis of wind energy resources based on real measurements in West bankePalestine, Int. J. Energy Econ. Pol. 9 (2019) 26e32. [58] H.R. Alsamamra, J.A.H. Shoqeir, Assessment of wind power potential at eastern-Jerusalem, Palestine, Open J. Energy Effic. 9 (2020) 131e149. [59] CEGCO, Ibrahimyah Wind Power Station, 2021 [WWW Document]. URL, https://www. cegco.com.jo/Ibrahimyah-Wind-Power-Station (accessed 5.20.21). [60] O.O. Badran, Wind energy research and development in Jordan, in: World Renewable Energy Congress VI, Elsevier, 2000, pp. 2360e2363. [61] CEGCO, Hofa Wind Power Station, 2021 [WWW Document]. URL, https://www.cegco. com.jo/View_Article.aspx?type¼2&ID¼786 (accessed 5.20.21).

Wind energy in Jordan and Palestine Chapter | 7 [62]

[63] [64]

[65] [66]

[67] [68]

[69]

[70]

[71] [72] [73]

[74]

[75] [76]

269

NERC, Capacity Building in Wind Energy and Concentrating Solar Power Project (WECSP), 2011 [WWW Document]. URL, http://www.nerc.gov.jo/EN/ListDetails/Wind_ Projects/1029/1 (accessed 5.21.21). Jordan Wind Project Company, Home | Jordan Wind Project Company (JWPC), 2015 [WWW Document]. URL, http://www.jordanwind.com/ (accessed 5.20.21). Elecnor, Elecnor Wins the Contract to Build a 100-MW Wind Farm in Jordan - 21/05/2018 | elecnor.com, 2018 [WWW Document]. URL, https://www.elecnor.com/news/elecnor-winsthe-contract-to-build-a-100-mw-wind-farm-in-jordan-en (accessed 5.21.21). M. Ghazal, Spanish Firm to Build $112m Wind Power Plant in Maan, Jordan Times, 2014. Alcazar Energy, Alcazar Energy’s Al Rajef Wind Farm (ARWF) Achieves COD, 2018 [WWW Document]. URL, https://alcazarenergy.com/alcazar-energys-al-rajef-wind-farmarwf-achieves-cod/ (accessed 5.21.21). I. Rodriguez Alvarez, News Release from Vestas Mediterranean Vestas Wins 89 MW EPC Project in Jordan, 2016. R. Warrier, Kepco-funded $180m 89MW Fujeij Wind Project Begins Ops in Jordan Projects and Tenders - Construction Week, 2019. Online [WWW Document]. URL, https:// www.constructionweekonline.com/projects-and-tenders/259809-kepco-funded-180m89mw-fujeij-wind-project-begins-ops-in-jordan (accessed 5.22.21). Mass group holding, Wind Power Project - AlTafila, 2018 [WWW Document]. URL, http:// www.massgroupholding.com/English/Newsdetail-unit_2.aspx?jimare¼14&title¼Wind Power Project - AlTafila&cor¼7 (accessed 5.22.21). NS Energy, Vestas Wins EPC Contract for 52MW Abour Wind Park in Jordan, 2018 [WWW Document]. URL, https://www.nsenergybusiness.com/news/vestas-wins-epc-contract-for52mw-abour-wind-park-in-jordan/# (accessed 5.22.21). I. Shumkov, þþ, 2018 [WWW Document]. URL, https://renewablesnow.com/news/vestasto-build-52-mw-wind-park-in-jordan-634521/ (accessed 5.21.21). A.I.O. Zaid, A.M. Othman, A.O. Mostafa, Scope of utilization of a hybrid system of solar and wind energies as a storage system in Palestine, Int. J. Sci. Eng. Res. 7 (2016) 22e28. HCO news, West Bank Hospital Adding Wind Turbine, HCO News, 2012 [WWW Document]. URL, https://hconews.com/2012/10/24/west-bank-hospital-adding-wind-turbine/ (accessed 6.29.21). R. Tahboub, I. Ibrik, M. Tamimi, The potential and feasibility of solar and wind energy applications in Al-Ahli Hospital, in: A Paper Presented at the 4th International Energy Conference in Palestine, 2011. meetMED, Country Report on Energy Efficiency and Renewable Energy Investment Climate Palestinian Territories, 2020. Z. Milhem, Paving the Way for a Renewable Energy Future in Palestine, thisweekinpalestine, 2021.

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Part VI

Geothermal energy

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Chapter 8

Tapping hot rocks: a review of petrothermal energy and Enhanced Geothermal Systems (EGSs) Markus Loewer and Maximilian Keim Technical University of Munich, Geothermal-Alliance Bavaria, Munich Institute of Integrated Materials, Energy and Process Engineering, Germany

1. Introduction Most of the world’s geothermal energy is stored in so-called petrothermal reservoirs [1] that are characterized by insufficient permeability for geothermal use. Accordingly, petrothermal energy (Greek: petros: rock) attempts to transfer the thermal energy from the reservoir rock to an added heat transport medium (mostly water), which is circulated in artificial flow paths. This distinguishes them from the so-called hydrothermal systems, which use heat from existing thermal water in naturally permeable aquifers. It is, for example, estimated that the theoretical potential for electricity generation from petrothermal reservoirs in Germany is about 1100 EJ [2], which means that the resource could have a significant share in the energy supply from renewable energies (RE) in the future. However, the technology for using petrothermal reservoirs is rather complex and without innovative procedures it is not possible to establish sufficient heat exchange in the reservoir rocks for geothermal energy use. The most promising approach for the use of geothermal energy from reservoirs with low permeability is the use of preexisting structures like faults and fractures. The term “enhanced geothermal system” (EGS) refers to both the catalog of engineering measures and the geological system itself, whose low hydraulic permeability is artificially increased by these measures and thus made geothermally useable. The majority of EGS projects worldwide focuses on areas with elevated heat flux and on fault zones in crystalline reservoir rocks. Granites and gneisses provide favorable mechanical properties for the Renewable Energy Production and Distribution. https://doi.org/10.1016/B978-0-323-91892-3.00003-0 Copyright © 2022 Elsevier Inc. All rights reserved.

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application of rock engineering procedures and often increased radiogenic heat production [3,4]. Accordingly, EGS projects, and also the term “petrothermal energy” are mostly directly associated with crystalline rocks. However, EGS projects also access sedimentary rocks such as at Grob Scho¨nebeck, Germany or Rittershoffen, France [5,6]. In fact, the transitions between hydrothermal and petrothermal reservoirs are rather fluent [7]. Thus, even in hydrothermal reservoirs with insufficient permeability of the sedimentary rock, permeability can be increased by applying EGS in local fault zones [8]. EGS differs from “ordinary” hydrothermal energy in that the system is largely fault-controlled and the hydraulic conductivity is improved by extensive measures. International expert studies see the greatest future potential of geothermal energy in the successful implementation of EGS [9e11]. However, a standardized procedure remains to be established, despite several decades of experience. This review takes a critical look at the EGS technology and discusses the conditions under which this technology can have a future. In particular, open research questions and the effort required to adequately answer them will be addressed.

2. Technological retrospective The idea of extracting energy from geothermal reservoirs with artificially created heat exchange surfaces in rock was developed in the early 1970s at Los Alamos in New Mexico (United States), under the name “hot dry rock” (HDR) [12,13]. At that time, hydraulic fracturing technology (also known as hydrofrac) had already been known for more than 20 years in the oil industry, as well as in the field of developing repositories for radioactive waste [14,15]. As rock becomes hotter with increasing depth, the hydrofrac process was applied at greater depths to use the existing reservoir temperatures for geothermal energy production. This concept involves the creation of fractures by hydraulically increasing pressure in the reservoir with the aim of creating artificial flow paths in an impermeable rock matrix (e.g., Ref. [16]). By injecting water into the artificial flow path, the thermal energy is transferred from the surrounding rock to the fluid and then extracted through a second borehole, where it can be used, for example, to generate electricity [13]. The decisive factor here is that the two boreholes must be hydraulically connected via the artificially created flow system in order to create a closed circuit. At the same time, a thermal short must be avoided. After almost 20 years the project in Los Alamos was abandoned because of financial reasons (further details in Section 4.1). The HDR process was expected to make it independent of particularly favorable geological conditions, such as those naturally present in hydrothermal geothermal energy, which would have made larger geothermal resources developable practically everywhere in the world. This was an expectation that could not be fulfilled until today. In addition to the first experiments at Los Alamos, numerous pilot projects have been carried out in

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various countries over the past decades. All these projects were able to prove that hydraulic stimulation enhances the permeability of the reservoir rock. However, in most cases it was observed that the increase in hydraulic permeability was not greatly related to the creation of new fractures in the rock, but rather to the extension or displacement of fractures already present in the rock by shear fractures [17]. Consequently, in crystalline rocks, there is generally no widespread formation of new fracture surfaces, but rather an offset of already existing fracture surfaces whose friction has been reduced by fluid injection. This observation had already been made in the HDR project at Rosemanowes Quarry in the United Kingdom in 1977 [18] (see Section 4.2). These pilot projects have not only demonstrated that fractures are ubiquitous and widespread in the continental crust, but also that entire fracture zones, which can contain large amounts of thermal water, are common. The term HDR was less frequently used in the course of the observation of these “wet” rocks and was increasingly replaced by the broader term “enhanced geothermal system.”

3. Methodology Besides temperature, the most important factor in calculating the economic viability and potential of geothermal reservoirs is the amount of thermal water that can be extracted per unit of time. At greater depths, where temperatures become economically viable, optimal hydrogeological conditions are comparatively rare. In order to improve the hydraulic properties of the reservoir rock, stimulations are carried out at the EGS to connect naturally existing fractures and faults into a permeable network. Thus, a heat exchanger is created in the subsurface, which essentially has to meet two criteria: provide sufficient surface area and transfer length to ensure adequate long-term heat diffusion between the rock and the fluid. Second, high hydraulic permeability must be guaranteed in order to achieve sufficient flow and thus energy efficiency. In order to create an EGS, at least two wells (one injection and one production well) must be drilled to greater depths with correspondingly high temperatures (Fig. 8.1). The permeable fracture network is created between the boreholes by stimulation measures. To control and regulate the progress of the stimulation measures, acoustic sensors are used, which are placed in additional boreholes in the vicinity of the actual underground reservoir (see also Section 3.3).

3.1 Creation of the reservoir Basically, there are two mechanisms that occur as a result of hydraulic stimulation: 1. In hydraulic fracturing, tensile fractures propagate from the borehole into the surrounding rock, where the injection pressure of the stimulation fluid

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FIGURE 8.1 Illustration of an EGS with a production well (red) and an injection well (blue), as well as a monitoring well (gray). The geothermal plant at the surface is used to convert the extracted energy into district heat and/or electricity. The thermal water passes through a heat exchanger and then through an organic Rankine cycle (ORC) or Kalina cycle (in the case of electricity generation). The steam from the heated working fluid is converted into electricity by a turbine. The cooled thermal water enters the reservoir with fresh water through the injection well, where it is heated again. Modified from S. Huang, Commentary: geothermal energy in China, Nat. Clim. Change, 2 (8) (2012), 557e560.

must be higher than the minimum principal stress ðs3 Þ and the tensile strength of the intact rock (see Fig. 8.2 [19]). Here, already existing cracks oriented perpendicular to the principal stress can be opened or widened by exerting pressure beyond the minimum principal stress. To create a whole stack of cracks, fluid injection is carried out at narrow intervals. 2. In hydraulic shear, an offset of already existing crack surfaces is set in motion by the applied fluid overpressure. The prerequisite for this is that the cracks are oriented favorably in the direction of the main stress in order to be able to initiate a shearing process during the stimulation.

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FIGURE 8.2 Comparison between hydraulic fracturing and hydraulic shearing. (A) Hydraulic fracturing opens up new or existing expandable fractures by injecting fluid under high pressure, where the injection pressure must be higher than the minimum principal stress ðs3 Þ. (B) Hydraulic shearing aims to reactivate preexisting natural fractures with a preferential orientation, where the injection pressure can be lower than the principal stress. After V. Gischig, G. Preisig, HydroFracturing versus hydro-shearing: a critical assessment of two distinct reservoir stimulation mechanisms, Proceedings to the 13th International Congress of Rock Mechanics, ISRM 2015, 10e13 May 2015, Montre´al, Canada, 2015.

Hydraulic shearing is usually achieved at longer intervals or in the open borehole (see Fig. 8.2 [19]). Both mechanisms occur in the context of hydraulic stimulation and can be considered as end members as described above. Which mechanism predominates depends on the rock structure, the existing stress, and the orientation of the existing cracks with respect to the main stress. Experience from large-scale stimulation experiments in the crystalline basement suggests that hydraulic shear dominates within a few decameters of the injection point, while hydraulic fracturing is particularly relevant in the near-well field [20]. Experiments in the Mayet de Montagne granites in France have also shown that channeling (formation of a few preferred main flow paths) prevents further propagation and exploitation of multiple hydraulic fractures [21,22]. Regardless of which process dominates, the direction of reservoir propagation and the geometry of the stimulated volume are highly dependent on the in situ stress and direction, as well as the natural fracture network [23]. The particular mechanism triggered by the stimulation has different effects on hydraulic permeability. At depths relevant for EGS, an increase in permeability of at least two to three magnitudes is targeted [19]. Previously, several projects have demonstrated that the process of hydraulic shearing by sliding along cracks can cause an increase in permeability of this magnitude [23,24]. The key difference between these two mechanisms is that shearing is practically irreversible due to the shifting and rearrangement of the contact surfaces relative to each other. Therefore, the shear crack expansion remains open even after the application of pressure. This is not the case with fracture cracks. Here, the resulting crack that has developed can only be kept open and hydraulically permeable with the help of proppants.

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3.2 Borehole stimulation Numerical studies by Gischig and Preisig [19] suggest that hydraulic stimulation in long open sections of the borehole does not cause uniform widening of all fractures across the borehole (see Fig. 8.3A). Instead, the stimulation selectively focuses on a few favorably oriented fractures under critical stress in the open section. Therefore, hydraulic shearing leads to heat exchangers with flat geometry (2D), rather than spatial reservoirs (3D). In agreement with the results of the numerical studies, flat reservoirs are also found in the EGS projects at Basel, Soultz-sous-Foreˆts, and the Cooper Basin. Due to the geometry of the reservoir, the smaller heat transfer area can become a decisive disadvantage despite good flow rates. Injection via long open borehole sections is therefore rather unsuitable for creating isotropic, that is, directionindependent, 3D reservoirs. Instead, controllable stimulation with several sections is preferable (Fig. 8.3B), which reduces the influence of larger, critically stressed faults by targeting smaller fractures [20]. A deviation of the drilling direction in the reservoir from vertical to horizontal can contribute significantly to an improvement of the stimulation measures. With a good knowledge of the local stress field and the directional pattern of existing faults, drilling can be placed in the optimal direction with the highest possible efficiency for stimulation, with reference to the stimulation effect. Horizontal drilling also allows relatively long drilling sections in the reservoir and thus a larger entry and volume exchange area. According to the study described in Ref. [25], the creation of several smaller reservoirs by “multiple fracs” connected by horizontal wells is considered the most economically promising. More importantly, the generation of multiple smaller fracs carries a lower risk of increased seismicity than large-scale stimulation

FIGURE 8.3 (A) Illustration of a long open drilling section with intersecting faults of different orientations. (B) Illustration of several open sections separated from each other, allowing specific fractures to be targeted by hydraulic stimulation.

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operations, which can cause uncontrolled shearing. The goal of the stimulations is to achieve a satisfactory connection between the wells, which can be assessed by circulation tests. According to Ref. [17], the artificially created reservoir must meet the following expectations: 1. For the longest possible system life, a large volume of rock with a large heat exchange surface should be hydraulically accessible. 2. For low energy consumption during pumping, the flow resistance between the boreholes must be as low as possible. A flow resistance of 0.1 MPa/L/s is often stated as the desired target. 3. For the most efficient and low-risk system, fluid losses to the surrounding rock should be as low as possible. Experience from previous projects has shown that it is generally difficult to reduce the flow resistance between boreholes to achieve the desired target of 0.1 MPa/L/s. The flow resistance can be reduced by decreasing the distance between the boreholes. The distance, however, should not become too small, since falling below a certain threshold would lead to thermal or hydraulic short-circuiting and thus a rapid drop in production temperatures. For this reason, a compromise must be found between designing for low flow resistance and the longevity of the system. The Soultz-sous-Foreˆts project is a milestone with respect to the high demands that are placed on the artificial reservoir heat exchanger. Despite the considerable distance of 450 m between the boreholes, the flow resistance was reduced to the target of 0.1 MPa/L/s by means of hydraulic and chemical stimulation, while avoiding fluid losses (see Section 4.4).

3.3 Chemical stimulation Petrothermal geothermal reservoirs often show a poor hydraulic connectivity, restricting the heat extraction from the subsurface [13]. For enhancing the hydraulic connection between the reservoir and the geothermal wells chemical stimulation methods are used beside the hydraulic (and thermal) stimulation methods (e.g. Refs. [26,27]). The goal of chemical stimulation is to enhance the permeability of the reservoir by removing material deposited in fractures, fissures of the reservoir or the borehole, for example, by scaling or drilling mud deposition [27]. One advantage of chemical stimulation compared to hydraulic stimulation is the minimized risk inducing seismicity, provided that the chosen stimulation pressures are low. Chemical stimulation methods have been used in the oil and gas industry for a long time and have been also adopted to geothermal wells in the last 4 decades [27,28]. Chemical stimulation agents are typically hydrochloric acid (HCl), hydrofluoric acid (HF), and in rarer cases also organic acids like nitrilotriacetic or citric acid (e.g. Ref. [29]). They are used individually or as mixtures. In most documented cases, acidification includes three steps: (1) preflush (HCl), (2) main flush

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(HCleHF mixture), and (3) overflush (HCl, KCl, NH4Cl, or freshwater) [27,30,31]. As additives, typically corrosion inhibitors were used to protect the casing string (e.g. Ref. [29]). More aggressive acids like HCl and HF are generally used for near-well and organic acids for far-field stimulation measures. Two different modes of chemical stimulation methods are generally conducted: (A) matrix acidizing which is performed below the fracturing rate and pressure, meaning that the reaction takes place in natural fractures and pores, and (B) fracture acidizing, which is performed above the fracturing pressure affecting mostly newly formed fractures [30]. The first application of chemical stimulation in the field of geothermal energy was at the Fenton Hill project in the United States. Here a mixture of Na2CO3 with NaOH solution was injected into the metamorphic reservoir. However, the permeability was not improved significantly due to the lack of fracture networks in the reservoir ([33] and references therein). A comprehensive overview of chemical treatments in several geothermal wells over 30 years can be found in Refs. [27] and [31]. The list shows that for many projects an increase in productivity was achieved through chemical treatment. The project in Soultz-sous-Foreˆts uses a variety of chemical stimulation measures and thereby is described in more detail. In all wells, long-term injection of HCl was performed at low concentrations. The objective was to dissolve secondary carbonates existing in the fractures [29,32]. Also, stimulation by so-called mud acid (HF þ HCl) was performed in all wells in order to dissolve especially clay minerals. In contrast to the mud acid injection, a clear improvement of productivity by HCl was not observed in all wells. In one well, nitrilotriacetic acid was used in order to form complexes with Fe, Ca, Mg, and Al, and thereby enhance the dissolution of corresponding minerals. The stimulation showed no success and reduced the productivity. In two wells, further organic acids (organic clay acids) were tested. The retardation effect of organic clay acids fluid allows stimulation deep in the reservoirs, compared to HCl mixtures (retarded acid systems). The injection of organic clay acids shows positive effects on the productivity of one well, however there were only marginal effects in other tested wells [29]. In general, the project shows that an increase in productivity by chemical stimulation was reached by a factor of 1.12e2 [29]. The injectivity and productivity of each well were affected differently [27]. Hydraulic tests were carried out in this well to evaluate the impact of the hydraulic stimulation. The authors [29] mentioned that a further improvement could be reached if selected zones were stimulated. In Soultz-sous-Foreˆts, the acid was injected through the whole open-hole section and therefore the permeability (and stimulation effect) was strongly dependent on preexisting fractures [33]. An increase in productivity was also achieved at the Grob Scho¨nebeck project in Germany by acidification of the sandstone reservoir with low-concentration HCl [26]. In addition to field trials, numerous

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chemical stimulation studies have been conducted to improve hydraulic conductivity, in the form of laboratory tests to investigate the chemical processes of different rock types and chemicals, sometimes even before the actual stimulation [28,30]. Besides hydraulic and chemical stimulation of geothermal reservoirs, thermal stimulations also are used for enhancing the productivity of geothermal wells. For this, cold water is injected. Due to the low temperature of the water compared to the temperature of the rock, the stress in the rock changes, leading to stimulation of natural fracture networks or the initiation of new fractures (e.g. Ref. [26]). The authors in Ref. [34] reported that they increased the permeability at the Raft River site (United States) successfully by thermal stimulation. In summary, chemical stimulation can significantly improve reservoir productivity, depending on the reservoir and rock type. The chemical treatment program must be decided for each individual project (and each individual well) and has to be adopted to the reservoir rocks.

3.4 Monitoring The shear mechanism, and thus the sliding of two fault surfaces against each other, can lead to significant induced seismicity (c.f., in the Basel geothermal project with a magnitude of 3.4; Section 4.5). Fracturing, in which tensile fractures occur, is in principle less seismogenic than shearing. However, shear failure can also occur here, and thus seismicity also. Studies described in Ref. [35] show how, depending on the combination of material properties and applied stress, several tensile cracks can combine to form shear cracks during hydraulic stimulation measurements, or how shear cracks can connect individual tensile cracks. Shear-induced slip doesn’t need to result in significant seismicity, but can also be aseismic. Depending on the in situ stress and geology, aseismic slip can make a significant contribution [36]. Therefore, a detailed understanding of the causes and differences between aseismic and seismic slip resulting from stimulation measures is an important research topic in order to minimize the risks caused by stimulation. While aseismic slip can only be detected indirectly, all seismic events can be detected using monitoring methods. The detailed location and evaluation of microseismic activity provides important information on the underlying mechanisms and thus also on the formation or extension of cracks. Therefore, monitoring is essential to visualize by means of 3D visualization of the results of the stimulation process and the associated permeability increase. Fig. 8.4A shows the microseismic cloud around the three boreholes of the EGS project in Soultz-sous-Foreˆts, which was generated during the stimulation process (after [17]). From the seismic cloud, a geometric image of the reservoir can be created. Fig. 8.4B shows a horizontal section through the main fracture of the Soultz reservoir at 4900 m depth.

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FIGURE 8.4 (A) Microseismic clouds around the project wells in Soultz-sous-Foreˆts in perspective view. (B) Crack at 4900 m depth deduced from the hypocenter density distribution. From S. Baisch, R. Vo¨ro¨s, E. Rothert, H. Stang, R. Jung, R. Schellschmidt, A numerical model for fluid injection induced seismicity at Soultz-sous-Foreˆts, Int. J. Rock Mech. Min. Sci. 47 (2010) 405e413.

4. EGS in the context of global deep geothermal energy High temperatures at shallow depths are mainly found in areas of continental plate subduction and associated volcanism (so-called high-enthalpy reservoirs; Fig. 8.5). Consequently, the use of geothermal energy, especially for electricity generation, is geographically limited. To reach high subsurface temperatures far from plate boundaries, it is necessary either to rely on intracontinental rift fractures (e.g., the East African Rift Valley) or to extract geothermal energy from greater depths (low-enthalpy reservoirs). This shows that natural hydraulically permeable rock layers in the deep subsoil are mainly limited to deep sedimentary basins or fault zones and are therefore also present only to a limited extent. A recent overview of EGS projects around the world is provided in Refs. [33,37,38]. Each project has helped to move closer to future commercialization of EGS technology. In particular, it has been demonstrated that fractures and, in some cases, entire zones of fractures are ubiquitous in the subsurface [17]. Not all EGS prototypes around the world have been designed as large-scale deep geothermal projects. However, as project details would be beyond the scope of this chapter, five key projects are discussed below.

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FIGURE 8.5 Distribution of geothermal plants (black dots) and various EGS projects (stars) worldwide, including plate boundary types and major zones of active volcanism. From I. Moeck, Catalog of geothermal play types based on geologic controls, Renew. Sustain. Energy Rev. 38 (2014) 867e882 and modified using data from S.-M. Lu, A global review of enhanced geothermal systems (EGS), Renew. Sustain. Energy Rev. 81 (2018) 2902e2921.

4.1 Fenton Hill (United States) The Fenton Hill HDR project, located in the Valles Caldera in northern New Mexico, was planned and supervised for 23 years by the Los Alamos Research Center, which became famous for its nuclear weapons research. In the initial phase of the project in 1972, an exploratory well (“Granite Test,” GT-1) was drilled 785 m deep into the granitic basement, in which the first hydraulic fracturing tests followed the year after [13]. The experiment provided fundamental information on the suitability of the drilling tool and hydraulic fracturing in a crystalline basement. In 1979, an HDR research field was then established with two wells drilled to a depth of 2.6 km, followed by another test field with a doublet to a depth of 4400 m [18]. With flow rates of 7e16 L/s and temperatures of 140 C, a small power plant with a binary circuit was installed on the first research field, which provided 60 kW of electrical power. After extensive fracturing measurements and lateral drilling, hydraulic communication was also established on the second research field. This resulted in flow rates of 12e14 L/s and a flow impedance of 2.1 MPa s L1 [39]. However, in the closed-loop flow test, no stable flow rate could be achieved, and circulation was interrupted. In addition, fluid losses of up to 30% occurred. However, some engineers at the time assumed that similar flow rates to those at the first site would have been achieved after a few weeks. At a production temperature of 210 C, a thermal output of 14 MWth was reached [13]. The Fenton Hill HDR project was halted in 1996 due to cost considerations.

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4.2 Rosemanowes Quarry (United Kingdom) The first European HDR project was carried out by the Camborne School of Mines in Carnemenellis granite at Rosemanowes quarry from 1977. The granite here is characterized by numerous natural fractures to great depths. In contrast to Fenton Hill, the crystalline basement was therefore considered more as a kind of discontinuous fractured material whose natural fluid capacity can be increased by stimulation measures. The resulting reservoir is therefore not completely isolated from the outside world. In fact, these considerations about expanding the permeability of an unconfined reservoir by means of hydraulic stimulation were already the basis for later EGS projects. In 1983, after several near-surface drillings and initial experiments, two boreholes were drilled to a depth of 2000 m in the granite [18]. The drilling layout was similar to that of the Fenton Hill project, with the difference that the drill holes were deviated parallel to the maximum horizontal stress and the vertical spacing of the drill holes was 300 m [39]. Extensive hydraulic stimulation measurements initially failed to establish a hydraulic connection between the drill holes. With a third well drilled at 2652 m, a flow rate of up to 24 L/s with thermal water temperatures of 100 C could be achieved after stimulation measurements. However, the following years of high-pressure flow tests with subsequent overstimulation led to a thermal short. The experiments led to the understanding that natural fractures are widespread in granite and that the formation of the fracture network is dominated by natural fractures, regardless of the fracturing method used [18].

4.3 Hijiori (Japan) The Japanese HDR Hijiori project (North Honshu) was carried out between 1985 and 2002 by the Japanese organization NEDO in a high-enthalpy volcanic zone in granodioritic reservoirs. One injection well and three production wells were drilled into an initially shallower reservoir (1800 m at 250 C). The number of production wells was intended to compensate for the low production rates of previous projects [40]. In the second phase, the wells were deepened to a slightly deeper reservoir (2300 m at 270 C) and the well arrangement was changed: one central injection well and two outer production wells (spaced 70e130 m apart). As in the United Kingdom, reservoir stimulation has shown that widespread natural fractures and cracks dominate fluid flow and that “opening” the reservoir results in large fluid losses (30%e60%). Stimulation measures mainly affect only a few specific fractures, which creates a risk of short-circuiting. However, the selective use of open hole packers is no longer possible above 200 C [67]. An accurate analysis of local stresses is considered particularly important for the development of HDR. Too high or too low injection pressures have a significant long-term impact on reservoir productivity and heat recovery [40]. Long-term (550 days) injection tests at

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Hijiori with pumping temperatures of 150e190 C (despite the much higher reservoir temperatures) resulted in maximum pumping rates of just under 14 L/s, which would correspond to a heat output of about 8 MWth (return of about 50 C). In addition to the low production rates, long-term testing revealed particular scaling problems such as anhydrite, calcite, and amorphous silicate minerals in the production wells and pipelines. In August 2002, the Hijiori project, together with the other Japanese HDR project at Ogachi [41], was shut down after 17 years.

4.4 Soultz-sous-Foreˆts (France) This European project in the central part of the Upper Rhine Graben in France introduced the “EGS” designation during the project. It was the first project in the world to achieve the long sought-after goal of a reservoir impedance of 0.1 MPa/L/s through stimulation measurements [42]. The project started in 1988 as a research project and is now a commercially used EGS plant, generating an electrical power of about 1.4 MWel at a production rate of 35 L/ s and temperatures of 150e160 C (return temperature: 70e80 C) [43]. The geological context of Soultz is characterized by a thermal anomaly (up to 3.7 km depth) and numerous fault zones almost parallel to the main direction of the trench [39]. The largest of these faults are responsible for 90% of the natural water flow in the granite [44]. Four deep boreholes with open sections of 500e750 m were drilled in Soultz, one of them to 3500 m and three others (later) to 5000 m depth. Initial stimulation measurements indicated that the increase in permeability was mainly due to weak natural fractures in the hydrothermally altered shear zones that cross the boreholes and tend to shift due to stimulation [45]. Two EGS systems were produced during the project period at 2800e3600 m (doublet system, now abandoned) and 4400e5000 m (triplet system, in operation) by hydraulic stimulation. In both reservoirs, flows of 25e55 L/s could be generated. To avoid flow losses, thermal water pumps were used for the first time in an EGS [39]. Due to seismicity induced at higher injection rates, the injection rate in the central well was reduced. The project with the commercial device represents a milestone in the technology. However, part of this success may be due to the advantageous tectonic conditions of the Upper Rhine graben structure [39].

4.5 Basel (Switzerland) The petrothermal project in Basel (“Basel Deep Heat Mining”) marks a central point in EGS technology, namely that of the public perception of the technology. During the project several seismic events of medium magnitude (M > 3) have occurred during the high-pressure stimulation of the granitic reservoir rocks at about 5 km depth [46]. These events were felt by the general public and brought media attention to the technology. The reservoir

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in Basel can be regarded as a granitic rock body of very low hydraulic permeability, which has few fractures with equally low permeabilities. In 2006, stimulation measures irreversibly increased the permeability by two magnitudes. However, the hydraulic contact created in the reservoir differs significantly from the EGS concept of a densely distributed fracture network interconnected over a large volume of rock [24]. Analysis of the microseismicity and flow directions indicates that the reservoir had developed along a single definite fracture zone bounded by a relatively narrow area of a few decameters. Jung [39] infers from the evaluation of the seismic plume that lateral cracks (wing-cracks) were generated by the stimulation. Accordingly, Jung [39] suggests the “wing-crack” model to describe the increased seismicity, in place of the notion of a shear process. The EGS project in Basel was discontinued in December 2009 after an extensive expert review of the occurrence of induced seismicity during stimulation [9]. As learnt from the experience at Basel, new stimulation concepts, such as the multicrack method, should be considered for future projects to create reservoirs with more spatial extent and lower seismic risk [46]. Seismic shaking also occurred in a later hydrothermal project in St. Gallen and near Strasbourg, in which the latter has ceased operations due to seismicity. In St. Gallen, seismic events led to less concern but the project had to be discontinued due to insufficient production rates.

5. The technical potential of the example of Germany The technical potential for electricity generation from petrothermal systems in Germany is estimated at 1100 EJ (35 TWa), which would include in particular the extensive crystalline area of central and southern Germany, but also the Rotliegende in the North German Basin, as well as the crystalline Upper Rhine Graben [2]. According to Ref. [2], the technical potential for combined heat and electricity production would be higher by a factor of 1.5 than for electricity alone, which is explained by the low efficiency of electricity production (about 10%e12% for electricity production, compared to almost 100% for heat utilization) [47]. If technical, structural, and legal restrictions are also taken into account (e.g., restrictions on use in nature parks and water protection areas, biosphere reserves, etc.) and if only heat supply is considered (and assuming 2500 full load hours per year), this corresponds to a technical potential for district heating of 86e191 GWth, or 214e478 TWh/a [48]. Considering the technical potential and thus also the heat demand density, this corresponds to about half of the technical potential that could be made available for heat supply in Germany. From a purely geological point of view, large parts of central Germany, and thus a large part of the German crystalline subsurface, would be suitable for petrothermal energy. However, the potential of EGS and especially of petrothermal EGS is much more difficult to quantify than the petrothermal

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potential alone, as EGS requires knowledge of the relevant fault and fracture zones. Crystalline rocks belonging to the Variscan zone and extending over large parts of Europe contain different geothermal reservoirs [49]. However, most areas are poorly characterized in terms of subsurface exploration. In Germany, in addition to the research projects in Hannover and GrossSchoenebeck, there are three hydrothermal EGS plants (Landau, Insheim, and Bruchsal) on the Upper Rhine Graben (as well as various other projects on the French and Swiss sides of the Upper Rhine Graben). However, there is much less experience with petrothermal EGS projects. In the past, the technology was able to prove that it was technically feasible, as the European research project in Soultz-sous-Foreˆts showed. Whether petrothermal EGS can be economically viable, especially for electricity or heat production, has however not been proven yet [39]. One reason is that, despite almost 50 years of experience, a relatively small number of pilot projects and global research projects have been put into practice compared to the research and development effort in the hydrocarbon industry. At the same time, the greatest potential for cost reduction in deep geothermal energy is expected to come mainly from learning and scaling effects, especially in the area of drilling and stimulation technologies, as well as from the improvement and optimization of plant technology [50]. Similar to purely hydrothermal power-heat projects, drilling costs, which increase disproportionately with depth, are the most important cost factor for petrothermal geothermal energy [48].

6. Discussion and comparison 6.1 HDR versus EGS In theory, there is a clear separation between the initial idea of HDR and the later EGS method [39]. The EGS method focuses on the widening and shearing of already existing natural fractures and faults, whereas the HDR method focuses on the targeted hydraulic connection of boreholes via numerous artificially created fractures (see Fig. 8.6). The latter involves keeping the newly created flow zones open with the help of proppants. However, due to the complexity of the subsurface, an increase or change in pressure may in principle also simultaneously cause shear movements and new fractures. Brown et al. [13] pointed out that one of the most important characteristics of “real” HDR projects is their spatial constraint. This means that the HDR reservoir must be sealed on all sides by dense rock and at the same time be in a kind of “stress cage” (an annular zone of overcompressed rock, due to the effect of internal overpressure). Another feature is that HDR systems are created completely artificially, that is, no natural fractures can be used as heat exchangers or have connections with them. By Brown’s definition [13], the Fenton Hill project was the only HDR project in the world to date. However, during the Rosemanowes project experience, it was

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FIGURE 8.6 Schematic representation of the HDR concept (A) with vertical fractures, as realized in the initial project at Fenton Hill (Los Alamos), compared to the EGS concept, which assumes the presence of natural cracks (B; according to the review article in Ref. [39]).

recognized that cracks are mainly generated in the immediate vicinity of the borehole and do not propagate into the intact rock, but rather along weak points such as healed fractures. On the research side, either a new version of the classical HDR method (multi-frac concept) or the EGS method is being followed, depending on the geological context and the question at hand. The latter is the only one that has already reached technical maturity in the Upper Rhine Graben.

6.2 Back to the HDR concept? According to Ref. [39] the EGS concept initially gained acceptance from the 1980s onward for technical reasons, since the process did not require temperature-resistant open-hole injection packers. This had consequences in the technical execution of the stimulations: on the one hand, EGS well path planning aims at a different orientation of the borehole with respect to the main stress field than the HDR method, and on the other hand, EGS aims at vertically penetrating as many natural fractures as possible, which have to be stimulated with very large amounts of water. The latter has the risk of inducing uncontrolled seismicity. As a criterion for the longevity of the reservoir, the heat exchange area was replaced by the accessible rock volume. By changing the original (HDR) concept, into a shear and fissure extension-based concept (EGS), according to Ref. [39], the progress of HDR technology was held back for several decades. The risk of intense seismic activity, is increased in EGS projects compared to HDR. Jung [39] suggests that shear of the connected fracture network is not the key mechanism of reservoir formation in EGS, but rather the formation of a single large lateral crack that forms at irregularities

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such as natural fracture ends or in the vicinity of larger, partially healed fault zones (so-called wing crack). The large shear offset at the root of the lateral arms allows for the occurrence of larger seismic events, which can occur both during the stimulation period and during backsliding during the pressure adjustment. Accordingly, it is necessary to prevent the occurrence of lateral cracks of larger dimensions. Jung [39] recommends replacing the EGS concept with the original multi-frac concept according to the HDR method, with the main difference being that in the concept the targeting of tensile cracks should be replaced by multiple lateral cracks (about 30e40), on a horizontal parallel borehole section of 1 km length and 500 m apart. Appropriate systems would be capable of operating for at least 25 years, with a pumping rate of 100 L/s and an electrical output of 5e10 MW. The basis for a potential implementation of the multi-frac concept is a progress in the drilling technology. In particular, practical experience with directional drilling sets and drill bits in deep deviated wells, as well as cementation in the long horizontal drilling section, are of great relevance to minimize investment risks for later routine application [51]. Regarding the generation and geothermal operation of multiple fractures to connect two parallel horizontal drilling branches in the deep subsurface, no empirical data are available currently.

6.3 Differences from natural gas and oil fracking Fracking performed by the oil and gas industry does not differ from the processes during geothermal stimulation in terms of mechanics but in terms of dimensions, materials, and fluid input. Hydraulic fracturing in geothermal systems usually focuses on comparatively dense rocks (granite, gneiss, granodiorite, etc.). In contrast, oil and gas fracking is commonly related to sedimentary rocks like shists and sandstones. Accordingly, hydraulic stimulation in natural gas/petroleum reservoirs uses different pressures because the rocks have lower shear strengths and stresses. For the inflow improvement of hydrocarbons toward the production wells, only hydraulic stimulations in the vicinity of the well (meter to decameters) are necessary [52]. In contrast to natural gas fracking, the volumes of water used in EGS projects are much higher and must be injected within several days to weeks [9]. For conventional natural gas production, a combination of horizontal drilling technology and multi-frac methods is used. Accordingly, the HDR multi-frac concept, as shown in the section above, is strongly oriented on the concept for natural gas fracking. The EGS process, on the other hand, stands out more. With hydraulic stimulation in deep geothermal energy, the frac fluid consists of pure water. If, however, the classic HDR process is used again, the use of proppants will become unavoidable. In the past, quartz sand or ceramic pellets were used for gas production, as well as other substances as

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chemical additives to keep the artificially formed fractures open. Typical fluid mixtures consist of up to 99.8% water. In Germany, for example, any additives can be approved without restrictions [25].

7. Environmental aspects The geothermal technology aims to make a valuable contribution to the reduction of greenhouse gases, especially in low-enthalpy areas. In principle, this is achieved both by preventing unnecessary greenhouse gas emissions from energy imports and by eliminating the need for centralized or decentralized combustion of hydrocarbons for heating or electricity production. The implementation and operation of geothermal plants is not entirely free of risks to the environment, but this also applies to other energy generation technologies. The term “environment” is used here to include ecological and social factors, such as the occurrence of seismic events.

7.1 Life cycle analysis The environmental performance of deep geothermal energy, like any other technology, should not be viewed in a one-sided manner. Energy must be invested in the deep drillings and a thermal water circuit must be kept running with pumps to transport the heat to the surface. In addition, there is the production and use of materials, as well as plant dismantling and backfilling of boreholes (c.f., [53]). Life cycle analysis (LCA) aims to balance the environmental footprint of products (in the case of EGS plants, electricity and heat or both) over their entire lifetime. Due to the small number of LCAs of low-enthalpy plants, especially also hydrothermal geothermal plants, and the small amount of long-term data, no clear picture can be obtained regarding the LCA of EGS plants. However, studies show that the life cycle assessment of power generation plants is highly dependent on the ORC working fluid used and the coverage of captive power demand [54]. A recent study described in Ref. [53] shows that geothermal plants for district heating have a very good environmental performance. The environmental performance of EGS is limited to the pilot project in Soultz-sous-Foreˆts and subsequent plants in the Upper Rhine Graben, which do not provide a consistent picture [55,56]. The reason for this can be found, among others, in the drilling operation, which is characterized by different drilling meters and drilling duration, as well as by different drive systems (diesel, electric). The previous studies conclude that the combined production of electricity and heat, as well as the use of innovative drilling tools (e.g., thermal spallation drilling), as well as the longest possible use or lifetime of the geothermal plant can improve the environmental balance most significantly [55,56].

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7.2 Groundwater protection and scalings Deep fluids differ significantly in their composition from near-surface groundwater due to the age and weathering of the surrounding rock. With increasing depth, salt content of the water (brine) usually increases and becomes undrinkable and toxic. While hydrothermal brine in contact with limestone and dolomite rock has a neutral pH and contains dissolved ions of the carbonate rock, petrothermal waters in crystalline rock are mostly basic and have higher ion concentrations. Deep wells are designed in which the thermal water transported to the surface and reinjected is isolated from the near-surface aquifer by multiple barriers (standpipe, anchor pipe, interstitial cementing, and injection/production pipe). Deep fluids also contain gases, some of which are toxic (hydrogen sulfide, radon) and explosive (methane, hydrogen) or promote the greenhouse effect (CO2, methane). Accordingly, pressure maintenance and various filter devices are used to prevent any uncontrolled emission of the gases. It is even possible to convert them into a commercial secondary use by means of separation. The exploitation of fluids (gases or ions) seems to be an especially new field for investors at the moment. The possibility of extracting lithium from geothermal brine is becoming increasingly attractive due to the growing demand for lithium-ion batteries [57]. The high concentration of dissolved elements in thermal water results in various precipitations (so-called scalings: carbonates, sulfates, hydroxides, sulfides, etc.) within the thermal water circuit, depending on temperature and pressure differences, mainly caused by temperature and pressure changes (e.g. Refs. [58,59]). Crystalline rock contains a relatively higher concentration of radioactive isotopes (potassium, uranium or thorium, and radon) and heavy metals (lead, copper, arsenic, etc.) compared to carbonates. In the case of radionuclides, which can accumulate in a concentrated manner in the form of precipitates and, in extreme cases, accumulate on above-ground components of the geothermal plant, certain radiation protection measures must be applied [60]. According to the Federal Office for Radiation Protection in Germany [61], the maximum dose of 1 millisievert (mSv) per year can be exceeded for employees in geothermal plants under unfavorable conditions (for comparison, the average effective annual dose of flight personnel is up to 2 mSv) [61]. In this case, dose reduction measures must be considered and work on certain parts of the plant may only be carried out within a limited time frame. The radiation exposure must be monitored accordingly.

7.3 Induced seismicity The Human-induced Earthquake Database (HiQuake) includes the records of 700 cases of anthropogenically induced earthquakes over the last 150 years [62].

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Examples of cases of induced seismicity include tunneling, flooding, dams, nuclear bomb testing, glacier erosion, groundwater withdrawal, fracking, gas storage, carbon sequestration, mining activities, and deep geothermal energy. In many cases it is not possible to distinguish whether a seismic event was directly induced by human activity or indirectly triggered, or whether it occurred naturally [63]. The energy release can basically carry seismic or aseismic (slow rupture without triggering earthquakes) signatures, and the relationship between fluid injection, earthquakes, and an aseismic subsurface change is scientifically debated. Evans and Valley and Amman et al. [17,23] assume that induced seismicity is inevitably associated with hydraulic stimulation in EGS projects, since sliding is due to increased pore pressures during fluid injection, which occurs so rapidly that seismic waves must inevitably be generated in the process. Factors that increase the likelihood of seismic events include stimulationspecific parameters (the rate, volume, and depth of injection) and reservoir characteristics (stress state, rock type, proximity to faults). According to Ref. [64], the risk of major seismic events can be reduced by varying and optimizing hydraulic stimulation frequency and strength. For this purpose, the authors proposed a so-called fatigue stimulation using hydraulic fracking and several pressure and relief cycles under increasing stimulation pressure. The fatigue technique is intended to create a larger and more complex fracture network than conventional stimulation, which reduces the risk of major seismic events. Currently under construction and planned EGS projects are still confronted with the challenge of increasing the natural hydraulic permeability by several magnitudes and to accept microseismic events or to use them for monitoring; at the same time, however, keep the events on such a small scale that they can only be perceived by sensitive sensors and not, or only to a small extent, by humans. The first promising experiments with an innovative stimulation technique have already been conducted at an intermediate scale [64]. Furthermore, seismic events can be reacted to at an early stage by using monitoring systems in combination with a response plan [65]. Such a procedure can significantly reduce the risk of noticeable events. A comprehensive overview of potential environmental impacts resulting from deep geothermal stimulation activities is provided in Ref. [66].

8. Conclusion The availability of deep natural thermal water aquifers (hydrothermal energy) is limited worldwide. Most geothermal energy is stored in relatively dense and low-permeable rocks. Without the improvement of natural flow paths with the help of EGS technology, geothermal energy in petrothermal geological settings cannot be extracted using the current state of the art. The further development of petrothermal energy is therefore dependent on this

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technology [25]. One reason for the slow technology development is seen in the low number of demonstration plants. According to Ref. [50], fundamental research questions about the creation of hydraulic conductive and sustainable reservoirs can only be answered by demonstration at suitable sites. To potentially identify sites for demonstration projects, the regional geology must be extensively explored. With regard to sufficiently high flow rates, the EGS technology, with the process of hydraulic shearing of already existing fractures, is the only proven technology so far. This is largely due to the projects in the Upper Rhine Graben, which have been brought to commercial maturity. However, as a rift system, the Upper Rhine Graben has a special geological setting which, in terms of tectonics and geology, shows hardly any parallels to many other areas. On the French side of the Upper Rhine Graben, seismic events related to an EGS project in the Strasbourg area have led to a halt of the project. However, on the French as well as the Swiss side, several EGS projects, in particular also for heat supply, are still in planning. Both hydraulic shearing and hydraulic fracturing are fundamentally associated with microseismic events. Seismicity associated with hydraulic shearing is mostly directly due to an increase in permeability caused by pressure exertion. In contrast, the occurrence of seismicity due to the fracking process is not clearly correlated with an increase in permeability. The multi-frac concept recommended in Ref. [39] and elsewhere, according to the original HDR procedure, is intended to prevent major seismic events while eliminating dependence on existing faults. However, unlike EGS, this relies on the use of proppants and additives. There is still a great need for research in the field of petrothermal energy. Depending on the geological setting, the question on which technology guarantees both the lowest risk of noticeable seismic events and the success of finding sufficient quantities of thermal water, must be evaluated in advance through intensive exploration of the geology and tectonics of the local subsurface.

References [1]

[2]

[3] [4]

R. Bracke, Petrothermale Nutzung und Stimulationsoptionen, in: M. Bauer, W. Freeden, H. Jacobi, N. Thomas (Eds.), Handbuch Tiefe Geothermie: Prospektion, Exploration, Realisierung, Nutzung, Springer, Berlin Heidelberg, 2014, pp. 245e273. H. Paschen, D. Oertel, R. Gru¨nwald, Mo¨glichkeiten der geothermischen Stromerzeugung in Deutschland. e Sachstandsbericht, Bu¨ro fu¨r Technikfolgen-Abscha¨tzung beim Deutschen Bundestag, vol. 84, Arbeitsbericht, Berlin, 2003, p. 129. C. Clauser, Radiogenic heat production of rocks, in: H.K. Gupta (Ed.), Encyclopedia of Solid Earth Geophysics. Encyclopedia of Earth Sciences Series, Springer, Dordrecht, 2011. Z. Sun, A. Wang, J. Liu, B. Hu, G. Chen, Radiogenic heat production of granites and potential for hot dry rock geothermal resource in Guangdong Province, Southern China, in: Proceedings World Geothermal Congress 2015, Melbourne Australia, 2015.

294 PART | VI Geothermal energy [5] G. Zimmermann, I. Moeck, G. Blo¨cher, Cyclic waterfrac stimulation to develop an enhanced geothermal system (EGS)dconceptual design and experimental results, Geothermics 39 (1) (2010) 59e69. [6] C. Baujard, A. Genter, V. Maurer, E. Dalmais, J.J. Graff, J. Schmittbuhl, The ECOGI EGS project in Rittershoffen, France, Trans. Geotherm. Resour. Counc. (2014) 267e270. [7] E. Huenges, Enhanced geothermal systems: review and status of research and development, in: R. DiPippo (Ed.), Geothermal Power Generation, Woodhead Publishing, 2016, pp. 743e761. Hrsg. [8] I. Moeck, Catalog of geothermal play types based on geologic controls, Renew. Sustain. Energy Rev. 38 (2014) 867e882. [9] S. Hirschberg, S. Wiemer, P. Burgherr, Energy from the Earth e deep geothermal as a resource for the future? in: Zentrum fu¨r Technologie-Abscha¨tzung, vdf Hochschulverlag AG, ETH Zu¨rich, 2015, p. 526. [10] C. Jain, C. Vogt, C. Clauser, Maximum potential for geothermal power in Germany based on engineered geothermal systems, Geotherm. Energy 3 (1) (2015) 1e20. [11] J.L. Renner, The Futeure of Geothermal Energy: Impact of Enhanced Geothermal Systems (EGS) on the United States in the 21st Century. United States, 2006. [12] M. Smith, The Furnace in the Basement, Part 1 e the Early Days of the Hot Dry Rock Geothermal Energy Program, 1970e1973, LA-120809, UC-1240, Los Alamos National Laboratory Report, USA, 1995. [13] D.W. Brown, D.V. Duchane, G. Heiken, V.T. Hriscu, Mining the Earth’s Heat: Hot Dry Rock Geothermal Energy, Springer-Verlag, Berlin Heidelberg, 2012, p. 658. [14] J.B. Clark, A hydraulic process for increasing the productivity of wells, J. Pet. Technol. (1949) 1e8. Petroleum Transactions AIME, T.P. 2510. [15] R.J. Sun, Theoretical size of hydraulically induced horizontal fractures and corresponding surface uplift in an idealized medium, J. Geophys. Res. 74 (1969) 25. [16] E. Barbier, Geothermal energy technology and current status: an overview, Renew. Sustain. Energy Rev. 6 (1e2) (2002) 3e65. ¨ berblick u¨ber Enhanced Geothermal Systems, GEOForum [17] K. Evans, B. Valley, Ein U ACTUEL, Band 4, 2005, pp. 17e24. [18] R. DiPippo, Enhanced Geothermal Systems-Projects and Plants: Chapter 22 in Book: Geothermal Power Plants: Principles, Applications, Case Studies and Environmental Impact, fourth ed., Elsevier Ltd, 2016. [19] V. Gischig, G. Preisig, Hydro-Fracturing versus hydro-shearing: a critical assessment of two distinct reservoir stimulation mechanisms, in: Proceedings to the 13th International Congress of Rock Mechanics, ISRM 2015, May 10e13 2015, Montre´al, Canada, 2015. [20] K. Evans, U. Wieland, S. Wiemer, D. Giardini, Deep Geothermal Energy R&D Roadmap for Switzerland, Swiss Competence Centers for Energy Research (SCCER SoE), Zurich, Switzerland, 2014, pp. 1e43. [21] J. Desroches, F. Cornet, channeling and stiffness effects on fluid percolation in jointed rocks, Rocks Joints (1990) 527e534. Barton & Stephanson (eds), Rotterdam. [22] K. Marakchi, V. Magnenet, J. Schmittbuhl, A. Genter, C. Fond, D. George, S. Ahzi, Flow channeling in EGS reservoir: from fracture aperture variability to large scale deformation, in: Proceedings of the European Geothermal Congress, Pisa, Italy, 3e7 June 2013, 2013. [23] F. Amman, V. Gischig, K. Evans, J. Doetsch, R. Jalali, B. Valley, H. Krietsch, N. Dutler, L. Villiger, B. Brixel, M. Klepikova, A. Kittila¨, C. Madonna, S. Wiemer, M.O. Saar, S. Loew, T. Driesner, H. Maurer, D. Giardini, The seismo-hydromechanical behavior during deep geothermal reservoir stimulation: open questions tackled in a decameter-scale in situ stimulation experiment, Solid Earth 9 (2018) 115e137.

Tapping hot rocks Chapter | 8 [24] [25]

[26]

[27]

[28]

[29]

[30] [31]

[32]

[33] [34]

[35] [36] [37]

[38] [39]

[40] [41]

295

M. Ha¨ring, U. Schanz, F. Ladner, B. Dyer, Characterization of the Basel 1 enhanced geothermal system, Geothermics 37 (2008) 469e495. acatech, Position “hydraulic fracturing e eine Technologie in der Diskussion.” Aus der Reihe: acatech Position, Deutsche Akademie der Technikwissenschaften, 2015, pp. 1e65 (Mu¨nchen). G. Zimmermann, G. Blo¨cher, A. Reinicke, W. Brandt, Rock specific hydraulic fracturing and matrix acidizing to enhance a geothermal systemdconcepts and field results, Tectonophysics 503 (1e2) (2011) 146e154. S. Portier, F.D. Vuataz, P. Nami, B. Sanjuan, A. Ge´rard, Chemical stimulation techniques for geothermal wells: experiments on the three-well EGS system at Soultz-sous-Foreˆts, France, Geothermics 38 (4) (2009) 349e359. J. Luo, Y. Zhu, Q. Guo, L. Tan, Y. Zhuang, M. Liu, C. Zhang, M. Zhu, W. Xiang, Chemical stimulation on the hydraulic properties of artificially fractured granite for enhanced geothermal system, Energy 142 (2018) 754e764. P. Nami, R. Schellschmidt, M. Schindler, T. Tischner, Chemical stimulation operations for reservoir development of the deep crystalline HDR/EGS system at Soultz-sous-Foreˆts (France), in: Proceedings, 32nd Workshop on Geothermal Reservoir Engineering, Stanford University, Stanford, California, USA, 2008, pp. 28e30. S. Portier, L. Andre´, F.D. Vuataz, Review on chemical stimulation techniques in oil industry and applications to geothermal systems. Engine, Work Package 4 (2007) 32. E. Schill, A. Genter, N. Cuenot, T. Kohl, Hydraulic performance history at the Soultz EGS reservoirs from stimulation and long-term circulation tests, Geothermics 70 (2017) 110e124. M. Schindler, J. Baumga¨rtner, T. Gandy, P. Hauffe, T. Hettkamp, H. Menzel, P. Penzkofer, D. Teza, T. Tischner, G. Wahl, Successful hydraulic stimulation techniques for electric power production in the Upper Rhine Graben, Central Europe, in: World Geothermal Congress, vol. 2529, 2010. S.-M. Lu, A global review of enhanced geothermal systems (EGS), Renew. Sustain. Energy Rev. 81 (2018) 2902e2921. J. Bradford, M. Ohren, W. Osborn, J. McLennan, J. Moore, R. Podgorney, Thermal stimulation and injectivity testing at Raft River, ID EGS site, in: Proceedings of the 39th Workshop on Geothermal Reservoir Engineering, Stanford, February 24e26, 2014, 2014. H.H. Einstein, W.S. Dershowitz, Tensile and shear fracturing in predominantly compressive stress fieldsda review, Eng. Geol. 29 (2) (1990) 149e172. F. Cornet, J. Helm, H. Poitrenaud, A. Etchecopar, Seismic and aseismic slips induced by large-scale fluid injections, Pure Appl. Geophys 150 (1997) (1997) 563e583. K. Breede, K. Dzebisashvili, X. Liu, G. Falcone, A systematic review of enhanced (or engineered) geothermal systems: past, present and future, Geotherm. Energy J. 1 (4) (2013) 1e27. K. Breede, G. Dzebisashvili Falcone, Overcoming challenges in the classification of deep geothermal potential, Geotherm. Energy Sci. (2015) 19e39. R. Jung, EGS e Goodbye or back to the future, in: R. Jeffrey (Ed.), Effective and Sustainable Hydraulic Fracturing, IntechOpen, 2013. https://www.intechopen.com/chapters/ 44719. (Accessed 29 September 2021). I. Matsunaga, H. Niitsuma, Y. Oikawa, Review of the HDR development at Hijiori site, Japan, in: Proceedings of the World Geothermal Congress 2005, Antalya, Turkey, 2005. H. Kaieda, H. Ito, K. Kiho, K. Suzuki, H. Suenaga, K. Shin, Review of the Ogachi HDR project in Japan, in: Proceedings of the World Geothermal Congress 2005, Antalya, Turkey, 2005.

296 PART | VI Geothermal energy [42] A. Genter, K. Evans, N. Cuenot, D. Frizsch, B. Sanjuan, Contribution of the exploration of deep crystalline fractured reservoir of Soultz to the knowledge of enhanced geothermal systems (EGS), Compt. Rendus Geosci. 342 (2010) 502e516. [43] J. Schmittbuhl, Monitoring of (enhanced) geothermal systems, in: Presentation at the GAB Autumn School, 8the9th October 2018, and Strasbourg, France, 2018. [44] R. Jung, Hydraulic fracturing and hydraulic testing in the granitic section of borehole GPK1, Soultz-Sous-Foreˆts, Geotherm. Sci. Technol. 3 (1991) 149e198. [45] A. Ge´rard, A. Genter, T. Kohl, P. Lutz, P. Rose, F. Rummel, The deep EGS (enhanced geothermal system) project at Soultz-sous-Foreˆts (Alsace, France), Geothermics 35 (2006) 473e483. [46] F. Ladner, O. Ha¨ring, Hydraulic characteristics of the Basel 1 enhanced geothermal system, GRC Transactions 33 (2009) 199e203. [47] S. Eyerer, S. Hofbauer, C. Wieland, C. Schifflechner, Potential der hydrothermalen Geothermie zur Stromerzeugung in Deutschland, Geothermie-Allianz Bayern, TechnischeUniversita¨t Mu¨nchen, 2017, pp. 1e38. [48] UBA, Kommunaler Klimaschutz durch Verbesserung der Effizienz in der Fernwa¨rmeversorgung mittels Nutzung von Niedertemperaturwa¨rmequellen am Beispiel tiefengeothermischer Ressourcen (Entwurf Endbericht) e Umweltforschungsplan des BMU, Umweltbundesamt, 2018. Feb 22, 2018. [49] G. Trullenque, A. Genter, B. Leiss, B. Wagner, R. Bouchet, E. Leoutre, Upscaling of EGS in different geological conditions: a European perspective, in: Proceedings, 43rd Workshop on Geothermal Reservoir Engineering, Stanford University, Stanford, California, 2018. February 12, 2018. [50] A. Heumann, E. Huenges, Technologiebericht 1.2 Tiefengeothermie innerhalb des Forschungsprojekts TF_Energiewende, 13.1_Wuppertal Report, Technologien fu¨r die Energiewende - Band 1, WI, ISI, IZES (Hrsg.) (2018) 85e134. [51] R. Jatho, T. Tischner, M. Wellbrink, S. Krug, Erschließung petrothermaler Geothermiereservoire e Teilprojekt 1 e Fracoperationen in dichten Gesteinsformationen und technische Bewertung des Multifrackonzepts. Abschlussbericht fu¨r BMWi, BGR, Hannover, 2015. [52] M. Ha¨ring, Geothermische Stromproduktion aus Enhanced Geothermal Systems (EGS) e Stand der Technik, Geothermal Explorers Ltd. Im Auftrag des Elektrizita¨tswerks der Stadt Zu¨rich (EWZ), 2007. [53] C. Bott, K. Menberg, F. Heberle, D. Bru¨ggemann, P. Bayer, Life cycle assessment of geothermal power generation in the Southern German Molasse Basin-The binary plant Kirchstockach, in: EGU General Assembly Conference Abstracts, 2021 pp. EGU21-9842. [54] F. Heberle, C. Schifflechner, D. Bru¨ggemann, Life cycle assessment of Organic Rankine Cycles for geothermal power generation considering low-GWP working fluids, Geothermics 64 (2016) 392e400. [55] K. Menberg, S. Pfister, P. Blum, P. Bayer, A matter of meters: state oft eh art in the life cycle assessment of enhanced geotehrmal systems, Energy Environ. Sci. 9 (2016) 2720e2743. [56] A. Pratiwi, G. Ravier, A. Genter, Life-cycle climate-change impact assessment of enhanced geothermal system plants in the Upper Rhine Valles, Geothermics 75 (2018) 26e39. [57] L. Kavanagh, J. Keohane, G. Cabellos, A. Lloyd, J. Cleary, Global lithium sourcesd industrial use and future in the electric vehicle industry: a review, Resources 7 (57) (2018) 1e29.

Tapping hot rocks Chapter | 8 [58]

[59]

[60] [61]

[62] [63]

[64] [65]

[66]

[67]

297

B. Ko¨hl, M. Elsner, T. Baumann, Hydrochemical and operational parameters driving carbonate scale kinetics at geothermal facilities in the Bavarian Molasse Basin, Geotherm. Energy 8 (1) (2020) 1e30. F. Nitschke, J. Scheiber, U. Kramar, T. Neumann, Formation of alternating layered Ba-Srsulfate and Pb- sulfide scaling in the geothermal plant of Soultz-sous-Foreˆts, Neues Jahrbuch Mineral. Abhand. (2014) 145e156. J. Mouchot, G. Ravier, O. Seibel, A. Pratiwi, Deep geothermal plants operation in Upper Rhine Graben: lessons learned, in: European Geothermal Congress, 2019. BfS, Ru¨cksta¨nde aus der tiefen Geothermie, Bundesamt fu¨r Strahlenschutz, 2020. https:// www.bfs.de/DE/themen/ion/umwelt/rueckstaende/tiefengeothermie/tiefengeothermie_node. html. (Accessed 29 September 2021). G. Foulger, M. Wilson, J. Gluyas, B. Julian, R. Davies, Global review of human-induced earthquakes, Earth Sci. Rev. 178 (2018) (2018) 438e514. T. Dahm, S. Cesca, S. Hainzl, T. Braun, F. Kru¨ger, Discrimination between induced, triggered, and natural earthquakes close to hydrocarbon reservoirs: a probabilistic approach based on the modeling of depletion-induced stress changes and seismological source parameters, J. Geophys. Res. Solid Earth 120 (4) (2015) 2491e2509. A. Zang, G. Zimmermann, H. Hofmann, O. Stephansson, K.-B. Min, K. Kim, How to reduce fluid- injection-induced-seismicity, Rock Mech. Rock Eng. 52 (2019) 475e493. G. Hillers, T.A.T. Vuorinen, M.R. Uski, J.T. Kortstro¨m, P.B. Ma¨ntyniemi, T. Tiira, P.E. Malin, T. Saarno, The 2018 geothermal reservoir stimulation in Espoo/Helsinki, Southern Finland: seismic network anatomy and data features, Seismol Res. Lett. 91 (2A) (2020) 770e786. T. Plenefisch, C. Bo¨nnemann, L. Bru¨ckner, L. Ceranna, N. Gestermann, G. Houben, T. Tischner, U. Wegler, M. Wellbring, Tiefe Geothermie e mo¨gliche Umweltauswirkungen infolge hydraulischer und chemischer Stimulationen, Umweltbundesamt, Texte 104/2015, 2015. H. Kaieda, Multiple reservoir creation and evaluation in the Ogachi and Hijiori HDR projects, Japan, in: Proceedings of the World Geothermal Congress 2015, Melbourne, Australia, 2015.

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Part VII

Hydropower

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Chapter 9

Retrofitting and Refurbishment of hydropower plants: case studies and novel technologies* Emanuele Quaranta1 and Julian Hunt2 1 European Commission Joint Research Centre, Ispra, Italy; 2International Institute for Applied Systems Analysis, Laxenburg, Austria

1. Introduction The powering of nonpowered dams (NPDs) and barriers, and the modernization of the aged hydropower plants (HPPs), are emerging practices of hydropower development, due to the minimal impacts on ecosystems and the fact that most of the infrastructure is already in place [42,45]. Novel technologies are under development in this context to fit the different hydraulic and topographic contexts [51,77,102]. For example, in the United States (USA) there are 2500 dams that provide 78 GW of conventional hydropower and 22 GW of pumped-storage hydropower, but the USA has more than 80,000 NPDs, providing a variety of services ranging from water supply to inland navigation. Powering of these dams can add 12 GW of installed power, and 8 GW of this potential is associated with the largest 100 dams [37]. According to the European Environment Agency, there are currently approximately 7000 large dams in Europe, and thousands of additional smaller NPDs, for example, historic weirs and mill sites, that in Europe are estimated to be around 60,000 [75]. In South Africa, the potential of NPDs is estimated at 250 MW [72]. However, a feasibility study was conducted in the Piedmont region of North Carolina (cataloging over 1000 non-Federal dams with hydraulic heads ranging from 4.6 m to 10.7 m, and power capacity 200

2.0%

2.6%

1.0%

1.3%

0.5%

0.7%

308 PART | VII Hydropower

TABLE 9.2 Efficiency upgrading after refurbishing runner seal components [44]. Runner seal component

Modifications and/or replacement

Crown

0.2%e2.0%

Band

0.2%e2.0%

TABLE 9.3 Efficiency upgrading after refurbishing water passage components [44]. Water passage component

Surface finish improvements

Modifications or replacement

Spiral case

0.3%

0.3%

Stay ring

0.2%

0.3%e2.0%

Guide vanes

0.2%e2.0%

0.3%e0.5%

Draft tube

0.3%

0.3%e1.0%

of the same order of magnitude [27]. Eberle et al. [28] estimated an increase of 1% in the efficiency of a Francis turbine as a result of upgrading the draft tube. Liu et al. [56] estimated an increase of 0.5% in the efficiency of a Francis turbine as a result of minor modifications in the stay and guide vanes. MESA Associates Inc. and Oak Ridge National Laboratory [61] mentioned an increase of 0.1%e0.8% in the efficiency of Francis and Kaplan-Bulb turbines as a result of the application of a proper coating. In Ref. [36] it was estimated that hydropower upgrading can lead to the following technology gain if an HPP of the 1970s is upgraded: þ0.5% turbine efficiency, þ6.0% turbine capacity, þ0.6% generator efficiency, þ7.5% generator capacity, and þ3% in turbine efficiency from degradation recovery. Therefore, the increase in the electromechanical efficiency can be estimated as 0.5% þ 0.6% þ 3% ¼ 4.1%. Draft tube and gates can gain 2%. These data are in line with a Swiss study [8]. Eberle et al. [28] reported an increase of 6% in the efficiency of a Francis turbine after the replacement of the runner and guide vanes. Papillon and Freeman [70] reported an increase of 7% in the efficiency of a Francis turbine after the replacement of the runner, stay vanes, and guide vanes. Benigni et al. [5] reported an increase of 7% in the efficiency of a Francis turbine after the replacement of the runner and guide vanes. March and Fisher [59] reported an increase of 3.7% in the efficiency of a Francis turbine (weighted over the entire operating range) after the replacement of the turbine runner with a new

Retrofitting and Refurbishment of hydropower plants Chapter | 9

309

selfaerated runner. It should be noted that the design of the new runner was constrained by the need to increase the concentration of dissolved oxygen in the plant releases. In the case reported by Ref. [59] an increase of 3.7% in the turbine efficiency resulted in an increase in the turbine capacity of 10%. Three more successful cases where the original turbine runner has been replaced with a self-aerated one are reported by Ref. [58]. After replacing the Francis runner at the Krasnoyarsk HPP (Russia), the turbine efficiency increased from 94% to 96.7%.3 As part of the modernization program of the Bratsk HPP (Russia), 12 runners were replaced after 50 and more operating years. The new runners have a more optimal profile and high efficiency due to modern technologies. The costs of replacing runners were offset by increased power generation. In the first half of 2019 alone, additional total generation with the same volume of water amounted to 0.595 TWh, or an increase of 5.3%.4 In another project, the projected increase in energy production through the modernization of the main generating equipment at four large HPPs (total installed power of 15 GW) was estimated at 2.4%.5 In [88] the Francis turbine efficiency was increased by 5%, in Ref. [91] by 25%, in Ref. [84] by 5%. In Ref. [93]; the power capacity of a Kaplan-Bulb turbine under 18 m head was increased from 24.3 to 29 MW, and in Ref. [96] the power of a Pelton turbine (62.5 MW commissioned in 1986) was increased by 9%, while the efficiency increased by 1.4%. In Ref. [73] it was shown as the Pelton unit efficiency can be increased by 3% due to casing optimization (see also Ref. [80]). Benigni et al. [5] refurbished a Kaplan-Bulb turbine increasing efficiency by 2%. Values for the increase in efficiency from 4% to 7% have been reported for several refurbishment projects of the hydraulic turbines and the components of the hydraulic passage [11,68,74]. It must be noted that ecologically improved turbines are under development, for example, the Alden and Minimum Gap Runner turbines, that can be installed instead of Francis and Kaplan-Bulb turbines up to 40 m head (research is under development for higher heads). These turbines reduce fish mortality, while providing a slightly lower efficiency than nonecologically improved turbines [79].

7. Efficiency improvement at part load Hydropower industry is facing an increasing demand of turbines working efficiently over a wider range of operating conditions (from part-load to full load), because the operating hours at part load in some HPPs are overcoming those at BEP, or they are very close. For this reason, it is increasingly 3. https://kges.ru/press_tsentr/novosti/na_krasnoyarskoy__ges_ustanovleno_novoe_rabochee_ koleso_gidroagregata_5. 4. https://www.ogirk.ru/2019/8/7/bratskaja-gjes-eshhe-bolshe-chistoj-jenergii/. 5. https://www.vedomosti.ru/business/articles/2016/02/19/630675-evrosibenergo-modernizatsiyu.

310 PART | VII Hydropower

becoming a design goal turbines that yield an overall enhancement of efficiency (weighted efficiency [66]), over the full operating range than an increased efficiency at full load and at BEP. In order to improve the weighted efficiency, different technologies exist, for example, active and passive flow control in the draft tube, new gate and turbine design, variable speed, new governors and control techniques. For example, the average efficiency gain was 3% for the 400 MW Okawachi pumped-storage plant [95]. Cateni et al. [21] reported an increase of 7% in the part load efficiency of a Francis turbine. Enomoto et al. [29] reported an efficiency gain over the entire operating range of a Francis turbine with a new wicket gate profile of 0.6%. The reshaped geometry of the stay vanes analyzed in Ref. [11] increased the weighted efficiency by 5.7% while the overall turbine weighted efficiency improvement was close to 7% when including the new wicket gates and the modified stay vanes. Vortex rope control and flow field optimization in the draft tube, e.g., with air and water injections, or Jgroves, can also improve the efficiency at part load [51,65]. New runner types like the X-blade Francis turbine and the Deriaz turbine (a Francis-type turbine with adjustable blades) have been introduced for part load optimization [14,64]. Another way to increase the performance of Francis turbines is the use of splitter blades, which are shorter blades added alternatively to the main blades. Therefore, there are fewer blades on the runner-outlet side, so the blades can be lengthened toward the downstream side (i.e., the internaldiameter side). One example of this design is the Francis turbine at the Ontake Power Station. The measured efficiency characteristic of the splitter blade-fitted runner, compared with the measured efficiency of the existing runner, showed an improvement of 7% at maximum efficiency, and 11% at part load (40% of the design flow rate, [39]). An increased efficiency exceeding 95% due to the use of splitter blades is presented in Ref. [14] for heads of about 350 m. The use of splitter-blade and X-blade runners results in reduced pressure pulsations, cavitation intensity, stresses in the turbine components and very stable over the whole range of operation with a smooth part-load operation. This increases total hours of generation by eliminating unplanned shutdown problems caused by fatigue cracks. Variable speed is a current key technology for extending the operating range of a hydroelectric unit and for adapting the HPP operation to different conditions easier, especially at part load. The cost of upgrading a hydropower to allow variable speed operation is very case dependent. In the eStorage project, a cost of 150 kV/MW was estimated for the upgrade of a conventional pumpedstorage power plant to allow variable operation [4]. The variable speed improves turbine efficiency, particularly when pumping, and enhances the fishfriendly characteristics of the turbine operation at part load, since the rotational speed is reduced instead of closing the blade opening [79]. Some key examples are the Buenameso´n RoR HPP, where the two variable speed units were successfully commissioned in 2013. In the Compuerto reservoir HPP (which was

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commissioned in 1967 with an operating head between 63 and 102 m), a variable speed unit was successfully commissioned in 1994 and given priority when for whatever reason one of the units has to operate at partial load. See Refs. [43] and [12] for a complete review on variable speed technology. Advanced governing systems for transient operations are also being developed to improve performance and reduce damages during transient operation [78], as well as transient modeling [54].

8. Digitalization and flow forecast Digitalization consists in collecting (by proper instrumentation [89,98]) and processing data, and adjusting the working conditions of hydropower components. Digitalization leads to several benefits: advanced grid balancing services without compromising reliability and safety, improvement of predictive maintenance, prolongation of the lifetime, reduction of the outage time, addressing cyber-security risks, increase of the overall efficiency and annual generation. In Ref. [6], cost savings over 8 months due to the prevention of unplanned shutdowns were estimated in the range of 25 kV to 100 kV for a 1000 MW HPP in Italy equipped with Francis-type pump-turbines. It is estimated that a total 42 TWh could be added to present hydropower energy production by implementing hydropower digitalization. Such an increase could lead to annual operational savings of 5 $ billion and a significant reduction of greenhouse gas emissions [51]. Quaranta et al. [78] calculated an additional annual energy generation of 0.5% in one case, and 1.2% in a second case, in two Italian HPPs by implementing digitalization. The cases reported by Hydrogrid showed an efficiency increase by 0.4% and 1% [57], and þ11% of annual energy generation due to the better inflow forecast. XFLEX HYDRO [97] showed that by using machine learning methods on operational time statistics feeding an optimization algorithm, 2% in energy production can be gained by a Kaplan-Bulb turbine. Furthermore, digitalization enables to drastically reduce the response time of hydro units [97]. Digitalization also allows to assess the economic impact of offering additional reserve flexibility, and to prevent failures and damages with the implementation of HPP digital twins. The cost of a predictive system for one unit (development and implementation at HPP) was found to be about 200,000 V [35]. An additional increase and optimization could be achieved with the use of software that uses genetic algorithms, for example EASY [47,48]. Digitalization and flow forecast can also improve fishway management, by evaluating and quantifying the effect of hydrological variability on fishways to identify and solve operational problems and to optimize their performance. To improve further the flexibility of HPPs by digitalization, novel surfacecluster approach toward transient modeling of hydraulic-turbine governing systems in the start-up process can be implemented. The transient process, an essential condition for the operation of the hydraulic turbine governing system,

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is critical for the safety and stability of a HPP. Furthermore, mid- and shortterm forecast of the flow are also of high importance for a better water management and production optimization [24,71,77].

9. Integration with other energy sources In order to improve flexibility, HPPs can also be integrated and coordinated with other energy technologies. The hybridization of a HPP with a battery energy storage system (BESS) can improve the promptness of the HPP for frequency support, thanks to the storage battery system and can provide a faster frequency regulation of the power system. In this way, the life span of the electromechanical equipment is increased and the outage time is reduced. The cost of a BESS depends on the type of battery. The cost of a Li-ion battery ranges around 500 USD/kWh and is expected to decrease by around 50% by 2030. ENGIE integrated a 12.5MW/13-MWh Li-ion BESS in the Pfreimd hydropower system in 2018. The BESS is operated in combination with pumped-storage units to provide ancillary services. Fortum integrated a 2-MW/1.5-MWh Li-ion BESS in the Ja¨rvenpa¨a¨ HPP. The BESS provides frequency controlled normal operation reserves, also known as frequency containment reserves for normal operation (FCR-N), in the reserve market operated by Fingrid. Fortum uses its hydropower generation assets as backup reserve when the BESS cannot provide FCR-N as required by Fingrid because of having reached the maximum or minimum state-of-charge [18,19]. Major debates are also arising on the use of batteries instead of Pumped Storage Hydropower (PSH). Batteries do not have to be expansive centralised installations with capacities in the order of magnitude of several GWh. The required capacity can be broken down into smaller units and distributed across a number of sites. Hence, they are not impacting on the local landscape to the same degree. However, batteries have particular requirements with regard to the materials that they are made from, how they can be operated, and how they are decommissioned at their end of life. Batteries are particularly well suited to fast-response short-term balancing requirements, while PSH hold large volumes and can provide long-term storage, with a lifespan of up to 150 years, with respect to 20 years of batteries. Therefore, batteries should be seen as a complementary technology rather than as substitutes. LCA analyses show lower impacts of PHS than batteries, except for natural land transformation [100]. HPPs can also be integrated with floating photovoltaic (FPV) and PV on dam surfaces. The benefits gained by a hybrid FPV-hydro plant can be summarized as follows. 1. Grid connection. Artificial hydropower reservoirs are equipped with power generators and are grid-connected, thus the related costs of FPV are lower than those of a land installation.

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2. Reduction of power fluctuation. In temperate nonalpine regions, the FPV panels give the maximum energy yield during the hot season when the HPPs may register a reduction of power. 3. No land occupancy. The main advantage of FPV plants is that they do not conflict with other land uses. 4. Water saving. The partial coverage of basins has additional benefits such as the reduction of water evaporation. The water saving due to reduction of evaporation rate ranges between 15,000 and 20,000 m3 for hectare of FPV, that is 7000e10,000 m3 for MWp installed [90]. 5. Floating panels can increase the capacity factor6 of a HPP by 50%e100%. 6. Floating panels can gain 7%e14% of additional energy due to the reduction of the underneath temperature, with respect to a land installation. In Ref. [10], different floating PV types are described, with their working behavior. In Ref. [53], the global FPV potential has been estimated, while in Ref. [77] the increased hydropower potential due to evaporation reduction has been estimated. PV can also be installed on dam surfaces (gravity and arch dams) resulting in high efficiency due to excellent sun exposition in snow-covered mountains all over the year, since there is no fog in winter most of the time [49]. Further details can be found in Ref. [50]. In the case of PV on dams, the benefits are the following: 1. PV panels protect the dam surface from direct solar radiation that may negatively affect the stability of the dam itself, reducing thermal excursion of the dam surface and increasing dam durability 2. PV panels are installed on an existing structure (the dam surface), reducing land use 3. Energy generated by PV can be used for pumping in pumped-storage HPPs 4. PV panels are mounted on an inclined area, minimizing the distance required between two panels with respect to an analogous installation on a flat area, thus increasing solar energy generation. HPPs with large reservoirs are ideal solution to be combined with wind power generation, as the hydropower generation can be increased when there is low wind power, or reduced when there is excess wind power [20]. Even though pumped storage plants can store excess wind power generation, it only makes sense if its reservoirs have weekly, monthly, or seasonal cycles [41].

10. Environmental and practical considerations Many rehabilitation projects inherit the environmental and social issues neglected by the original projects implemented 30 or 50 years before [36], 6. Capacity Factor: ratio of annual energy generation to the product of installed power by 8760 h

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e.g., reservoir sedimentation, environmental impacts and resettlements. On average, 0.73% of the European HPP reservoir volume is annually lost due to sedimentation, 0.22% in US, 1.2% in Turkey, 2.3% in China [86]. Apart from the various negative effects of sedimentation, one major consequence is a continuous diminishing of storage volume, having negative effects on hydropower production [69]. An example is the Ceppo Morelli (Italy) storage hydropower facility which currently operates as a RoR, losing its main asset of supplying peak energy when demand is high [25]. Nonetheless, to keep hydropower economical, environmentally friendly and socially acceptable over the long term, sustainable solutions to cope with sediments are required. There is a great need for reconciling efforts between the diverging interests of hydropower production and ecology, to adhere by the European Union member states in line with the EU Water Framework Directive [15] and the associated mandatory national River Basin Management Plans [16]. Technical measures to counter reservoir sedimentation are available today, but these still need to be further developed and improved to achieve sediment continuity at hydropower reservoirs and weirs. Promising concepts are sediment bypassing through tunnels or channels, and fine sediment venting through low-level outlets and power waterways, respectively [9,30,38,46]. Further practices aimed at improving environmental sustainability are the development of innovative solutions for safe two-way fish passage, the release of targeted environmental flows and the use of turbines with reduced impacts on fish. Recent research showed very promising results in new designs of trash racks and guidance structures, to provide fish from passing through turbines [32,92]. The project implementation in reasonable timeframes is also a main challenge. For instance, a major upgrading window opens up typically between the 30th and 50th year of operation, depending on the structural part to be upgrated. The high income losses from stopping the station may even exceed upgrading costs associated with equipment and labor. Therefore, actions that decrease the required time between project conceptualization to its implementation are important (Pers. Comm. of Vattenfall). For example, in Ref. [36] a 10 MW unit forced out of operation for a year resulted in a loss of revenue of US$4.3 million based on an energy value of US$100/MWh. For comparison, the cost of a life extension involving a runner replacement and a generator rewind is close to US$6 million. The modernization of HPPs requiring also intervention on the civil infrastructures may need a concession renewal. New environmental requirements, such as environmental flow release, will have to be implemented at the concession renewal, reducing generation in most of HPPs, that will happen by 2050 for most of the existing HPPs in Europe. In Switzerland, a production loss of at least 2.28 TWh (some 6% of 2018 generation) by 2050, after the renewal of all the concessions, has been predicted [101]. In Norway, the loss in power production due to revision of around 400 licenses that are due

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by 2022 is estimated between 2 to 4 TWh (1.4%e2.8% of annual production). However, the expected increase in inflow due to climate changes (higher water availability) is estimated to be higher, since the license was given 30 years ago.

11. Conclusions The powering of NPDs and the modernization of the aged HPPs are relevant strategies at the global scale, due to the minimal impacts on ecosystems and the fact that most of the infrastructure is already in place. Novel technologies are under development to be implemented during modernization interventions, and the case studies here presented show how much more energy and efficiency can be achieved, with the related challenges. The replacement of aged equipment is needed not only to reestablish the original design conditions, but also to increase flexibility, safety, and efficiency. The optimization of the weighted efficiency of the electro-mechanical equipment is of higher relevance than to achieve an increased efficiency at BEP, to ensure flexibility. Novel turbines are also under development, including turbines with improved environmental and ecological behaviour. The integration with other energy sources (photovoltaic, wind, batteries) can support the deployment and the optimal operation of each energy source, improving the overall performance of the combined/hybrid plant. The dam heightening is useful especially to increase the water storage capacity while digitalization and better inflow forecast can improve efficiency and annual generation, reducing spills. For example, in Ref. [77] it has been estimated that applying the dam heightening, novel electro-mechanical equipment, reduction of losses in waterways and digitalization, the annual energy generation in Europe could be enhanced by almost 10%. During modernization interventions, attention should be paid to environmental issues: de-sedimentation techniques and fish friendly solutions should be implemented, in order to increase the overall sustainability of the project.

Acknowledgment The Author E.Q. wants to mention here some of the experts involved as coauthors in the paper [77], who provided some case studies and input included here: George Aggidis, Robert M. Boes, Evgeniia Georgievskaia, Sebastian Muntean, Juan Pe´rez-Dı´az, Marco Rosa-Clot, Anton J. Schleiss, Elena Vagnoni.

References [1] T.B. Adams, Feasibility of Upgrading Existing Hydropower Infrastructure for Use in Renewable Energy Storage, Doctoral dissertation, Massachusetts Institute of Technology, 2018. [2] B. Allet, A. Schleiss, Hydropower in Switzerland. Future development, possibilities and limits (in German: Wasserkraft in der Schweiz e Ausbau, Mo¨glichkeiten und Schranken), Schweizer Ingenieur und Architekt 108 (29) (1990) 804e810.

316 PART | VII Hydropower [3] J.M. Andrewartha, J.E. Sargison, K.J. Perkins, The influence of freshwater biofilms on drag in hydroelectric power schemes, WSEAS Trans. Fluid Mech. 3 (3) (2008) 201e206. [4] M. Aunedi, D. Pudjianto, F. Teng, G. Strbac, Potential Economic and Environmental Value of Large-Scale Energy Storage in Europe, 2021. Available (on 29th March 2021): http:// www.estorage-project.eu/document-library. [5] H. Benigni, J. Schiffer, H. Jaberg, Refurbishment of twin Francis turbinesemaximizing the annual production, IoP Conf. Ser. Earth Environ. Sci. 240 (2) (2019) 022036, https:// doi.org/10.1088/1755-1315/240/2/022036. [6] A. Betti, E. Crisostomi, G. Paolinelli, A. Piazzi, F. Ruffini, M. Tucci, Condition Monitoring and Early Diagnostics Methodologies for Hydropower Plants, 2019 arXiv preprint arXiv:1911.06242. [7] S. Bieri, P. Strauss, P. Krebs, P. Ender, M. Peter, J.-P. Gisiger, H. Lozza, E. Ba¨umler, Ausbau und Erneuerung des Kraftwerk Augst, Wasser Energ. Luft 86 (3/4) (1994) 59e102. [8] R.M. Boes, Potenziale und Grenzen der Wasserkraft - was bringen Anlagenoptimierungen? (‘Potential and limits of hydropower - what can be gained from optimization of schemes?’), Natur und Mensch, Sonderheft Quo Vadis Wasserkraft? 53 (4) (2011) 24e28 ([in German]). [9] R.M. Boes, M. Mu¨ller-Hagmann, I. Albayrak, Design, operation and morphological effects of bypass tunnels as a sediment routing technique, in: Proc. 3rd Int. Workshop on Sediment Bypass Tunnels, National Taiwan University, Taipei, Taiwan, 2019, pp. 40e50. [10] F. Bontempo Scavo, G.M. Tina, A. Gagliano, S. Nizetic, An assessment study of evaporation rate models on a water basin with floating photovoltaic plants, Int. J. Energy Res. 45 (1) (2021) 167e188. [11] L. Bornard, F. Debeissat, Y. Labrecque, M. Sabourin, L. Tomas, Turbine hydraulic assessment and optimization in rehabilitation projects, IOP Conf. Ser. Earth Environ. Sci. 22 (2014) 012033, https://doi.org/10.1088/1755-1315/22/1/012033. ˆ . Rezek, L. Pinto, J. Bernardes, The [12] E. Bortoni, Z.D. Souza, A. Viana, H. Villa-Nova, A benefits of variable speed operation in hydropower plants driven by Francis turbines, Energies 12 (19) (2019) 3719, https://doi.org/10.3390/en12193719. [13] H. Brekke, Hydraulic TurbinesDesign, Erection and Operation, Norwegian University of Science and Technology (NTNU), Trondheim, Norway, 2001. [14] H. Brekke, Performance and safety of hydraulic turbines, IOP Conf. Ser. Earth Environ. Sci. 12 (2010) 012061, https://doi.org/10.1088/1755-1315/12/1/012061. [15] J. Brils, Sediment monitoring under the EU water Framework directive, J. Soils Sediments 4 (2004) 72e73, https://doi.org/10.1007/bf02991047. [16] J. Brils, Including sediment in European River Basin management Plans: twenty years of work by SedNet, J. Soils Sediments 20 (2020) 4229e4237, https://doi.org/10.1007/s11368020-02782-1. [17] B.T. Brunes, Increasing Power Output from Francis Turbines, Master Thesis, Norwegian University of Science and Technology, Trondheim, Norway, 2009. [18] R. Bucher, A. Schreider, On the pooling of hydro assets and grid-scale battery energy storage systems, Int. J. Hydropower Dams 5 (2017) 60e64. [19] R. Bucher, A. Schreider, S. Lehmann, Live test results of the joint operation of a 12.5 MW battery and a pumped-hydro plant, in: Proc. 2018 HYDRO Conference, October 15e17, 2018, Gdansk, Poland, 2018. [20] F.A. Canales, A. Beluco, C.A.B. Mendes, A comparative study of a wind hydro hybrid system with water storage capacity: conventional reservoir or pumped storage plant? J. Energy Storage 4 (2015) 96e105, https://doi.org/10.1016/j.est.2015.09.007.

Retrofitting and Refurbishment of hydropower plants Chapter | 9

317

[21] A. Cateni, L. Magri, G. Grego, Optimization of Hydropower Plants Performancee Importance of rehabilitation and maintenance in particular for the runner profiles, in: Proc. 7th International Conference on Hydraulic Efficiency Measurements, 3rde6th September 2008, Milan, Italy, 2008, pp. 1e12. [22] B. Clerc, P. Manso, G. De Cesare, Heightening of very high gravity dams: the case study of the Grande Dixence, in: G. Bolzon, D. Sterpi, G. Mazza`, A. Frigerio (Eds.), Numerical Analysis of Dams. ICOLD-BW 2019. Lecture Notes in Civil Engineering vol. 91, Springer, Cham, 2021, https://doi.org/10.1007/978-3-030-51085-5_43. [23] D. Cohen, Ukraine-hydropower Rehabilitation and System Control Project, The World Bank, 2002. Report No: 24947. [24] K. Cros, A.J. Schleiss, G. Artique, F. Jordan, Hydrological forecasting on glacier systems: temperature forecasting corrections, in: Proc. HYDRO 2016 Conference, Achievements, Opportunities and Challenges, 10e12 October 2016, Montreux, Switzerland, 2016. [25] C. De Michele, G. Salvadori, M. Canossi, A. Petaccia, R. Rosso, Bivariate statistical approach to check adequacy of dam spillway, J. Hydrol. Eng. 10 (1) (2005) 50e57, https:// doi.org/10.1061/(ASCE)1084-0699(2005)10:1(50). [26] E. de Podesta´ Gomes, S. Vajayfor, Brazilian hydroelectric rehabilitation potential and viability, Am. J. Hydropower Water Environ. Syst. 1 (2014) 17e24, https://doi.org/ 10.14268/ajhwes.2014.00014. [27] C. Descheˆnes, R. Fraser, J.P. Fau, New trends in turbine modelling and new ways of partnership, in: Proc. 4th International Conference on Hydraulic Efficiency Measurement, IGHEM, Toronto, Ontario, Canada, 2002, pp. 1e12. [28] P. Eberle, M. Couston, M. Sabourin, The refurbishment of low head Francis turbines, Int. J. Hydropower Dams 10 (1) (2003) 45e48. [29] Y. Enomoto, S. Kurosawa, H. Kawajiri, Design optimization of a high specific speed Francis turbine runner, IOP Conf. Ser. Earth Environ. Sci. 15 (3) (2012) 032010, https:// doi.org/10.1088/1755-1315/15/3/032010. [30] D. Felix, I. Albayrak, R.M. Boes, A. Abgottspon, Sediment transport through the power waterway and hydro-abrasive erosion on turbines, in: Proc. Hydro 2017 Conference, Sevilla, Spain, 2017. Paper 27.07. [31] D. Felix, M. Mu¨ller-Hagmann, R. Boes, Ausbaupotential der bestehenden Speicherseen in der Schweiz (‘Extension options of existing reservoir lakes in Switzerland’), Wasser Energ. Luft 112 (1) (2020) 1e10 ([in German]). [32] H.P. Fjeldstad, U. Pulg, T. Forseth, Safe two-way migration for salmonids and eel past hydropower structures in Europe: a review and recommendations for best-practice solutions, Mar. Freshw. Res. 69 (12) (2018). [33] Z. Fu, Y. He, S. Su, Key problems and solutions in arch dam heightening, Front. Architect. Civ. Eng. China 5 (1) (2011) 98e104, https://doi.org/10.1007/s11709-010-0004-7. [34] A. Fust, R. Ruoss, H. Vo¨gtli, J. Vontobel, Ausbau und Erneuerung des Rheinkraftwerkes Laufenburg, Wasser Energ. Luft 83 (1/2) (1991) 1e14. [35] E. Georgievskaia, Limitations of modern diagnostic and prognostic systems for a hydraulic unit’s health, Eng. Times 2 (1) (2021) 27e42, https://doi.org/10.3390/eng2010003. [36] J. Goldberg, O. Espeseth Lier, Rehabilitation of Hydropower: An Introduction to Economic and Technical Issues. Water Papers, World Bank, Washington, DC, 2011. https:// openknowledge.worldbank.org/handle/10986/17251.

318 PART | VII Hydropower [37] B. Hadjerioua, Y. Wei, S.C. Kao, An Assessment of Energy Potential at Non-powered Dams in the United States, Oak Ridge National Laboratory, Oak Ridge, 2013. Tennessee 37831 Managed by UT-BATTELLE, LLC for the U.S. DEPARTMENT OF ENERGY under contract DE-AC05-00OR22725. [38] W.H. Hager, A.J. Schleiss, R.M. Boes, M. Pfister, Hydraulic Engineering of Dams, Taylor & Francis, London, UK, 2020, https://doi.org/10.1201/9780203771433. [39] M. Harano, K. Tani, S. Nomoto, Practical application of high-performance Francis-turbine runner fitted with splitter blades at Ontake and Shinkurobegawa no. 3 power stations of the Kansai electric power CO., Inc, Hitachi Rev. 55 (3) (2006) 109e113. [40] G. Haury, P. Kesselring, K. Schrenk, T. Reumschu¨ssel, W. Biegen, E. Bro¨gelmann, Rhneinkraftwerk Wyhlen e Ausbau und Erneuerung, Wasser Energ. Luft 85 (11/12) (1993) 337e358. [41] J. Hunt, E. Byers, K. Riahi, S. Langan, Comparison between seasonal pumped-storage and conventional reservoir dams from the water, energy and land nexus perspective, Energy Convers. Manag. 166 (2018) 385e401. [42] H.H. Hwee, H.C. Poon, S.F. Lu, P.W. Fook, Converting dam: from water supply to hydropower generation, J. Eng. Technol. Adv. 2 (1) (2021) 37e56. [43] I. Iliev, C. Trivedi, O.G. Dahlhaug, Variable-speed operation of Francis turbines: a review of the perspectives and challenges, Renew. Sustain. Energy Rev. 103 (2019) 109e121, https://doi.org/10.1016/j.rser.2018.12.033. [44] International Energy Agency (IEA), Guidelines on Methodology for Hydroelectric Francis Turbine Upgrading by Runner Replacement, vol. 1, 2000 (Report). [45] International Energy Agency (IEA), Hydropower Special Market Report Analysis and Forecast to 2030, 2021. [46] J.M.I. Jenzer Althaus, G. De Cesare, A.J. Schleiss, Sediment evacuation from reservoirs through intakes by jet-induced flow, J. Hydraulic Eng. 141 (2) (2015) 04014078, https:// doi.org/10.1061/(ASCE)HY.1943-7900.0000970. [47] E. Kontoleontos, S. Weissenberger, Annual energy production (AEP) optimization for tidal power plants based on Evolutionary Algorithms-Swansea Bay Tidal Power Plant AEP optimization, IOP Conf. Ser. Earth Environ. Sci. 49 (10) (2016) 102009, https://doi.org/ 10.1088/1755-1315/49/10/102009. [48] E. Kontoleontos, S. Weissenberger, Annual energy production maximization for tidal power plants with evolutionary algorithms, Int. J. Fluid Mach. Syst. 10 (3) (2017) 264e273, https://doi.org/10.5293/IJFMS.2017.10.3.264. [49] A. Kahl, J. Dujardin, M. Lehning, The bright side of PV production in snow-covered mountains, Proc. Natl. Acad. Sci. U. S. A. 116 (4) (2019) 1162e1167, https://doi.org/ 10.1073/pnas.1720808116. [50] I. Kougias, K. Bo´dis, A. Ja¨ger-Waldau, F. Monforti-Ferrario, S. Szabo´, Exploiting existing dams for solar PV system installations, Prog. Photovolt. Res. Appl. 24 (2) (2016) 229e239, https://doi.org/10.1002/pip.2640. [51] I. Kougias, G. Aggidis, F. Avellan, S. Deniz, U. Lundin, A. Moro, P. Schild, Analysis of emerging technologies in the hydropower sector, Renew. Sustain. Energy Rev. 113 (2019) 109257, https://doi.org/10.1016/j.rser.2019.109257. [52] P. Lazaro, G. De Cesare, A. Madau, S. Bussalai, Heightening of the Maccheronis dam in Sardinia (Italy). Commission Internationale des grands barrages Vingt-Deuxie`me congre`s des grands barrages. June 2006, Barcelone, Spain, 2006.

Retrofitting and Refurbishment of hydropower plants Chapter | 9

319

[53] N. Lee, U. Grunwald, E. Rosenlieb, H. Mirletz, A. Aznar, R. Spencer, S. Cox, Hybrid floating solar photovoltaics-hydropower systems: benefits and global assessment of technical potential, Renew. Energy 162 (2020) 1415e1427, https://doi.org/10.1016/ j.renene.2020.08.080. [54] H. Li, B. Xu, E. Arzaghi, R. Abbassi, D. Chen, G.A. Aggidis, J. Zhang, E. Patelli, Transient safety assessment and risk mitigation of a hydroelectric generation system, Energy 196 (2020) 117135, https://doi.org/10.1016/j.energy.2020.117135. ˚ . Killingtveit, Increased generation from upgrading and extension [55] L. Lia, M.N. Aas, A projects, Int. J. Hydropower Dams 24 (4) (2017) 75e78. [56] X. Liu, Y. Luo, B.W. Karney, W. Wang, A selected literature review of efficiency improvements in hydraulic turbines, Renew. Sustain. Energy Rev. 51 (2015) 18e28, https:// doi.org/10.1016/j.rser.2015.06.023. [57] K. Madisetti, Digital transformation in the hydro sector, in: British Hydropower Association (BHA) Annual Conference 2019, 13e14 November 2019, Glasgow, Scotland, 2019. [58] P. March, Hydraulic and environmental performance of aerating turbine technologies, in: EPRI Conference on Environmentally Enhanced Hydropower Turbines, 2011, pp. 1e32. [59] P.A. March, R.K. Fisher, It’s not easy being green: environmental technologies enhance conventional hydropower’s role in sustainable development, Annu. Rev. Energy Environ. 24 (1) (1999) 173e188, https://doi.org/10.1146/annurev.energy.24.1.173. [60] A. Mellal, Heightening of an existing gravity dam-static and dynamic analyses, in: Numerics in Geotechnics and Structures, ZSoil Day, 28 August 2009, Lausanne, Switzerland, 2009. [61] MESA Associates Inc. and Oak Ridge National Laboratory, Hydropower Advanced Project e Best Practice Catalog e Francis Turbine, U.S. Department of Energy, 2012. Project No. DE-AC05-00OR22725. [62] V.E. Mikhailov, I.P. Ivanchenko, A.N. Prokopenko, Modern state of hydropower and construction of hydro turbines in Russia and abroad, Therm. Eng. 68 (2) (2021) 83e93. ¨ berle[63] P. Molinari, Alternative Wege zur Erho¨hung der Produktion aus Wasserkraft - U gungen zu Potenzial und Kosten einer Vergro¨sserung von Druckstollen am Beispiel von Ova Spin e Pradella (Alternative options to increase hydropower generationeevaluation of potential and cost of new pressure tunnel Ova Spin Pradella), Bulletin VSE/AES 12 (2011) 8e12 (in German). [64] A. Morabito, G.D.O. Silva, P. Hendrick, Deriaz pump-turbine for pumped hydro energy storage and micro applications, J. Energy Storage 24 (2019) 100788, https://doi.org/ 10.1016/j.est.2019.100788. [65] A. Muhirwa, W.H. Cai, W.T. Su, Q. Liu, M. Binama, B. Li, J. Wu, A review on remedial attempts to counteract the power generation compromise from draft tubes of hydropower plants, Renew. Energy 150 (2020) 743e764, https://doi.org/10.1016/j.renene.2019.12.141. [66] S. Muntean, R. Susan-Resiga, E. Goede, A. Baya, R. Terzi, C. Tıˆrs¸i, Scenarios for refurbishment of a hydropower plant equipped with Francis turbines, Renew. Energy Environ. Sustain. 1 (30) (2016) 1e6, https://doi.org/10.1051/rees/2016030. [67] H.I. Nogueira, M. Pfister, A.J. Schleiss, Approaches to reduce friction losses in headrace waterways of hydropower plants, J. Hydraul. Eng. 142 (5) (2016) 02516001, https:// doi.org/10.1061/(ASCE)HY.1943-7900.0001123. [68] J. Obrovsky, J. Zouhar, M. Abraham, A. Skotak, Development of wide operating range runner for Francis turbine upgrading, IOP Conf. Ser. Earth Environ. Sci. 240 (2019) 022014, https://doi.org/10.1088/1755-1315/240/2/022014.

320 PART | VII Hydropower [69] D. Pagliari, L. Rossi, D. Passoni, L. Pinto, C. De Michele, F. Avanzi, Measuring the volume of flushed sediments in a reservoir using multi-temporal images acquired with UAS, Geomat. Nat. Hazards Risk 8 (1) (2017) 150e166, https://doi.org/10.1080/ 19475705.2016.1188423. [70] B. Papillon, T. Freeman, Rehabilitating the Francis Units at Chief Joseph, Hydro Rev. 32 (8) (2013). [71] D. Paravan, T. Stokelj, R. Golob, Improvements to the water management of a run-of-river HPP reservoir: methodology and case study, Control Eng. Pract. 12 (4) (2004) 377e385, https://doi.org/0.1016/S0967-0661(03)00106-0. [72] T. Patsialis, I. Kougias, N. Kazakis, N. Theodossiou, P. Droege, Supporting renewables’ penetration in remote areas through the transformation of non-powered dams, Energies 9 (12) (2016) 1054. [73] S. Petley, G.A. Aggidis, Transient CFD and experimental analysis for improved Pelton turbine casing designs, IOP Conf. Ser. Earth Environ. Sci. 240 (2) (2019) 022005, https:// doi.org/10.1088/1755-1315/240/2/022005. [74] J. Pott, Manapouri turbine upgrade, in: Discussing the Challenges from Inception through to Implementation, HydroVision 2006 Conference, HCI Publications, Kansas City, Missouri, USA, 2006, 2006.  [75] P. Punys, A. Kvaraciejus, A. Dumbrauskas, L. Silinis, B. Popa, An assessment of microhydropower potential at historic watermill, weir, and non-powered dam sites in selected EU countries, Renew. Energy 133 (2019) 1108e1123. [76] E. Quaranta, P. Davies, Emerging and innovative materials for hydropower engineering applications: turbines, bearings, sealing, dams and waterways, and ocean power, Engineering (2021), https://doi.org/10.1016/j.eng.2021.06.025. [77] E. Quaranta, G. Aggidis, R.M. Boes, C. Comoglio, C. De Michele, E.R. Patro, A. Pistocchi, Assessing the energy potential of modernizing the European hydropower fleet, Energy Convers. Manag. 246 (2021) 114655. [78] E. Quaranta, M. Bonjean, D. Cuvato, P. Sarma, G. Slachmuylders, R. Clementi, F. Pasut, N. Bragato, Hydropower case study collection: innovative low head and ecologically improved turbines, hydropower in existing infrastructures, hydropeaking reduction, digitalization and governing systems, Sustainability 12 (2020) 8873, https://doi.org/10.3390/ su12218873. [79] E. Quaranta, J.I. Pe´rez-Dı´az, P. RomeroeGomez, A. Pistocchi, Environmentally enhanced turbines for hydropower plants: current technology and future perspective, Front. Energy Res. 592 (2021a). [80] E. Quaranta, C. Trivedi, The state-of-art of design and research for Pelton turbine casing, weight estimation, counterpressure operation and scientific challenges, Heliyon 7 (12) (2021) e08527. [81] H. Reif, A. Fust, Neubau des Wehres und Kraftwerk Rheinfelden (New construction of the Rheinfelden weir and hydropwer plant), Wasserwirtschaft 98 (12) (2008) 12e17 ([in German]). [82] J. Remondeulaz, L’ame´nagement Cleuson-Dixence dans une perspective de l’ouverture du marche´ de l’e´lectricite´ (The Cleuson-Dixence scheme in the perspective of electricity market opening), Wasser Energ. Luft 90 (1/2) (1998) 1e9 ([in French]). [83] L. Ribordy, Le puits blinde´ et le re´partiteur de l’ame´nagement Cleuson-Dixence (The penstock and bifurcated pipe of the Cleuson-Dixence scheme), Wasser Energ. Luft 90 (3/4) (1998) 53e60 ([in French]).

Retrofitting and Refurbishment of hydropower plants Chapter | 9

321

[84] M. Salleberger, C. Michaud, H. Born, S. Winkler, M. Peron, Design and Manufacturing of Francis Runners for Rehabilitation Projects, Hydro 2001, Riva del Garda, 2001. [85] C.J. Sandt, M.W. Doyle, The hydrologic and economic feasibility of micro hydropower upfitting and integration of existing low-head dams in the United States, Energy Pol. 63 (2013) 261e271. [86] A.J. Schleiss, M.J. Franca, C. Juez, G. De Cesare, Reservoir sedimentation, J. Hydraul. Res. 54 (6) (2016) 595e614, https://doi.org/10.1080/00221686.2016.1225320. [87] A. Schleiss, H. Ehrbar, J.P. Gisiger, Mauvoisin II hydropower project: geotechnical investigations and design of rock supporting works for an underground powerhouse with significant depth of rock cover [in German: Kraftwerksprojekt Mauvoisin II e Sondierkampagne und Bemessungskonzept fu¨r eine tiefliegende Kavernenzentrale], Felsbau 14 (6) (1996) 377e384. [88] D.S. Semerci, T. Yavuz, Increasing efficiency of an existing francis turbine by rehabilitation process, in: 2016 IEEE International Conference on Renewable Energy Research and Applications (ICRERA), Birmingham, 2016, pp. 107e111, https://doi.org/10.1109/ ICRERA.2016.7884440. [89] D. Silva, F. Carazas, G. Souza, Method to select instrumentation for hydraulic turbines in upgrading process, in: 2009 International Conference on Computers & Industrial Engineering, IEEE), 2009, pp. 1192e1197. [90] N.M. Silve´rio, R.M. Barros, G.L. Tiago Filho, M. Redo´n-Santafe´, I.F.S. dos Santos, V.E. de Mello Vale´rio, Use of floating PV plants for coordinated operation with hydropower plants: case study of the hydroelectric plants of the Sa˜o Francisco River basin, Energy Convers. Manag. 171 (2018) 339e349, https://doi.org/10.1016/j.enconman.2018.05.095. [91] J. Swiderski, J. Martin, High Power Francis Runner e Upgrade with a New Design Runner, Norcan Hydraulic Turbine Inc, 1999 report). [92] S. Tomanova, D. Courret, S. Richard, P.A. Tedesco, V. Mataix, A. Frey, S. Te´tard, Protecting the downstream migration of salmon smolts from hydroelectric power plants with inclined racks and optimized bypass water discharge, J. Environ. Manag. 284 (2021) 112012. [93] L. Tomas, S. Tridon, X. Cornut, Kaplan-Bulb turbine upgrade based on numerical simulation, Hydropower Dams 22 (4) (2015). [94] R. Uria Martinez, M. Johnson, R. Shan, US Hydropower Market Report (January 2021 Edition) (No. ORNL/SPR-2021/1782, Oak Ridge National Lab (ORNL), Oak Ridge, TN (United States), 2021. [95] M. Valavi, A. Nysveen, Variable-speed operation of hydropower plants: past, present, and future, in: 2016 XXII International Conference on Electrical Machines (ICEM), IEEE, 2016, pp. 640e646. [96] J. Vesely´, M. Varner, A Case Study of Upgrading of 62.5 MW Pelton Turbine. Upgrading and Refurbishing Hydro Power Plants VIII. Prague, Czech Republic, 2001. [97] XFLEX HYDRO, Latest News on the Demonstrations, 2021. https://xflexhydro.net. [98] A.M. Yanmaz, O. Ari, A study on dam instrumentation upgrading, KSCE J. Civ. Eng. 15 (2) (2011) 317e325, https://doi.org/10.47260/jesge/1115. [99] Z. Yumeng, G. Li, Z. Mi, Z. Fu, K. Wei, Heightening of an existing embankment dam: results from numerical simulations, chapter 2, in: Z. Fu, E. Bauer (Eds.), Dam Engineering, IntechOpen, 2020, https://doi.org/10.5772/intechopen.92221. [100] A. Immendoerfer, I. Tietze, H. Hottenroth, T. Viere, Life-cycle impacts of pumped hydropower storage and battery storage, Energy Environ. Eng. 8 (3) (2017) 231e245.

322 PART | VII Hydropower [101] R. Pfammatter, N. Semadeni Wicki, Energieeinbussen aus Restwasserbestimmungen e Stand und Ausblick, Wasser Energie Luft 110 (2018) 233e245. [102] E. Quaranta, A. Bahreini, A. Riasi, R. Revelli, The Very Low Head Turbine for hydropower generation in existing hydraulic infrastructures: state of the art and future challenges, Sustain. Energy Technol. Assess. 51 (2022) 101924. [103] S.J. Van Vuuren, C.L. Blersch, M. Van Dijk, Modelling the feasibility of retrofitting hydropower to existing South African dams, Water SA 37 (5) (2011) 679e692. [104] A. Wo¨rman, C.B. Uvo, L. Brandimarte, S. Busse, L. Crochemore, M.G. Lopez, J. Riml, Virtual energy storage gain resulting from the spatio-temporal coordination of hydropower over Europe, Appl. Energy 272 (2020) 115249.

Part VIII

Energy storage

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Chapter 10

Thermocline packed bed thermal energy storage system: a review Baoshan Xie1, Nicolas Baudin1, Je´roˆme Soto1, 2, Yilin Fan1 and Lingai Luo1 1 2

Nantes Universite´, CNRS, Laboratoire de thermique et e´nergie de Nantes, LTeN, Nantes, France; Institut Catholique d’Arts et Me´tiers de Nantes, ICAM, Carquefou, France

1. Introduction Energy demand is in rapid growth especially for energy sources without environmental issues of global warming and air pollution. The International Energy Agency (IEA) pointed out in “Tracking Report 2020” that the renewable energy counted for about 27% of the global electricity production in 2019 [1]. However, the use of renewable power needs to be significantly increased to half of the production to meet the demand of sustainable development scenario by 2030. Solar energy as a feasible alternative to fossil fuel is one of the promising options due to the large quantities of solar radiation on the surface of earth [2]. However, the solar power source and the power demand are both intermittent, and often in mismatch. To address these problems, the thermal energy storage (TES) system can be integrated in solar power plants to promote the system reliability and to replace conventional fossil fuel backup systems [3e5]. This economic and CO2 emission free solution allows buffering transient weather conditions, increases the annual capacity factor and evens the electricity production [6]. More than that, the TES has been applied in various energy systems in order to improve the system stability and efficiency, including solar water heater, waste heat recovery system, cooling system, and many others [7e13]. There are different ways to store heat: the sensible heat storage based on a change of temperature, the latent heat storage based on a physical status change, and the thermochemical storage based on endothermic/exothermic chemical reactions [14,15]. The thermochemical storage can potentially store more energy per volume unit (nearly 109 J/m3) but suffers from high complexity and costs [16] thus will not be involved in this chapter. In singleRenewable Energy Production and Distribution. https://doi.org/10.1016/B978-0-323-91892-3.24001-6 Copyright © 2022 Elsevier Inc. All rights reserved.

325

326 PART | VIII Energy storage

media systems, heat storage is achieved using the sensible heat transfer fluid (HTF) only, such as in domestic hot water tanks [17]. However, in concentrated solar power (CSP) plant applications, those require high temperatures and thus expensive and nonenvironmental friendly fluids, which usually shows poor thermal properties. The packed bed or dual-media is then preferred, with solid fillers in the tank acting as main storage media, exchanging heat with HTF through direct contact, decreasing thereby the total amount of HTF required. There are other considerations when conceptualizing a TES system, such as using active or passive, direct or indirect concept (Fig. 10.1). Such aspect will not be detailed here and the following parts of the chapter will focus on the storage tanks themselves. Typically the integrated TES system is designed as a one-tank or a twotank system [6,19]. In two-tank system, the HTF is stored in two isolated and insulated tanks with two extreme temperatures. One primary example of a two-tank system is a CSP plant, shown in Fig. 10.1A. In daytime, the HTF collects solar heat energy from solar receiver and transfers heat to the steam generator for power generation, and extra heat energy is stored in a hot tank. During the night or insufficient sunlight day, the HTF from the hot tank is delivered and used to maintain the power production. The one-tank system

FIGURE 10.1 CSP plant with Brayton gas cycle: (A) two-tank direct; (B) one-tank direct; (C) one-tank packed-bed direct; (D) one-tank packed-bed indirect storage systems [18]. Adapted from figures that obtained the copyright permission of Elsevier (License No. 5207601058078, December 14, 2021).

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(or single-tank) is a substitution of the conventional two-tank system that greatly cuts off investment costs by removing a tank, as shown in Fig. 10.1B. In this system type, the hot HTF is stored at the top, and the cold HTF stays at the bottom of tank. Physical stratification between both HTFs is maintained by buoyancy forces due to the density difference (hot HTF is lighter than cold one) [20]. The area in between the hot and cold HTF, characterized by a temperature gradient, is called thermocline and is represented on Fig. 10.2. With cheap fillers and smaller tank volume, the cost reduction of overall investment can be up to 35% for packed-bed TES tank in comparison with traditional two-tank TES system in CSP plant [21]. For many packing materials used in industry, the energy density in theory is about 180e250 MJ/m3 (or 50e70 kWhth/m3) based on a temperature change of about 100
C [22]. Due to these advantages, the thermocline packed-bed TES system is considered to be a promising technology for solar energy application, embracing the low-temperature and high-temperature ranges [23]. However, the shortcoming of the thermocline TES system also exists: most of the thermocline area is a “dead zone” because the heat stored in this region is mostly at a temperature lower than the cutoff temperature, under which the charging/discharging process is hard to be operated (Fig. 10.3). The thermocline degradation occurs or thermocline thickness increases in operation caused by many physical phenomena, including: l l l l

l l

Thermal diffusion in the solid fillers and the fluid. Heat losses through the walls. Heat convection of HTF itself resulted from flow turbulence in porous bed. Limited heat convection between solid and fluid causing heat transfer delay. Variable operational conditions during charging and discharging. Nonuniform flow distribution at the inlet due to sudden fluid injection or near the wall region because of the different porosities.

FIGURE 10.2 Schematic of thermocline during (A) charging and (B) discharging.

328 PART | VIII Energy storage

FIGURE 10.3 Illustration of intermediate “dead zone” in conventional rock-filled thermocline tank [24]. Adapted from copyright permission of Elsevier (License No. 5207601468200, December 14, 2021).

In addition, the thermocline packed-bed system faces challenges like conflict between high storage capacity per unit volume and low cost, the temperature drop or heat loss at the end of heat storage/release cycles, pressure drop under high porosity bed, and stability under various operational parameters. Therefore, investigations on the physical phenomena influencing the thermocline thickness and on the performance optimization under technoeconomic constraints of the single tank parameters are required. Only through that, the development of the thermocline packed-bed system will become more attractive. This chapter continues with a presentation of the different elements and components in thermocline packed-bed systems, followed by the performance indicators used to evaluate them, the performance improvement factors or influence factors. The fourth part compares several packed bed configurations, leading to a conclusion about the strength and disadvantages of each system. The fifth part presents how to investigate and optimize these systems: experimental works are scarce but many numerical models are available.

2. Packed bed thermal energy storage system components The main elements of a packed-bed thermocline TES system are (sensible and/ or latent) fillers, the HTF, the wall and insulation [25], and the inlet/outlet manifolds or diffusers. The following section presents these different components and the properties considered for the appropriate design.

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329

2.1 Solid fillers 2.1.1 Sensible material fillers Sensible heat storage occurs when the temperature of material rises. When choosing the materials, the important thermal properties are the volumetric heat capacity (r$Cp , J/m3 K), which dictates the energy density capability, and
  l ; m2 s , which reflects the rate of the heat released the heat diffusivity r$C p and absorbed [26]. Table 10.1 lists some sensible material fillers for packed-bed TES system and corresponding thermophysical properties. For most of sensible heat storage materials, the volumetric heat capacity can vary TABLE 10.1 Thermophysical properties of common sensible fillers for thermocline packed-bed TES. Sensible fillers

rs (kg/m3)

Cp,s (J/kg K)

ls (W/m K)

rs$Cp,s (kJ/m3 K)

Ref.

Cast iron

7900

837

29.3

6612

[27]

Steel

7870

565e571

49.8

4447e4494

[28,29]

Magnesia fire brick

1150

3000

5.0

3450

[30]

Coal fly ash brick

2600

735e1300

1.3e2.1

1911e3380

[31]

Castable ceramic

3500

866

1.4

3031

[32]

Blast furnace slag

2980

996

2e3.5

2968

[33]

Alumina (Al2O3) ceramic

3750

780

30

2925

[34]

Steatite

2680

1068

2.5

2862

[29,35]

Alumina

3670

750

21

2753

[31]

Granite rock and sand

2643

1020

2.2

2696

[36]

Concrete

2800

916

1.0

2565

[32,34,37]

Copper slag

3600

683 (300
C)

0.8

2450

[38]

Aluminum

2700

896

204

2419

[29]

Silicon carbide (SiC) ceramic

3210

750

120

2408

[34]

Quartzite rock and sand

2500

830

5.7

2075

[27]

Silica fire brick

1820

1000

1.5

1820

[30]

Soda-lime glass

2400

760

1.0

1824

[28]

330 PART | VIII Energy storage

between 900 and 3000 kJ/m3 K [39]. With favorable features of the proper volumetric heat capacity, low cost, and availability, sensible heat material is commonly used in industrial or lab thermocline tanks. Rocks are interesting fillers in packed-bed TES system since they have a high heat capacity and are cheap. Tiskatine et al. (2017) [32] evaluated 52 sensible heat materials of a packed-bed system for high-temperature CSP application. Among those, four types of materials, the dolerite, granodiorite, hornfels, gabbro, and quartzitic sandstone were found to be excellent in air-based solar. The amount of stored energy (Q, J) for a given temperature elevation is calculated as: ZT2 Q¼

m $Cp;s $dT

(10.1)

T1

where T1 (K) and T2 (K) is the initial and final temperature, respectively, m (kg) is the mass, Cp (J/kg K) is the specific heat capacity, and subscript ‘s’ refers to solid phase. r (kg/m3) is the density and l (W/m K) is the thermal conductivity. 2.1.2 Phase change material fillers Latent heat storage occurs when a material changes its phase from one physical state to another. When used in an industrial context of heating/ cooling, a material that undergoes this phenomenon and releases/absorbs sufficient heat in a narrow temperature range is called phase change material (PCM). Four types of phase transition exist [6]: solid-solid (crystalline heat), solid-liquid (fusion heat), liquid-gas (vaporization heat), and solid-gas (sublimation heat). Among them, PCM based on solid-liquid transition shows high melting/freezing enthalpy (e.g., around 200 J/g for organic paraffin) and is therefore widely used in TES [40e43]. As explained in Fig. 10.4, the material changes its phase from solid to liquid when temperature increases, and more amount of heat is exchanged during the latent storage in comparison to the sensible storage. In the following context, PCM is mainly refers to solid-liquid phase transition. Table. 10.2 lists several candidate PCM fillers and the corresponding thermophysical properties. The stored energy in different heating stages is calculated as: ZT2 Q¼

m $Cp;s $dT

ðT2 < Tm Þ

(10.2)

T1

ZTm Q¼

m $Cp;s $dT þ m$DHm T1

ðT2 ¼ Tm Þ

(10.3)

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331

FIGURE 10.4 Phase change temperature profiles [44,45]. Adapted from the figure that obtained the copyright permission of Elsevier (License No. 5207611412736, December 14, 2021).

ZTm Q¼

ZT2 m $Cp;s $dT þ m $DHm þ

T1

m $Cp;l $dT

ðTm < T2 Þ

(10.4)

Tm

where Tm (K) is the phase change temperature, T1(K) and T2 (K) is the initial and ending temperature, respectively, DHm (J/kg) is the phase change enthalpy, and the subscript ‘l’ refers to liquid phase of PCM. The phase change temperature is commonly maintained at a relatively stable value, allowing a constant temperature heat exchange for process control. But in some real cases, the phase change temperature is not a so stable platform and a small temperature range in phase transition actual appears [44]. This small gap is called the “sup-cooling” phenomenon caused by the nucleation rate [52,53]. According to this narrow temperature gap [54e56], the apparent heat capacity method accounting for latent heat as an equivalent heat capacity in this temperature range is usually used [57]. Moreover, due to the natural convection inside encapsulated PCM as shown in Fig. 10.5, the effective thermal conductivity is considered [60]. The density variation of PCM in phase change process can be negligible in the constant capsule volume [61]. Using encapsulated PCM as fillers is helpful to improve the stability and the sharpness of the thermocline in a packed-bed tank owing to the features presented above. Putting the PCM near the ports of tank system can restrict the outlet temperature at a constant value [62]. Ge et al. (2013) [51] summarized several types of PCMs that can be used in solar energy storage. Mixed molten

Solid

Phase transition


Liquid

PCM fillers

rs (kg/m )

Cp,s (J/kg K)

ls (W/ m K)

DHm (J/g)

Tm ( C)

rl (kg/m )

Cp,l (J/kg K)

ll (W/ m K)

Ref.

Na2SO4$10H2O

1485

1760

0.544

251

32.4

1458

3300

0.544

[46]

3

3

N-eicosane

788

2460

0.15

247

36.8

788

2460

0.15

[47]

Paraffin

910

2510

0.21

189

40e43

765

2210

0.29

[48]

Paraffin

789

1800

0.18

206

300.7

750

2400

2.40

[49]

DHm (J/g)

Tm (
C)

Examples

e

125e400

12e187

Paraffin, n-alkenes, mixture, fatty acids

e

e

270650

20e140

Na3SO4$10H2O, CaCl2$6H2O, Ca(NO3)2$4H2O, MgSO4$7H2O

1700e2500

e

e

200e500


> 1=6 < = lair 0:387$Raair 0:825 þ h hext ¼ ; Raair < 1012 (10.6) i 8=27 > H > 9=16 : ; 1 þ ð0:492=Prair Þ 3

where Raair ¼ Grair $Prair is the Rayleigh number (Ra), Grair ¼ g$b$Hv2 $DT is the Grashof number (Gr) and DT (K) is the temperature difference between surface and air. g (m/s2), b (1/K), and v (m2/s) is the gravity acceleration, thermal expansion coefficient of air, and kinematic viscosity, respectively. l

Heat radiation loss

The radiation heat loss is often ignored in simulation when its proportion is below 5% of the total energy loss [56]. But, for high-temperature TES tanks with molten salt, the outer surface temperature is not negligible even with good insulation layer. The effective outdoor heat transfer coefficient, including convection and radiation, is taken to be 25 W/m2 K based on ISO 6946 [99], despite can be ranged between 17 and 50 W/m2 K [100]. The radiative heat transfer coefficient (hrad , W/m2 K) based on StefaneBoltzmann law is written as follows:   4 ε$s$ T 4  Tamb (10.7) hrad ¼ T  Tamb where ε is the emissivity factor according to insulation properties, and s ¼ 5.67  108 W/m2 K4 is the StephaneBoltzmann constant. T (K) in here is the outer surface temperature. l

Wall heat storage/release

The tank wall absorbs a certain amount of heat from packed-bed in charging process and releases back to the bed in discharging process, leading to the overheated/overcooled fluid temperature in near-wall region compared

340 PART | VIII Energy storage

FIGURE 10.7 Schematic of wall impact for thermocline tank.

to that in central tank region (Fig. 10.7). This wall heat storage/release effect will further affect the thermocline flatness [27,101]. If the wall is bulky or with high heat capacity, the thermocline degradation is stronger. Simultaneously, the wall material with a larger heat diffusion can transfer heat faster, but is unavoidable to induce thermocline decay or instability and thus decreases the system efficiency. Through adding the energy terms of wall or insulation, the influence of volumetric heat capacity from wall and insulation layer on thermal performance of packed-bed thermocline system can be assessed. Models have been introduced in some literatures [76,102] and will be explained in detail in Section 5 of this chapter.

3.1.3 Level of thermal stratification The good thermocline quality of packed-bed TES tanks is often indicated by stable and enhanced thermal stratification. The objective is in fact to minimize the thermocline thickness and to separate the cold and hot HTFs without physical barriers [17]. Some dimensionless parameters are popularly used to reflect the thermal stratification, including the stratification number, the mix number, the thermocline thickness, etc. [103]. l

Stratification number

Stratification number (Str) is the relative value of average temperature gradients at any time in charging/discharging to the maximum average temperature gradient [104e107]: Str ¼

ðvT=vzÞt ðvT=vzt Þmax

(10.8)

Thermocline packed bed thermal energy storage system Chapter | 10




vT vz

" # N 1
t X Tiþ1  Tit 1 ¼ N  1 i¼1 Dz t

341






vT vz





Tmax  Tmin ¼ ðN  1Þ$Dz max

(10.9)

 (10.10)

where the ‘max’ and ‘min’ are the maximum and minimum value, respectively, t (s) is the time, and z is the z-axial coordinates. l

Mix number

A modified mix number (MIX) is proposed by Andersen et al. (2007) [108], taking the vertical temperature profile and the total energy stored in the tank into account [17,109,110]:   Estratified  Eexp  MIX ¼  (10.11) Estratified  Efully; mixed where Estratified , Eexp , and Efully; mixed the energy amount for a totally stratified tank (J), for the experimental tank (J) and for a fully mixed tank (J), respectively. The value of the Mix number ranges between 0 (perfect stratified tank) and 1 (fully mixed tank). l

Thermocline thickness

The thermocline thickness (Lthermocline , m) is defined as the covering length of the stratification region in bed, according to the physical boundary with certain temperature ranges [19,111]. It is calculated as: Lthermocline ¼ zfT ¼ TH  n%$ðTH  TC Þg  zfT ¼ TC þ n%$ðTH  TC Þg (10.12) where the threshold value of thermocline edge is defined as the hottest (TH, K)/ coldest (TC, K) temperature differs n% to the operational temperature range (TH  TC ). Actually, it is an effective thermocline thickness that only counts the part inside the bed. Because the thermocline physical edge may arrive or exceed the bottom/top before the outlet temperature reaches the cut-off temperature in charging/discharging. 3.1.4 Global thermodynamic efficiencies The global thermodynamic efficiencies of system can be evaluated in terms of energy efficiency, exergy efficiency, utilization ratio, capacity ratio, and so on [56]. l

Energy efficiency

Energy efficiency (h) is based on the first thermodynamics law. In charging (hch ), it is the ratio of the energy stored in bed (Estored , J) to the total input

342 PART | VIII Energy storage

energy (Ein, J) by HTF. In discharging process (hdisch ), it is the ratio of the extracted (or released) heat (Ereleased , J) from bed to the stored energy at the start of discharging. hch ¼ hdisch ¼

Estored Ein

(10.13)

Ereleased Estored

(10.14)

This indicator is really straightforward but it cannot give useful information on, for example, how the system approaches an ideal condition or the how fast the heat can be stored or absorbed at a given temperature [17]. l

Exergy efficiency

Exergy efficiency based on the second law of thermodynamics shows the availability (or exergy, Ex, J) in the form of useful energy that can be extracted from the storage [17]. The exergy efficiency in charging and discharging (hx;ch , hx;disch ) is similar to energy efficiency, defined as: hx;ch ¼ hx;disch ¼

Ex;stored Ex;in

(10.15)

Ex;released Ex;stored

(10.16)

In practice, using exergy efficiency shows two advantages: (1) it considers the temperature differences for the same energy content storages which suits better the TES systems with thermal stratification; and (2) it considers the causes and the position of quantitative losses such as the mixing of HTF at different temperatures as well as heat losses toward the environment, information eventually required for performance improvement [17].

3.1.5 Cost The capitalized cost is an important criterion of a TES system in addition to the capacity ratio or efficiency. The capitalized cost of thermocline packed-bed system involves several aspects: (1) the storage media and HTF themselves; (2) the enclosure of TES container like tank wall and insulation. The heat exchanger part can usually be removed for packed-bed thermocline TES tank, greatly reducing the cost as have been introduced in many investigations. For instance, Mostafavi Tehrani et al. (2019) [112] reported that the dual-media thermocline system could reduce the cost by 49% compared to a pipeless shell-and-tube system. Galione et al. (2005) [54] reported that by using abundant packing materials such as rocks, pebbles and sands, and with cheap HTF, the cost can be reduced by 70% than two-tank system.

Thermocline packed bed thermal energy storage system Chapter | 10

343

3.2 Performance influencing parameters The factors that influence the performance of packed-bed thermocline systems may be classified into operational parameters, geometrical parameters, and thermophysical parameters [113], as illustrated in Fig. 10.8. The operational parameters are commonly decided by the requirements of certain application. The geometrical parameters include the tank and filler geometries and configurations. The thermophysical parameters are mainly decided by the selected material themselves and are usually temperature and/or pressure dependent. Some of these factors are introduced in detail in this subsection.

3.2.1 Operational parameters The HTF mass flow rate, the inlet temperature, the cut-off temperature, and the cycling number are main operational parameters. l

Mass flow rate

The HTF mass flow rate mainly determines the flow conditions and heat transfer rate between different phases. Commonly, higher flow velocity is beneficial to reduce the charging/discharging time due to the increment of heat transfer rate between HTF and solid fillers [50,55,117]. Nallusamy et al. (2006) [118] proved that when the flow rate increased from 2 to 6 kg/min, the time required for the complete charging decreased by 24% in a PCM packedbed thermocline system. However, some works found that the total stored energy in the tank [69] and the thermocline development [117,119] were less influenced by the HTF flow rate. In fact, the impacts of the high velocity on uneven flow temperature distribution and stratification cannot be neglected in

FIGURE 10.8 Influencing parameters of packed-bed thermocline TES system.

344 PART | VIII Energy storage

actual cases. The mass flow rate should be determined by comprehensively considering various factors such as the complete time, the efficiency and the flow distribution uniformity. More discussion on the influence of this parameter can be found in Ref. [120]. l

Inlet temperature

The inlet temperature is usually decided by application specifications. It determines the temperature difference thus the driving force for the heat transfer between HTF and solid fillers, but also responsible for the heat loss from the storage tank to the ambient. The inlet temperature impacts on heat transfer rate, heat loss, and total stored/released energy should be firstly investigated before system optimization [50]. More information about the influence of this parameter is presented in Ref. [120]. l

Cut-off temperature

Likewise, the cut-off temperature referring to the termination condition of operation which is usually decided application specifications. It is often set as 0.8e0.95 times to working temperature range in discharging process, and 0.05e0.2 times in charging process [75,121,122]. With lower cut-off temperature, the storage tank cannot be fully charged. In discharging, a lower cutoff outlet temperature will cause more heat loss because of longer operation time, and may be insufficient to drive the power generation or energy supply. l

Cycling operation

Efficient thermal cycling is closely related to the level of thermal stratification inside the tank [123]. Firstly, the thermocline zone is expanding and stratification degrading after several charging/discharging cycles, causing the declined efficiency [27]. In the end, the thermocline region could occupy the whole tank volume. Secondly, the heat loss and pumping loss increase as the cycling number increases [94]. As a result, a trade-off of the cycling numbers should be decided according to the output, thermocline thickness, to optimize the capacity and efficiency of system for long-term use.

3.2.2 Geometrical parameters l

Tank diameter-to-height ratio (aspect ratio)

 D leads to the decreased In general, the increasing aspect ratio of tank H heat loss because of the smaller lateral wall surface area for the same bed volume. Zanganeh et al. (2015) [94] reported that when the ratio increase from 0.5 to 2, the fraction of the pumping energy strongly decreased from 6.75% to 0.75% due to the shorter bed length. Conversely, the overall efficiency decreased due to the weaker heat transfer rate caused by the decreased fluid velocity at constant inlet mass flow rate.

Thermocline packed bed thermal energy storage system Chapter | 10

l

345

Particle size

Sensible fillers could have a wide range of average particle size, usually varying between 1  103 me0.05 m. Bruch et al. (2014) [124] once investigated the fluid flow through a 3 mm sand bed and a 3 cm rock bed in pilot-scale thermal oil bed system. Smaller particle diameter facilitates the flow distribution for better thermal stratification and can increase heat transfer surface area [125], but in the meantime will cause higher pressure drops. Even the influence of boundary effect of mass transfer can be alleviated under a large bed-to-particle diameter ratio [35,80]. Larger particles (with lower thermal conductivity) may extend the temperature gap between solid and fluid, causing the faster expansion of the thermocline [34]. Sorour (1988) [126] suggested to use intermediate particle size of 18 mm with low Reynold number (Re) instead of small particle size of 12 mm with high Re to increase the storage efficiency. PCMs use the “container” to seal the material to avoid leakage. The encapsulated PCM capsules may be classified based on the diameter into: macro (>1 mm); micro (1e1000 mm); nano ( > > x1 ðtÞ ¼ c01 þ c11 t > > < x ðtÞ ¼ c þ c t 2 02 12 (11.5) > « > > > > : xp ðtÞ ¼ c0p þ c1p t where c01 ; c02 ; :::; c0p ; c11 ; :::; c1p are the constants of simple LRs. The MLR technique can be summarized by the algorithm depicted in Fig. 11.8.

4.2 NARX technique NARX and NAR neural networks are associated to the same ANN category, and the only difference between these techniques is that NARX model consider the exogenous input parameters in the forecasting process [33]. The output signal yðtÞ can be expressed as a function of input signal xðtÞ as follows:    yðtÞ ¼ f xðt  1Þ; .; xðt  dx Þ; yðt  1Þ; .; y t  dy (11.6) where dx and dy are, respectively, the input and output time offsets of the NARX network.

Long-term load forecasting Chapter | 11

401

FIGURE 11.8 MLR algorithm.

Fig. 11.9 illustrates the NARX network structure which consists of three main layers: the input, the hidden, and the output layers. The first layer consists of the present and prior inputs and outputs that are then fed into the hidden layer.

5. Performance measurement criteria The performance comparison of different techniques is mainly based on the evaluation of the prediction error. The latter is defined as the difference

402 PART | IX Smart grids

Z 1

Wi h1

Whh1 2

bh1

bh 2

Wh0N

l

b0

FIGURE 11.9 NARX architecture.

between y, the actual value of the electricity consumption and yb, the estimated one. Therefore, we define the Mean Absolute Error (MAE), Mean Absolute Scaled Error (MASE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) as follows: 1 0 k X 1 jeðtÞj C B (11.7) MASE ¼ A @ 1 k t¼1 jyðtÞ yðt  1Þj k1 MAEðWÞ ¼

k 1X jeðtÞj k t¼1

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u k u1 X RMSEðWÞ ¼ t e2 ðtÞ k t¼1 MAPEð%Þ ¼

k 1X jeðtÞj  100 k t¼1 yðtÞ

(11.8)

(11.9)

(11.10)

These criteria are the most widely used ones in the literature [34]. The MAPE and RMSE errors allow to evaluate the performance of the forecast by presenting raw (nonnormalized) quantifications. When the consumption tends to zero, the MAPE itself tends to a very large value that is difficult to process. In order to overcome this problem, the MASE criterion is proposed for intermittent time series in particular. This criterion allows to have an accurate prediction around zero. Its particularity lies in the fact that it never gives infinite values except in the case where all the yðiÞ measurements are identical. Since the load data are always quite far from zero, the MAPE criterion is sufficient because it has a significant relative error. Thus, the MAPE criterion is chosen in this study to assess the forecast accuracy. The threshold value of this criterion is selected referring to the literature where some works are

Long-term load forecasting Chapter | 11

403

summarized in Table 11.1. The literature review shows that a MAPE under 3% is judged to be satisfactory. Consequently, the MAPE cut-off is fixed to 3%, where forecasts beyond this limit are regarded as critical points.

6. Simulation results and discussion As mentioned in Section 2.1, the electricity consumption dataset consists of 264 samples, the latter is split into subsets of different sizes as a function of the studied time frame. For the NAR and NARX techniques, these subsets are further segmented into three sets; 70% for learning, 15% for validation, and 15% for testing. The NAR and NARX training technique, the most common one is the LevenbergeMarquardt backpropagation procedure [51]. The MAPE is computed for several time frames and various forecast horizons and the results are summarized in Tables 11.2 and 11.3. The analysis of these results reveals that the MAPE exceeds the fixed threshold in some cases which demonstrates the presence of critical points after which the forecasts’ accuracy is affected. For the time series techniques, the MAPE vary from 0.6% to 14.11% and from 0.34% to 41.95%, respectively, for ARIMA and NAR techniques for a study time frame lower than 10 years. Over a 10-year time period, the NAR technique does not outpace the fixed MAPE limit for various forecasting horizons, unlike the ARIMA models which show some critical points like 1995, 2005, and 2010 after which the prediction accuracy is reduced. The presence of these critical points may be explained by two hypotheses: (1) ARIMA models have a limited ability to track load pattern changes when the load becomes nonuniform, (2) external factors other than historical electricity consumption data may exist and whose influence is important and may significantly affect the prediction performance. The first assumption is verified by comparing simulation results of ARIMA models and NAR techniques for a 10-year study period where all critical points are eliminated for the NAR technique which reveals that ARIMA models performance is limited for this time frame. For the second assumption, it is proved by the persistency of the critical points 1995 and 2005 for both ARIMA and NAR techniques which demonstrates the influence of exogenous factors that cannot be dismissed. For econometric approaches, the simulation results for several time frames indicate that the “CO2 emissions” factor appears in all the chosen combinations, followed by “EXGS,” which reveal the importance of both variables in predicting the electricity demand. Referring to Tables 11.2 and 11.3, MLR technique results show that the critical points 2000 and 2005 are present in all the studied time frame. This implies two assumptions: (1) the limitation of the technique, (2) the presence of a new factor that has a high impact on the variation of electricity consumption. Regarding NARX technique, the simulation results show a good forecast with an average MAPE of 0.93% for a forecasting horizon of 5 years. For the remaining time periods under study, the

References

Methods

Forecasting horizon

MAPE

References

Methods

Forecasting horizon

MAPE

[35]

ACO

1979e2025

1.07%

[36]

ANN-TLBO

1980e2020

1.50%

[37]

GA

1980e2025

2.72%

[38]

ANN-PSO

1967e2030

1.51%

[39]

SA

1990e2020

1.6%

[40]

ANN-GA

1981e2008

3.68%

[41]

PSO

1982e2030

1.16%

[42]

SVR-DE

1987e2008

1.1%

[43]

ABC

1981e2030

2.26%

[44]

Optimized GM

2001e12

3.23%

[45]

ICA

1986e2017

1.14%

[46]

ARIMA-PSO

2006e10

2.19%

[47]

ACO-ILS

1990e2030

1.15%

[48]

Fuzzy-GA

1990e2010

7.45%

[49]

PSO-ACO

1979e2025

1.03%

[50]

PSO-GA

1980e2006

0.98%

Mean

e

e

e

e

e

e

2.11%

404 PART | IX Smart grids

TABLE 11.1 Review of the research on energy demand forecasting by different methods.

Long-term load forecasting Chapter | 11

405

TABLE 11.2 MAPE of different techniques as a function of forecasting horizon for a 5-year study period.

NARX technique has demonstrated its superiority over the MLR with an average MAPE of 0.58%. However, the NARX technique has also presented some critical points: 1985, 1990, 1995, and 2000. The first three critical points are shared with NAR technique which shows that the hypothesis of exogenous factors is no more valid. The simulation results of the various forecasting techniques for a 5-year forecasting horizon under different time frames are depicted in Fig. 11.10. The latter shows that the predicted and the real values are in agreement for the majority of the studied time periods for the MLR, NAR, and NARX techniques. It can also be detected that the prediction accuracy is better for a study period greater than 15 years for the MLR, NAR, and NARX techniques. Yet, NARX shows a better performance even when the studied time frame is restricted to 5 years contrary to other techniques. It can also be figured out that the prediction accuracy is better for a study period over 15 years for the MLR, NAR, and NARX. Furthermore, it is observed that for ARIMA models, acceptable forecasting results are achieved when the load pattern is almost linear as in the case of 15 and 30 years’ time frames, however, the forecasting performance is reduced for the rest of the studied periods.

406 PART | IX Smart grids

TABLE 11.3 MAPE of different techniques as a function of forecasting horizon for a study period higher than 5 years. Forecasting horizon Study period

1971-1980

1981-1990

1991-2000

2001-2010

1971-1985

1986-2000

1971-1990

1991-2010

1971-1995

1971-2000

1971-2005

1971-2010

MAPE (%) Technique BJ NAR MLR NARX BJ NAR MLR NARX BJ NAR MLR NARX BJ NAR MLR NARX BJ NAR MLR NARX BJ NAR MLR NARX BJ NAR MLR NARX BJ NAR MLR NARX BJ NAR MLR NARX BJ NAR MLR NARX BJ NAR MLR NARX BJ NAR MLR NARX

5 years 1,5 1,99 4,84 2,08 1,07 0,51 1,2 0,65 1,23 0,88 1,61 1,38 0,68 1,75 0,7 0,155 1,27 0,32 1,11 0,318 1,03 0,3 1,75 0,38 2,9 0,34 0,9 0,22 0,69 0,253 1,06 0,169 6,27 0,27 6,8 0,43 0,66 0,27 1,46 0,163 4,57 0,21 4,54 0,19 0,69 0,33 0,62 0,62

10 years 1,95 6,17 3,69 4,32 3,29 1,5 2,97 1,87 2,15 3,78 3,67 1,48

15 years 2,38 10,9 4,01 4,8 4,94 2,98 4,15 3,25 2,96 6,21 3,48 1,89

20 years 3,89 16,35 6,64 5,77 6,47 4,8 6,95 4,68

25 years 5,4 21,53 9,76 8,49 7,6 6,2 7,88 5,77

30 years 6,91 26,31 15,04 13,4

34 years 7,97 29,17 18,94 17,58

Factors Pop, IMGS, CO

SSER, EXGS, CO

SSER, EXGS, CO

Pop-15-64, IMGS, CO 1,67 0,44 0,92 0,58 1,97 1,49 5,88 0,71 5,52 0,33 1,41 0,31

3,5 0,78 1,22 0,96 2,55 2,64 6,63 1,14 7,42 0,51 1,33 0,53

5,16 1,34 1,25 0,968

6,74 1,93 2,11 1,07

7,87 2,39 2,36 1,074

Pop, SSER, EXGS, CO SSER, EXGS, CO

9,13 0,75 2,41 0,69

10,34 0,98 2,67 1,02

Pop, SSER, EXGS, CO Pop-1564, IMGS, CO

7,84 0,54 5,06 0,45 2 0,54 4,57 0,44 6,07 0,32 7,27 0,28

9,4 0,95 6,09 0,54 3,14 0,8 4,96 0,57

10,6 1,27 7,21 0,74

SSER, EXGS, CO

Pop, SSER, EXGS, CO

SSER, GDP, CO

Pop-1564, IMGS

The simulation results for a 15-year time period for different prediction horizons are depicted by Fig. 11.11. The latter show that the forecasts’ precision decreases as the forecasting time frame increase. NAR and NARX techniques show a better tracking of the electricity load pattern demonstrated by the reduced MAPE which does not exceed the threshold value, 3%, for a 10-year study period and above. However, the accuracy of the prediction is

Long-term load forecasting Chapter | 11

500

Study time frame (5 years) 1000

450

BJ NAR

400

M LR NARX

350 300 250 200 1 976

1 977

Study time frame (25 years) M easured

Electricity consumption (KWh)

Electricity consumption (KWh)

M easured

1 978

1 979

950

BJ NAR

900

M LR NARX

850 800 750 1996

1 980

1997

Study time frame (10 years)

500

NAR M LR

480

NARX

Electricity consumption (KWh)

Electricity consumption (KWh)

520

460 440 420 1982

1983

1984

1080 1060 1040 M easured 1020

980 2001

1985

BJ NAR

1000

M LR NARX 2002

Year Study time frame (15 years)

Study time frame (35 years)

Electricity consumption (KWh)

Electricity consumption (KWh)

2005

NAR M LR NARX

550

1987

1988

1989

1300 1250

NAR M LR NARX

1200 1150 1100 2006

1990

M easured BJ

2007

2008

2009

2010

Year

Year Study time frame (20 years)

Study time frame (39 years)

800

1450 M easured BJ

Electricity consumption (KWh)

Electricity consumption (KWh)

2004

1350 M easured BJ

M LR NAR NARX

700

650

600 1991

2003

Year

650

750

2000

1100 M easured BJ

500 1986

1999

Study time frame (30 years)

540

600

1998

Year

Year

400 1981

407

1992

1993

Year

1994

1995

1400 M easured BJ NAR M LR 1350 2011

NARX 2012

2013

2014

Year

FIGURE 11.10 Simulation results under different study periods for a 5-year forecasting horizon.

408 PART | IX Smart grids

Forecasting time frame (20 years)

Forecasting time frame (5 years) M easured BJ 600

Electricity consumption (KWh)

Electricity consumption (KWh)

650

NAR M LR NARX

550

1100

M easured BJ

1000

NAR

900

M LR NARX

800 700 600 500

500 1986

1987

1988

1989

1990

1990

1995

Year

1400

700

NAR MLR

Electricity consumption (KWh)

Electricity consumption (KWh)

Measured BJ

NARX 650 600 550 500 1986

M easured BJ

1200

NAR

1000

M LR NARX

800

600 1988

1990

1992

1994

1985

1990

1995

Year

800

NARX

Electricity consumption (KWh)

Electricity consumption (KWh)

NAR M LR

700 600

1988

1990

1992

2005

2010

Forecasting time frame (30 years) 1500

M easured BJ

900

2000

Year

Forecasting time frame (15 years) 1000

500 1986

2005

Forecasting time frame (25 years)

Forecasting time frame (10 years) 800 750

2000

Year

1994

Year

1996

1998

2000

M easured BJ NAR M LR NARX

1000

500 1985

1990

1995

2000

2005

2010

Year

FIGURE 11.11 Simulation results for a 15-year study period under various forecasting horizons.

affected when the studied data history is limited to 5 years. These results reveal that the prediction horizon affects considerably the forecasting process, where performance is reduced for large prediction time frames. Furthermore, it is noticed that, among the four studied techniques, ARIMA models find it difficult to track the load pattern presenting the highest MAPE percentage for the majority of cases. Thus, it can be concluded that ARIMA models present the lowest performance compared to other techniques for the Tunisian dataset. As mentioned before, the critical points 1995 and 2005 are common to NAR and NARX techniques which leads to the assumption that these techniques need a larger number of data history samples to achieve satisfactory results. Consequently, to verify the validity of this assumption, NAR and

Long-term load forecasting Chapter | 11

409

NARX techniques are tested on a larger database with a total of 4544 samples [52]. The performance of these techniques is assessed for a 5-year and 10-year time frames. The simulation results for different studied cases for both techniques are presented by Fig. 11.12. Results analysis reveals that the number of samples has an important impact on the forecasting accuracy which is considerably affected for a limited data history. These findings may be justified by the fact that the dataset for such techniques is split in three parts: training, validation, and testing, and hence a larger number of samples is necessary to reach better performance. Therefore, the assumption of limited samples’ number is proven to be correct. Still, the NARX technique yields the best performance with a MAPE average value of 0.46% versus NAR technique, with a 0.57%. Furthermore, it is observed that the NARX technique has the potential to accurately forecast the changes in the load pattern for a long forecasting horizon up to 35 years. These outcomes support the results obtained for the Tunisian case. Table 11.4 summarizes the obtained results in terms of speed and accuracy for the different studied forecasting techniques. Table 11.3 shows that neural network-based techniques outperform other techniques considering accuracy and speed. Furthermore, it has been demonstrated that NARX technique presents the best performance with a MAPE of 0.58% and a speed of 5.2 s. However, the interpretation of this technique is still difficult as there is no explicit equation between the input and output variables. Still, its forecasting accuracy makes it a good candidate for long-term prediction. It can therefore be deduced that the econometric approach outperforms the time series approach. 5 years (NAR)

10 years (NAR)

5 years (NARX)

10 years (NARX)

3

MAPE (%)

2.5 2 1.5 1 0.5 0 5

10

15

20

25

30

35

Forecasting horizon

FIGURE 11.12 Simulation results for different forecasting horizon for the 5- and 10-year study periods for NAR and NARX.

410 PART | IX Smart grids

TABLE 11.4 Qualitative comparison of the studied techniques. Performance criterion

ARIMA

NAR

MLR

NARX

MAPE (%)

4.76

0.81

3.26

0.58

Speed (s)

25.18

7.14

7.74

5.2

7. Conclusion A comparative study of two different forecasting approaches, namely, the time series and the econometric one has been presented in this chapter. Considering data history period and forecasting horizon, two different techniques were examined for each approach. The ARIMA models and the NAR technique for time series approach, the MLR and the NARX techniques for the econometric approach. The study was performed on Tunisia’s electricity consumption from 1971 to 2014. The simulations revealed the existence of critical points after which prediction performance is severely degraded. These critical points were removed firstly by employing econometric approaches and then by expanding the dataset sample size to guarantee the reliability and performance of the various studied techniques. The findings of this study demonstrated that NARX technique outperforms other techniques for the different studied cases with regard to rapidity and precision. Moreover, it has been noticed that the presence of exogenous factors in the forecasting process yields better performance where econometric methods overcome the time series. In addition, it has been remarked that the number of the samples in the dataset has a significant effect on the prediction accuracy especially for ANN techniques. The outcomes of this study offer a valuable baseline for both current and future researches in the field of long-term prediction. This may be relevant for electric utility studies, aiming mainly to provide a continuous energy supply with the lowest cost.

References [1] T. Hong, P. Pinson, Y. Wang, et al., Energy forecasting: a review and outlook, IEEE Open Access J. Power Energy 7 (2020) 376e388. [2] M. Faheem, S.B.H. Shah, R.A. Butt, et al., Smart grid communication and information technologies in the perspective of Industry 4.0: opportunities and challenges, Comp. Sci. Rev. 30 (2018) 1e30. [3] G.R. Esteves, B.Q. Bastos, F.L. Cyrino, et al., Long term electricity forecast: a systematic review, Procedia Comput. Sci. 55 (2015) 549e558. [4] L. Xu, S. Wang, R. Tang, Probabilistic load forecasting for buildings considering weather forecasting uncertainty and uncertain peak load, Appl. Energy 237 (2019) 180e195.

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IEA, Perspectives E´nerge´tiques Mondiales, 2016. A. Al Mamun, M. Sohel, N. Mohammad, et al., A comprehensive review of the load forecasting techniques using single and hybrid predictive models, IEEE Access 8 (2020) 134911e134939. [7] D.W. Van der Meer, J. Wide´n, J. Munkhammar, Review on probabilistic forecasting of photovoltaic power production and electricity consumption, Renew. Sustain. Energy Rev. 81 (2018) 1484e1512. [8] L. Hernandez, C. Baladron, J.M. Aguiar, et al., A survey on electric power demand forecasting: future trends in smart grids, microgrids and smart buildings, IEEE Commun. Surv. Tutor. 16 (3) (2014) 1460e1495. [9] K.B. Lindberg, P. Seljom, H. Madsen, et al., Long-term electricity load forecasting: current and future trends, Util. Pol. 58 (2019) 102e119. [10] T. Hong, S. Fan, Probabilistic electric load forecasting: a tutorial review, Int. J. Forecast. 32 (3) (2016) 914e938. [11] S.R. Khuntia, J.L. Rueda, M.A. van der Meijden, Forecasting the load of electrical power systems in mid-and long-term horizons: a review, IET Gener., Transm. Distrib. 10 (16) (2016) 3971e3977. [12] B. Yildiz, J. Bilbaoa, A. Sproul, A review and analysis of regression and machine learning models on commercial building electricity load forecasting, Renew. Sustain. Energy Rev. 73 (2017) 1104e1122. [13] B. Nepal, M. Yamaha, A. Yokoe, T. Yamaji, Electricity load forecasting using clustering and ARIMA model for energy management in buildings, Jpn. Architec. Rev. 3 (1) (2020) 62e76. [14] J. Mi, L. Fan, X. Duan, Y. Qiu, Short-term power load forecasting method based on improved exponential smoothing grey model, Math. Probl Eng. 11 (2018). [15] J. Mohammed, S. Bahadoorsingh, N. Ramsamooj, C. Sharma, Performance of exponential smoothing, a neural network and a hybrid algorithm to the short term load forecasting of batch and continuous loads, in: 2017 IEEE Manchester PowerTech, 2017, pp. 1e6. [16] M.Q. Raza, A. Khosravi, A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings, Renew. Sustain. Energy Rev. 50 (2015) 1352e1372. ¨ zmen, G.W. Weber, Long-term load forecasting: models based on MARS, [17] G. Nalcaci, A. O ANN and LR methods, Cent. Eur. J. Oper. Res. 27 (4) (2019) 1033e1049. [18] D. Solyali, A comparative analysis of machine learning approaches for short-/long-term electricity load forecasting in cyprus, Sustainability 12 (9) (2020) 3612. [19] J.W. Taylor, Triple seasonal methods for short-term electricity demand forecasting, Eur. J. Oper. Res. 204 (1) (2010) 139e152. [20] S. Motepe, A.N. Hasan, R. Stopforth, Improving load forecasting process for a power distribution network using hybrid AI and deep learning algorithms, IEEE Access 7 (2019) 82584e82598. [21] S. Ramos, J. Soares, Z. Vale, S. Ramos, Short-term Load Forecasting Based on Load Profiling, in: Power and Energy Society General Meeting, PES), 2013, pp. 1e5. [22] M.R. Kazemzadeh, A. Amjadian, T. Amraee, A hybrid data mining driven algorithm for long term electric peak load and energy demand forecasting, Energy 204 (2020) 117948. [23] S. Sengar, X. Liu, Ensemble approach for short term load forecasting in wind energy system using hybrid algorithm, J. Ambient Intell. Hum. Comput. (2020) 1e18. [24] M.Y. AL-Hamad, I.S. Qamber, GCC electrical long-term peak load forecasting modeling using ANFIS and MLR methods, Arab J. Basic Appl. Sci. 26 (1) (2019) 269e282. [5] [6]

412 PART | IX Smart grids [25] L. Tang, X. Wang, X. Wang, et al., Long-term electricity consumption forecasting based on expert prediction and fuzzy Bayesian theory, Energy 167 (2019) 1144e1154. [26] https://data.worldbank.org/. Accessed 15 June 2021. [27] F.L. da Silva, F.L.C. Oliveira, R.C. Souza, A bottom-up bayesian extension for long term electricity consumption forecasting, Energy 167 (2019) 198e210. [28] J. Cederborg, S. Sno¨bohm, Is there a Relationship between Economic Growth and Carbon Dioxide Emissions?, 2016. [29] L. Ghods, M. Kalantar, Different methods of long-term electric load demand forecasting; a comprehensive review, Iran. J. Electr. Electron. Eng. 7 (4) (2011) 249e259. [30] J.P. Hermias, K. Teknomo, J.C.N. Monje, Short-term stochastic load forecasting using autoregressive integrated moving average models and Hidden Markov Model, in: 2017 International Conference on Information and Communication Technologies (ICICT), 2017, pp. 131e137. [31] A. Di Piazza, M.C. Di Piazza, G. Vitale, Solar and wind forecasting by NARX neural networks, Renew. Energy Environ. Sustain. (2016) 1e39. [32] R.A. de Marcos, A. Bello, J. Reneses, Electricity price forecasting in the short term hybridising fundamental and econometric modelling, Elec. Power Syst. Res. 167 (2019) 240e251. [33] M. Massaoudi, I. Chihi, L. Sidhom, et al., An effective hybrid NARX-LSTM model for point and interval PV power forecasting, IEEE Access 9 (2021) 36571e36588. [34] J. Jung, R.P. Broadwater, Current status and future advances for wind speed and power forecasting, Renew. Sustain. Energy Rev. 31 (2014) 762e777. [35] M.D. Toksarı, Ant colony optimization approach to estimate energy demand of Turkey, Energy Pol. 35 (8) (2007) 3984e3990. [36] E. Uzlu, M. Kankal, A. Akpınar, T. Dede, Estimates of energy consumption in Turkey using neural networks with the teachingelearning-based optimization algorithm, Energy 75 (2014) 295e303. [37] O. Ersel Canyurt, H. Ceylan, H. Kemal Ozturk, A. Hepbasli, Energy demand estimation based on two-different genetic algorithm approaches, Energy Sources 26 (14) (2004) 1313e1320. [38] F. Ardakani, M. Ardehali, Long-term electrical energy consumption forecasting for developing and developed economies based on different optimized models and historical data types, Energy 65 (2014) 452e461. [39] S. Tutun, C.-A. Chou, E. Canıyılmaz, A new forecasting framework for volatile behavior in net electricity consumption: a case study in Turkey, Energy 93 (2015) 2406e2422. [40] A. Azadeh, S. Ghaderi, S. Tarverdian, M. Saberi, Integration of artificial neural networks and genetic algorithm to predict electrical energy consumption, Appl. Math. Comput. 186 (2) (2007) 1731e1741. [41] A. Askarzadeh, Comparison of particle swarm optimization and other metaheuristics on electricity demand estimation: a case study of Iran, Energy 72 (2014) 484e491. [42] J. Wang, L. Li, D. Niu, Z. Tan, An annual load forecasting model based on support vector regression with differential evolution algorithm, Appl. Energy 94 (2012) 65e70. ¨ Zceylan, M. Gu¨Ndu¨Z, T. Paksoy, Swarm intelligence approaches to es[43] M.S. KıRan, E. O timate electricity energy demand in Turkey, Knowl. Base Syst. 36 (2012) 93e103. [44] H. Zhao, S. Guo, An optimized grey model for annual power load forecasting, Energy 107 (2016) 272e286.

Long-term load forecasting Chapter | 11 [45]

[46]

[47]

[48] [49]

[50] [51]

[52]

413

E.H. Nasab, M. Khezri, M.S. Khodamoradi, E.A. Gargari, An application of imperialist competitive algorithm to simulation of energy demand based on economic indicators: evidence from Iran, Eur. J. Sci. Res. 43 (2010) 495e506. Y. Wang, J. Wang, G. Zhao, Y. Dong, Application of residual modification approach in seasonal arima for electricity demand forecasting: a case study of China, Energy Pol. 48 (2012) 284e294. M.D. Toksari, A hybrid algorithm of ant colony optimization (ACO) and iterated local search (ILS) for estimating electricity domestic consumption: case of Turkey, Int. J. Electr. Power Energy Syst. 78 (2016) 776e782. X. Liu, J. Fang, Long-term load forecasting based on a time-variant ratio multiobjective optimization fuzzy time series model, Math. Probl Eng. 2013 (2013). ¨ zceylan, M. Gu¨ndu¨z, T. Paksoy, A novel hybrid approach based on particle M.S. Kıran, E. O swarm optimization and ant colony algorithm to forecast energy demand of Turkey, Energy Convers. Manag. 53 (1) (2012) 75e83. M. Amjadi, H. Nezamabadi-Pour, M. Farsangi, Estimation of electricity demand of Iran using two heuristic algorithms, Energy Convers. Manag. 51 (3) (2010) 493e497. Y. Amellas, O. El Bakkali, A. Djebli, A. Echchelh, Short-term wind speed prediction based on MLP and NARX networks models, Indones. J. Electr. Eng. Comput. Sci. 18 (1) (2020) 150e157. Https://www.nyiso.com/public/markets_operations/market_data/load_data/index.jsp, Accessed 15 June 2021.

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Chapter 12

A short review of grid voltage sags and current control techniques of voltage source inverters in distributed power generation systems Mohamed Hamdi1 and Mahmoud Hamouda2 1

Higher Institute of Technological Studies, Department of Electrical Engineering, Gafsa, Tunisia; Research Laboratory LATIS, National Engineering School of Sousse, University of Sousse, Sousse, Tunisia 2

1. Introduction In recent years, the penetration level of distributed power generation systems (DPGS) in the electrical networks is becoming more and more increased. For instance, the global installed capacity of PV generators reached 116.9 GW in 2019 with an increase of about 13% as compared to the year 2018 [1]. The massive installed power from DPGS and continuous change of network structure and characteristics have therefore led to the development of new grid codes which specify a set of requirements for the DPGS for normal and grid faults operations [2]. Fig. 12.1 illustrates a generic configuration of a DPGS. In most commonly used configurations, the active power is first transferred from distributed sources (photovoltaic park, wind farm, microturbine, etc.) to the dc bus. The power is thereafter injected into the grid through a three-phase voltage source inverter (VSI), the key element of the power conversion system. Note that for small-scale generation systems, the two-level topology is the most utilized where the power is injected into the low-voltage (LV) grid. This is because two-level VSIs require less power switches and also provide a good stability of the dc-bus voltage. As for the power levels in the multimegawatt range, the power injection is made directly in the medium voltage (MV) grid through multilevel and multicellular inverters [3]. Renewable Energy Production and Distribution. https://doi.org/10.1016/B978-0-323-91892-3.00012-1 Copyright © 2022 Elsevier Inc. All rights reserved.

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416 PART | IX Smart grids

FIGURE 12.1 Typical configuration of distributed sources connected to the grid through a threephase VSI.

In the steady-state operation of the distribution/transmission network, the DPGS are required to participate in the stabilization of the system in emergency situation such as frequency deviation resulting from generation/demand unbalance. Moreover, a high capability of reactive power regulation is mandatory for voltage stabilization. In the case of fault in distribution or transmission system, DPGS are subject to severe requirements commonly known as fault ride through (FRT) requirement [4e6]. The latter are needed to alleviate the impact of the disturbance which may lead to voltage collapse [7]. For instance, Fig. 12.2 shows the fault ride through (FRT) voltage profile issued by the ENTSO-E for the European countries. When a fault occurs, the depth of voltage sag may reach 95% of the rated voltage before being cleared by a protection tip within 0.14e0.25 s. After the fault clearance, the rated grid voltage must be recovered within 1.5e3 s. During this severe disturbance, the DPGS are required to remain connected to the electrical network. Moreover, they must help support the grid voltage by supplying a defined amount of reactive power depending on the sag severity [8]. Fig. 12.3 illustrates the reactive current profile (Iq) that should be injected into the grid during

U(pu) 1 0.85

0.05-0.15 0

0.14 - 0.25

1.5 - 3

t (sec)

Time fault occured

FIGURE 12.2 ENTSO-E FRT requirement for grid connection below 110 kV.

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417

Iq/Irated Dead Band 100%

20% 0

0.5

0.9 1 Grid voltage (pu)

FIGURE 12.3 Generic reactive current requirement versus grid voltage during fault.

faults. As can be seen, when the voltage drops below 50% of the rated, it is mandatory that only the reactive power must be supplied by the DPGS to the grid. This chapter provides in its first part a short review of voltage sags caused by grid faults where the possible grid faults (LG, LL, LLG, LLL, LLLG) and the six resulting voltage sags (A, B,.F) are discussed. The second part presents several voltage support strategies and provides a detailed explanation of the methodologies used to compute the appropriate references of the active and reactive powers injected by the VSI during the fault and postfault operation. The last part reviews the most popular current control methods of the VSI utilized as a power electronic interface between the DPGS and the grid. These current control methods developed to ride through voltage sags are classified in two main groups. The first group uses a PWM modulator to synthesize the appropriate voltage that should be synthesized at the inverter’s AC terminals. The second category eliminates the PWM modulator by applying only one switching state during the pulse period. A discussion of the performances of each control method is provided by the end of this chapter.

2. Grid faults and voltage sags characteristics A voltage sag event is a sudden reduction in the grid voltage’s magnitude at a point of the distribution network below a threshold value (generally 10% of the rated voltage), during a short period time (sag duration) ranging from half a cycle up to few seconds [9]. The main causes of voltage sags which may be balanced or unbalanced are: (1) symmetrical and asymmetrical short-circuits at a point of the electrical system, (2) earth faults, (3) starting of large induction motors and transformers energizing [10,11]. According to European standards EN 50160, the duration of voltage sags can be classified in four groups [12]: -

Short and shallow (up to few seconds and below 60%). Short and deep (up to few seconds and more than 60%). Long and shallow (above few seconds and below 60%). Long and deep (above few seconds and more than 60%).

418 PART | IX Smart grids

In practice, most of voltage sags are unbalanced giving rise to a negative sequence component in the grid voltage and a zero-sequence component. When a fault (caused by a short-circuit or earth fault) occurs at a certain point of the power system, the propagation phenomenon provides different voltage sags with different characteristics through the bus-bar or nodes at different locations within the system. In order to analyze and assess the voltage sags experienced by a VSI connected to a faulty grid, let us consider the power circuit of Fig. 12.4A where the VSI is connected to the grid through a three-phase transformer. Assume now a short-circuit occurring at a point F along the distribution line between phase a and the ground. An equivalent circuit is depicted in Fig. 12.4B where the power source and fault impedance seen from the PCC are named Z S and Z F , respectively. The voltages experienced by the PCC and fault point F are named VABC and Va’b’c’, respectively. The voltages Eabc provided by the power generator are assumed sinusoidal and balanced. Moreover, the currents iLa, Lb, Lc are much smaller than the fault current; therefore, they are assumed equal to zero i.e., iabc z ia0 b0 c0 0 . Since the short circuit occurred between phase a and the ground, therefore va0 ¼ 0. Moreover, since the current in the faulty phase ðia Þ is much larger than the one in phases b and c, therefore it is possible to neglect these currents ðib ¼ ic ¼ 0Þ without missing the generality of the analysis. Consequently the positive-, negative-, and zero-sequence components of the line current iabc are computed using Fortescue transformation matrix as follows: 2 3 2 32 3 þ 2 6 la 7 1 6 1 a a 76 ia 7 6 7 6 0 7; a ¼ exp j2p3 ; (12.1) 6 la 7 ¼ 6 1 a2 a 7 4 5 4 5 4 05 3 0 1 1 1 l a

which yields to 1 þ  0 la ¼ la ¼ la ¼ ia 3

(12.2)

(A)

FIGURE 12.4A Power circuit of a VSI connected to the grid through a three-phase transformer.

A short review of grid voltage sags Chapter | 12

419

(B)

FIGURE 12.4B Equivalent circuit based on grid fault analysis.

On the other hand, since Va0 ¼ 0, the positive-, negative-, and zerosequence voltage components at the fault point are computed as follows: 3 2 2 3 32 þ 2 V 0 1 a a 0 6 a 7 16 7 76 6 7 6 Vb 0 7 (12.3) 6 V a0 7 ¼ 6 1 a2 a 7 4 5 5 4 4 0 5 3 V c0 1 1 1 V a0 Since (1 þ a þ a2) ¼ 0, therefore the following relationship is deduced from Eq. (12.3) þ



V a0 þ V a0 þ V 0a0 ¼ 0

(12.4)

Based on Eqs. (12.2) and (12.4), it is possible to draw the interconnected sequence network as depicted in Fig. 12.5, where the generator provides only a þ  positive sequence voltage Ea i.e., Ea ¼ E 0a ¼ 0. Based on the circuit of Fig. 12.5 and using Kirchhoff laws, the positive-, negative-, and zero-sequence components of the unbalanced voltage sags experienced by the PCC are determined as follows: 2 3 2 3 þ V 6 A 7 16 2 þ d 7 þ 6 7 (12.5) 6 VA 7 ¼ 6 1 þ d 7 5E a 4 0 5 34 1 þ d VA where d is referred to as sag parameter defining a relationship between the line impedances at the source side and the fault side. Its expression is determined from the schema of Fig. 12.5 as follows: þ

d¼



0

ZF þ ZF þ ZF þ



0

3Z s þ Z F þ Z F þ Z F

(12.6)

420 PART | IX Smart grids

FIGURE 12.5 Sequence network interconnection for a single line-to-ground fault.

It is now possible to deduce from Eq. (12.5) and the Fortescue inverse transformation matrix the three phase voltages (V A , V B , and V C ) at the PCC such that 2 3 d 2 3 p ffiffi ffi 6 7 3 7 þ 1 6 VA 7 1 6 6 7  j  6 VB 7 ¼ 6 2 (12.7) Ea 2 7 4 5 36 pffiffiffi 7 4 5 VC 3 1  þj 2 2 In Eq. (12.7), the term d appear as the signature of the fault showing that only phase a is affected by the voltage sag of the studied example. The module of d defines the voltage sag severity, whereas its argument denotes the phase angle jump. The corresponding phasor diagram is depicted in Fig. 12.6A, where the argument of d is assumed equal to zero. Such a voltage sag is classified as type B where only the voltage amplitude of the corresponding faulty phase is decreased. On the other hand, the voltage sags as experienced by the VSI V a , V b , and V c (secondary side of the transformer) are determined from  the symmetrical  þ



0

components generated at the secondary side V a ; V a ; V a . Assume a delta/

star connection of the transformer; therefore, the zero-sequence voltage component is equal to zero. Moreover, according to ANSI/IEEE standard [13], the positive/negative sequence of the phase-to-neutral voltage at the low-

A short review of grid voltage sags Chapter | 12

421

(A)

FIGURE 12.6A Phasor diagram showing the voltages at the PCC corresponding to phase a to ground fault.

voltage side has a phase shift equal to 30 degrees/þ30 degrees with respect to the positive/negative sequence at the high-voltage side such that 8 þ þ > jp=6 > > < V a ¼ mV A exp 



V a ¼ mV A exp jp=6 > > > : V0 ¼ 0 a

(12.8a)

m is the voltage ratio of the transformer. þ  Substituting now V A and V A by their expressions computed in Eq. (12.5) yields 8 >  þ jp 1  > þ > > V a ¼ m 2 þ d Ea exp 6 > > 3 > <  þ 1   (12.8b) V a ¼ m  1 þ d Ea exp jp=6 > > 3 > > > > > : V0 ¼ 0 a

Using the Fortescue inverse transformation matrix defined by Eq. (12.8c), one can deduce the voltage sags experienced by the VSI as shown in Eq. (12.8d) 32 3 2 3 2 þ 1 1 1 V 76 a 7 6 Va 7 6 2 76 V 7 6 Vb 7 ¼ 6 a a 1 (12.8c) 54 a 5 4 5 4 2 Vc a a 1 0

422 PART | IX Smart grids

2

3

2

3  jp=6  d exp 2 þ 7 76   jp=6 7E þ 6 17 5 a 54  1 þ d exp 0 1 32

1

6 Va 7 1 6 2 6 V b 7 ¼ m6 a 4 5 3 4 Vc a

1 a a2

1

(12.8d)

The corresponding phasor diagram is illustrated in Fig. 12.6B where the voltages V a , V b , and V c caused by the grid fault and computed in Eq. (12.8c and 12.8d) are named V sag a , V sag b , and V sag c to avoid confusion with the voltages before the faults V a , V b , and V c . One can clearly observe that the voltage sag is transformed from type B (at PCC) to type C (experienced by the VSI) due to the deltaestar connection of the transformer. The study made in the above example can be generalized for the remaining types of grid faults i.e., line-to-line (LL), two lines to ground (LLG), three lines (LLL) and three lines to ground faults (LLLG). The characteristic parameters (sag type, sag severity, etc.) of the voltage sags experienced by the VSI for each fault are summarized in Table 12.1. Vmin denotes the lowest voltage amplitude among the three phases. The phasor diagrams of the different voltage sags [14] found in Table 12.1 and experienced by the VSI are depicted in Fig. 12.7. It is worth mentioning that the voltage sag severity can also be characterized by the voltage unbalance factor defined as follows [15]: n¼

V Vþ

(12.8e)

V  and V þ are the magnitude of the negative- and positive-sequence components, respectively. To evaluate the parameter n, consider again the above example that corresponds to an LG fault. Assume also that the positive-, negative-, and zero-sequence fault impedances are equals

(B)

FIGURE 12.6B Phasor diagram showing the voltage sag experienced by the VSI and corresponding to phase a to ground fault occurring at the PCC. Vsag a, Vsag b, and Vsag c refer to the voltages after the grid fault namely Va, Vb, and Vc in Eq. (12.8c and 12.8d). The voltages Va, Vb, and Vc in this figure refer to voltages before the fault.

A short review of grid voltage sags Chapter | 12

423

TABLE 12.1 Characteristics and propagation of voltage sags.

FIGURE 12.7 Phasor diagram of different voltage sags classified from “A” to “F” experienced by the VSI.

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  þ  0 Z F ¼ Z F ¼ Z F ¼ Z F . Therefore, the expression of d computed in Eq. (12.6) becomes d¼

ZF ZS þ ZF

(12.9)

Considering now that the phase angle of d is equal to zero, in this case, the real number d reflects the voltage sagging severity and ranges from 0 (when a fault is occurred just at the terminal of VSC, ZF ¼ 0Þ to 1 (when the fault location is more and more far away from the connection point of the transformer, ZF [ZS Þ. Based on the above considerations, the voltage unbalance factor in the case of LG fault is deduced from Eq. (12.5) as follows: nLG ¼

V  1 þ d ¼ 2þd Vþ

(12.10)

Fig. 12.8 depicts the variation the voltage unbalance factor n versus d for the case of LG fault according to Eq. (12.10) and also for LL and LLG faults. It can be concluded that LG fault is less severe than LL and LLG faults in term of the magnitude of negative sequence voltage. One can also observe that the LG fault produces the same shape as the LLG fault when the grid fault location is far away from the connection point of the transformer.

FIGURE 12.8 Variation of voltage unbalance factor versus d for LG, LLG, and LL grid faults.

A short review of grid voltage sags Chapter | 12

425

3. Voltage support concept and strategies to determine active and reactive power injected by the VSI during the fault and postfault operation In the previous section, it has been shown that the fault in some points of the power system generally results in the appearance of unbalanced voltage sags experienced by the VSI. This voltage sag may cause the following problems: - If the duration and amplitude of the sags are beyond the tolerated limit, the VSI will be disconnected from the grid due to the tripping of the undervoltage protection breakers. This phenomenon may lead to grid instability due to a decrease of the injected active power after the clearance of the fault. - Transient overcurrent peaks circulating through the inverter. This causes excessive heating of power semiconductors and may lead to their failure. Notice that VSIs are able to generate 1e2 p.u. fault current upon the capability of their semiconductor devices. - The unbalanced grid voltage sags give rise to significant active and reactive power oscillations. Notice that the active power oscillations cause unwanted fluctuation in the dc-bus voltage and may affect the inverter’s reliability. On the other hand, a significant reactive power oscillation would cause an undesirable fluctuation of the voltage experienced by the VSI. Therefore, it is very important to determine the appropriate amount of active and reactive powers to be injected by the VSI to mitigate the undesirable effects of voltage sags [16e18]. Moreover, since the VSI operates as a current source converter, therefore, we shall deduce the references of the currents injected by the VSI into the grid ig-abc. The computation of the powers’ and currents’ references should basically address the low-voltage ride through (LVRT) requirement imposed by grid codes. Up to this date, the existing grid codes only focus on voltage support problem by requesting the VSI to remain connected to the griddif the fault duration is under a specified limitdand inject an appropriate amount of active/ reactive power during the fault and postfault operation. This amount depends on the grid impedance and the amplitude of the voltage experienced by the VSI. The following subsections will provide a review of two strategies for the formulation of the appropriate references of the injected power to support the grid voltages during the fault and postfault operation.

3.1 Power injection in case of purely inductive grid impedance: voltage support oriented strategy proposed in Ref. [19] The strategy proposed in Ref. [19] was developed with the aim to help boost the grid voltage, i.e., support the grid voltage and limit the amplitude of the current injected by the VSI to the rated value. For the sake of simplicity, the power circuit of Fig. 12.9 is used to explain the strategy.

426 PART | IX Smart grids

FIGURE 12.9 Simplified power circuit of a VSI connected to the grid.

3.1.1 Voltage support concept in case of purely inductive grid impedance The voltage support concept presented in this section is based on the assumption that the grid impedance is purely inductive, i.e., Lg u[Rg , where u is the grid velocity. Only positive and negative sequences of the reactive þ  power are injected during the fault and postfault operation. Define ð V ; V Þ, þ  þ  ðV g ; V g Þ, and ðI g ; I g Þ as the phasors of the positive and negative sequences of the grid voltages at the PCC, the grid voltages, and the injected currents, respectively. The equivalent phasor diagram deduced from the power circuit of Fig. 12.9 is constructed as shown in Fig. 12.10, where fþ and f are the initial phases of positive and negative sequences of voltages at the  PCC. In this diagram, the positive sequence of the reactive current  (I g )



þ

Ig

leads V

þ

by 90

degrees. Moreover, its negative sequence lags V by 90 degrees. Accordingly, the amplitudes of positive and negative sequences of the voltages experienced by the inverter (Vþ, V) during the fault and postfault

þ

þ

FIGURE 12.10 Phasor diagram deduced from the power circuit of Fig. 9 where I g leads V by   90 degrees and I g lags V by 90 degrees.

A short review of grid voltage sags Chapter | 12

427

  operation can be expressed as a function of the grid voltages, Vgþ ; Vg and   injected currents Igþ ; Ig as follows: (

V þ ¼ Vgþ þ uLg Igþ V  ¼ Vg  uLg Ig

(12.11)

On the other hand, define Qþ and Q as the positive and negative sequences of the injected reactive power such that 8 3 þ þ > þ > < Q ¼ V Ig 2 (12.12) > > : Q ¼ 3V  Ig 2 Substituting (12.12) into (12.11) yields 8 2 Qþ > þ þ > < V ¼ Vg þ uLg þ 3 V  > 2 Q >  : V ¼ Vg  uLg  3 V

(12.13)

Eq. (12.13) explains clearly the concept of voltage support with a purely inductive grid. Indeed, to boost the voltage experienced by the VSI and avoid the tripping of the undervoltage protection breakers, we shall - Inject an appropriate amount of the positive sequence of reactive power ðQþ Þ to increase the amplitude of the positive sequence of the voltage at the PCC ðV þ Þ. - Inject an appropriate amount of the negative sequence of reactive power ðQ Þ to decrease the amplitude of the negative sequence of the voltage at the PCC ðV  Þ. Notice that the flexible boost of V þ and decrease of V  is achieved by injecting only reactive power into the grid since its impedance is assumed to be purely inductive.

3.1.2 Constraints and formulation of the references of the injected reactive power and grid current The positive and negative sequences of the reactive power Qþ, Q are determined to satisfy the following two constraints: Constraint 1: The flexible control of V þ and V  should be performed by maintaining the amplitude of the phase voltages at the PCC above the tolerated minimum amplitude Vmin and under the maximum safety amplitude Vmax . In other words, we shall determine Qþ and Q such that minfVa ; Vb ; Vc g  Vmin and max fVa ; Vb ; Vc g  Vmax

(12.14)

where Va ; Vb , and Vc are the amplitudes of va ; vb , and vc , respectively.

428 PART | IX Smart grids

Constraint 2: The voltage support in stiff grid require a high value of the reactive current. However, the amplitude of this current should not exceed the inverter’s power semiconductors capability, i.e.,   (12.15) max Iga ; Igb ; Igc  Imax where Iga ; Igb , and Igc are the amplitudes of the injected currents. Imax is the maximum safety current tolerated by the inverter. 3.1.2.1 Resolving of constraint 1’s requirement To fulfill the requirement of constraint 1, define the expressions of the voltages at the PCC in the ab reference frame: 8 þ þ þ < va ¼ V cosðut þ f Þ   (12.16a) : vþ ¼ V þ cos ut  p þ fþ b 2 8  þ  < va ¼ V cosðut  f Þ   (12.16b) : v ¼ V þ cos ut þ p  fþ b 2     þ  are the positive and negative sequences of the where vþ and v a ; vb a ; vb voltage experienced by the VSI at the PCC and expressed in the ab reference frame. The amplitude of the phase voltages can therefore be determined by applying the inverse Clark transformation to Eq. (12.16a) and (12.16b) which yields 8 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi > 2 > > Va ¼ ðV þ Þ þ ðV  Þ2 þ 2V þ V  cos f > > > > sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi >

> > 2p < 2 Vb ¼ ðV þ Þ þ ðV  Þ2 þ 2V þ V  cos f  (12.17) 3 > > > sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi > >

> > 4p > þ 2  2 þ  > > : Vc ¼ ðV Þ þ ðV Þ þ 2V V cos f  3 where f ¼ fþ  f is the phase angle jump between the phase voltages. Define 



8 2p 4p > > < x ¼ max cos f; cos f  3 ; cos f  3 (12.18) 



> > : y ¼ min cos f; cos f  2p ; cos f  4p 3 3

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429

Therefore, the maximum and minimum amplitudes of the phase voltages could be determined as follows: qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 (12.19a) maxfVa ; Vb ; Vc g ¼ ðV þ Þ þ ðV  Þ2 þ 2V þ V  x minfVa ; Vb ; Vc g ¼

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 ðV þ Þ þ ðV  Þ2 þ 2V þ V  y

(12.19b)

From Eq. (12.19a)e(12.19b) we can determine the appropriate references of the positive- and negative-sequences amplitudes (V ref þ , V ref  ) that satisfy constraint 1. Indeed, substituting Eq. (12.19a)e(12.19b) into (12.14) and replacing ðV þ ; V  Þ by (V ref þ , V ref  ) yields ffi qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  2  2 V ref þ þ V ref  þ 2V ref þ V ref  x  Vmax (12.20a) ffi qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2  2  V ref þ þ V ref  þ 2V ref þ V ref  y  Vmin

(12.20b)

Resolving (Eq. 12.20ae12.20b) into V ref þ and V ref  yields vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u u xV 2 þ yV 2  þ yV 2  xV 2 2  V 2  V 2 2 t min max max min max min V ref þ ¼ 2ðx  yÞ

V ref 

(12.21a) vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi q u u xV 2 þ yV 2   yV 2  xV 2 2  V 2  V 2 2 t min max max min max min ¼ 2ðx  yÞ (12.21b)

Eq. (12.21a) and (12.21b) allow therefore to determine the appropriate amounts of injected reactive power. Indeed, from Eq. (12.13) we can deduce the references of the reactive power positive and negative sequences (Qref þ and Qref  ) as a function of V ref þ and V ref  as follows:   V ref þ V ref þ  Vgþ 3 (12.22a) Qref þ ¼ 2 uLg   ref  ref   V  V V g 3 Qref  ¼  (12.22b) 2 uLg The reactive power references determined in Eq. (12.22a and 12.22b) allow therefore to boost the positive sequence of the voltage amplitude at the PCC and reduce its negative-sequence amplitude while respecting the requirement of constraint 1.

430 PART | IX Smart grids

3.1.2.2 Resolving of constraint 2’s requirement Similarly to Eq. (12.17), the theoretical amplitudes of the injected phase currents could be estimated using Eq. (12.23) hereafter: rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi  2  2 8 þ  þ  I ¼ I g þ I g þ 2I g I g cos fI > > > ga > > > sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi >

ffi >  2  2 < 2p þ  þ  Igb ¼ I g þ I g þ 2I g I g cos fI  (12.23) 3 > > > > sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi > >

ffi >  þ 2  2 > 4p :  Iþ þ I þ 2I þ Igc ¼ g g g I g cos fI  3 Igþ and Ig are estimated with (12.12), where Qþ and Q are replaced by Qref þ and Qref  computed in Eq. (12.22a and 12.22b). Moreover, since the grid impedance is assumed to be purely inductive, therefore fI ¼ p  f. Therefore, the reactive power references computed in Eq. (12.22a and 12.22b) are applied only if the amplitudes of the estimated current in (12.23)  fulfill the requirement of constraint 1, i.e., max Iga ; Igb ; Igc  Imax . If the estimated current amplitudes are higher than Imax , therefore, the reactive power references are limited to the following saturation values: þ ref þ Qref sat ¼ Q

I  max  max Iga ; Igb ; Igc

(12.24a)

 ref  Qref sat ¼ Q

Imax  max Iga ; Igb ; Igc

(12.24b)



Since the VSI is viewed from the grid as a current source, therefore we should provide the current references as control inputs. The instantaneous references for the VSI current control loops are computed as a function of the positive and negative sequences of the reactive and expressed in the ab reference frame as follows: " # 8 Vbþ Vb > 2 > ref ref þ ref  > iga ¼ þ    2 Q  2  2 Q > > 3 > > Vaþ þ Vb Vaþ þ Vbþ < " # (12.25) > > 2 Vaþ Va > ref ref þ ref  > > i ¼   2  2 Q þ    2 Q > > gb 3 : Vaþ þ Vb Vaþ þ Vbþ

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3.2 Power injection in case of resistive-inductive grid impedance: voltage supporteoriented strategy proposed in Ref. [20] 3.2.1 Voltage support concept in case of resistiveeinductive grid impedance In case of resistiveeinductive grid impedance, i.e., the grid resistance is not negligible, both active and reactive powers are injected during the fault and  postfault operation. Define I  gp and I gq as the phasors of the equivalent injected active and reactive currents, respectively. The latter are decomposed into positive and negative sequences as follows: þ



þ



I gp ¼ I gp þ I gp

(12.26)

I gq ¼ I gq þ I gq þ

(12.27)



I gp and I gp are the positive and negative sequences, respectively, of the active þ



þ



current. I gq and I gq are their reactive counterpart. I gp and I gp are in phase with þ



þ

þ

their respective grid voltages at the PCC V and V . I gq leads V by 90   degrees and I gq lags V by 90 degrees. The corresponding phasor diagram equivalent to the power circuit of Fig. 12.9 is therefore depicted in Fig. 12.11 hereafter.

FIGURE 12.11 Phasor diagram deduced from the power circuit of Fig. 9 with a resistivee inductive grid and injection of active and reactive currents.

432 PART | IX Smart grids

The amplitudes of the positive and negative sequences of the voltages experienced by the inverter (V þ , V  ) during the fault and postfault operation are therefore expressed as follows: rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2  2  8 þ þ þ þ þ þ V ¼ R I þ uL I þ þ uL I  R I V g g g g < gp gq g gp gq (12.28) ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi r :       V  ¼ Rg Igp  uLg Igq þ

V g

2

  uLg I  gp þ Rg I gq

2

Define ðPþ ; P Þ and ðQþ , Q Þ as the positive and negative sequences of the injected active and reactive powers, respectively. The latter are expressed as a function of the active and reactive currents amplitudes as follows: 8 3 þ þ > þ > < P ¼ V Igp 2 (12.29) > >  : P ¼ 3V  Igp 2 8 3 þ þ > þ > < Q ¼ V Igq 2 (12.30) > >  : Q ¼ 3V  Igq 2 Substituting (12.29) and (12.30) into (12.28) yields sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 8  2 2 2  >   2 2 > þ þ þ > > V R þ uLg Pþ  Rg Qþ ¼ P þ uL Q  Vþ g g > g þ þ < 3V 3V s ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi > >  2 2 2  >  2 2  >    >  uLg P þ Rg Q V : V ¼  Rg P  uLg Q þ g 3V 3V  (12.31) According to (12.31), the voltage support can be performed with three different strategies. Strategy 1: Inject only positive sequences of the active and reactive powers to increase the amplitude of the positive sequence of the voltage experienced by the inverter (Vþ). Strategy 2: Inject only negative sequences of the active and reactive powers to decrease the amplitude of V. Strategy 3: Inject both sequences (positive and negative) of the active and reactive powers to maximize the difference between Vþ and V. For the sake of simplicity, this chapter will provide a detailed description of only strategy 1.

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433

3.2.2 Objectives and optimal formulation of the references of the injected powers and grid current under strategy 1 Under strategy 1, the positive sequences of the active and reactive powers (Pþ, Qþ) are determined to satisfy the following two objectives: Objective 1: Maximize the amplitude of the positive sequence of the voltage experienced by the VSI (Vþ) through an appropriate injection of only positive sequence of active and reactive powers. This objective can be solved using the upper part of Eq. (12.31) i.e., sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  2 2 2   2 2  þ þ þ V ¼ þ Rg P þ uLg Q þ  uLg Pþ  Rg Qþ Vþ g þ 3V 3V (12.32) Objective 2: Inject the maximum rated current of the inverter. Since only positive sequence of the grid current is injected, therefore the amplitude of the negative sequence Ig is equal to zero. The amplitude of the positive sequence Igþ is therefore deduced from its active and reactive components as follows: rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi     Igþ ¼

Iþ gp

2

þ Iþ gq

2

Substituting, (12.29) into (12.33) yields qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 2 2 Igþ ¼ þ ðPþ Þ þ ðQþ Þ 3V

(12.33)

(12.34)

Therefore, the theoretical amplitudes of the injected phase currents are computed in a similar manner as given in (12.23) and setting Ig to zero which yields qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 2 2 Iga ¼ Igb ¼ Igc ¼ þ ðPþ Þ þ ðQþ Þ (12.35) 3V Eq. (12.35) clearly shows that by injecting only positive sequences of the active and reactive powers, we provide balanced phase currents. Moreover, the objective 2 can be achieved by setting Iga ¼ Igb ¼ Igc ¼ Imax where Imax is the maximum rated current of the inverter. The optimal solution of the problem defined by the aforementioned two objectives can be determined using the Lagrange multiplier. For this purpose, define the following Lagrange function: LðPþ ; Qþ ; lÞ ¼ f ðPþ ; Qþ Þ þ lgðPþ ; Qþ Þ

(12.36)

f ðPþ ; Qþ Þ is the objective function extracted from (12.32) i.e., f ðPþ ; Qþ Þ ¼ V þ ðPþ ; Qþ Þ

(12.37)

434 PART | IX Smart grids

l is the Lagrange multiplier. gðPþ ; Qþ Þ is a restriction extracted from (12.35) i.e., qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 2 2 gðPþ ; Qþ Þ ¼ þ ðPþ Þ þ ðPþ Þ  Imax (12.38) 3V Once the gradient with respect to Pþ , Qþ , and l is obtained, the optimal solution to this problem is obtained by equaling the gradient to zero: VLðPþ ; Qþ ; lÞ ¼

vL vL vL ¼0 þ þþ þ vP vQ vl

(12.39)

Solving (12.39) into Pþ and Qþ yields the optimal references of the active and reactive powers: 3 Rg Pref þ ¼ V þ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 Imax  2  2 Rg þ uLg

(12.40a)

3 uLg Qref þ ¼ V þ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 Imax  2  2 Rg þ uLg

(12.40b)

The power references in Eq. (12.40a and 12.40b) satisfy the two objectives of maximizing the amplitude of the positive sequence of the voltage experienced by the VSI and the injecting a maximum current equal to the inverter’s rated current. The appropriate references of the currents injected into the grid can therefore be deduced from the determined power references. The expression of the injected active and reactive currents in the ab reference frame is given as follows: 8 ref ref < iref ga ¼ igað pÞ þ igaðqÞ (12.41) : iref ¼ iref þ iref gb gbð pÞ gbðqÞ with

" # 8 > 2 Vaþ > ref ref þ > igað pÞ ¼ >  2 P > > 3  þ 2 > þ Vbþ V > a > > > > " # > > þ > V > 2 b ref > ref þ > igbð pÞ ¼  2 P > > 3  þ 2 > þ > Va þ Vb < " # > þ > V 2 > b ref ref þ >i >  2 Q > gaðqÞ ¼ 3   > þ 2 > > V þ Vbþ > a > > > > # " > > > 2 Vaþ > ref ref þ > igbðqÞ ¼ >  2 Q > > 3  þ 2 : Va þ Vbþ

(12.42)

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435

iref and iref are the a and b components, respectively, of the active current gað pÞ gbð pÞ . and iref are their reactive counterpart. iref gaðqÞ gbðqÞ

4. Current control methods 4.1 Control principle The explanation of the control strategies introduced in this section relies on the expended power circuit of a grid-connected VSI shown in Fig. (12.12). The main objective of a current control strategy is to determine the appropriate voltages at the VSI’s terminals (vinva, vinvb, and vinvc) to enable a perfect and fast tracking of the current references computed in the previous section. The computed voltages also referred to as control laws could be synthesized using either a PWM modulator or by applying only one switching state during the overall pulse period. The following subsections provide a description of three popular current control techniques for grid-connected VSI.

4.2 Voltage oriented control technique in a double dq synchronous reference frame The voltage-oriented control method performed in a double dq reference frame has been widely implemented to control grid-connected converters under unbalanced grid faults [21,22]. A generalized block diagram of this control method is depicted in Fig. 12.13. The (þ)/() sequence of the voltages at the PCC and grid currents are reported into two dq reference frames syn chronized with the components vþ d and vd respectively (block diagram within rectangle 1).  is all currents and voltages  The main advantage of this transformation þ  þ  þ   vþ d ; vd ; vq ; vq ; iinva ; iinvb , igd ; igd ; igq and igq become DC quantities that can

be controlled with PI compensators. Consequently four current control loops

FIGURE 12.12 Conventional power circuit of a grid connected VSI operating as current source.

436 PART | IX Smart grids

FIGURE 12.13 Block diagram of the VOC technique implemented in a double dq synchronous reference frame.

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437

are implemented in the (þ) and () reference frames as illustrated in the block diagram 2. The input of theses loops refer within rectangle   are the currents  þ ref þ  ref  ences iref for the (þ) sequence loops and iref for the () gd ; igq gd ; igq

sequence loops. These references are deduced from those computed in the previous section in the ab reference frame by simply transferring them into the double dq rotating frame. The outputs are the of the    (þ) and () sequences voltages across the inverter’s poles namely

þ vþ invd ; vinvq

and

 v invd ; vinvq .

The obtained control laws are thereafter transformed into the stationary ab reference frame to obtain vinva and vinvb as shown on the right hand part of rectangle 2. Thereafter, the three-phase voltage system vinva ; vinvb , and vinvc is deduced through an ab to abc transformation as shown in block diagram within rectangle 3. These target voltages at the inverter’s terminals are applied to the input of a PWM modulator to provide the appropriate gates pulses of the VSI power semiconductors as illustrated in the block diagram within rectangle 3. Note that the control loops are in general based on conventional PI compensators and must include also a decoupling between the dynamics of the d and q components of the grid currents. This control strategy provides satisfactory performance in steady-state operation and for steps changes of reference values. However, its dynamic response is not fast enough to withstand serious grid faults and prevent unacceptable over currents particularly in the case of high-power medium voltage applications with low switching frequency. This is mainly due to the following causes: - The narrow bandwidth of the PI controllers. - The low frequency of carrier signals in medium power low-voltage applications. - The use of a large value for the input filter inductor and the low-pass filters (LPF) to extract the (þ) and (þ) sequences of the grid currents reduces the bandwidth of the overall system and consequently slows down its dynamic response.

4.3 Voltage oriented control in the ab stationary reference frame A variety of control methods applied to DPGS were designed in the (a,b) stationary reference frame where the current references are inherently AC signals. Proportional Resonant (PR) controllers are considered among the most suitable alternatives for current control in stationary reference frames. They provide the same transient and steady-state performance as conventional PI controllers (implemented in synchronous reference frame) while avoiding Park transformations. In fact, they introduce an infinite gain at a selected resonant frequency which allows eliminating the steady-state error at that frequency [23,24].

438 PART | IX Smart grids

Many control methods based on PR controllers were proposed in recent literature to ride through voltage sags. Some of these control methods are based on the symmetrical sequences method [25]. However, in these research works, the voltage support control was not well explored. This issue was addressed in Refs. [26,27] where two voltage support control schemes were proposed to enable both positive-sequence voltage recovery and negativesequence voltage reduction. In Ref. [19] the authors proposed a reactive power control method where (þ) and () sequences of the reactive power were combined to flexibly regulate phase voltages at the PCC. None of the previous methods considered the transient current issue. Until present, few research works based on PR controllers were interested in the mitigation of overcurrent during the fault. In this paragraph, a typical PR-based current control scheme will be explained (Fig. 12.14) with the aim to help the reader understand the principle of such a control method established in a stationary reference frame. The grid voltages va,b,c and currents iga,gb,gc are first reported in a (a,b) stationary reference frame as shown in the block diagram within rectangle 1 of Fig. 12.14. Therefore two PR-based current controllers are implemented in the (a,b) reference frame to compute the appropriate poles voltages vinva and vinvb that enable the grid currents iga and igb to track their target references iref ga and iref gb (block diagram within rectangle 2). The computed control laws vinva and vinvb are thereafter transformed in to the abc reference frame. Finally, the obtained target voltages vinva ; vinvb , and vinvc at the inverter’s terminals are sent to the input of a PWM modulator to provide the appropriate gates pulses of the power switching devices as illustrated in the block diagram within rectangle 3. It is worth mentioning that PR current controllers are suitable for steadystate operation of power converters operating under unbalanced grid voltages. However, they also suffer from several drawbacks such as their slower dynamic response making them unsuitable to withstand serious grid faults. They are also vulnerable to slight grid frequency variations and errors in discrete models of the PR controllers.

4.4 Finite control set model predictive control The model predictive control (MPC) also referred to as Receding Horizon Control uses the model of the system to forecast its future behavior over a finite horizon. This information is thereafter used to compute the optimal control action, which fills a predefined optimization criterion [28]. The MPC technique can also be applied to control nonlinear systems without requiring a complex linearization procedure. Among a variety of possible MPC strategies, the finite-control set model predictive control (FCS-MPC) also referred to as

A short review of grid voltage sags Chapter | 12

FIGURE 12.14 Block diagram of the VOC in a stationary ab reference frame.

439

440 PART | IX Smart grids

direct MPC is particularly attractive for power converters and drives. Indeed, this control method determines directly the optimized switching states of the converter without the need of any modulation stage. Moreover, owing to the finite set of the feasible switching states of the power converter, the optimization problem is reduced to the selection of only one switching state that minimizes a predefined cost function [29e32]. Basically, the FCS-MPC is implemented in the discrete time domain. Its operation principle with the two-level VSI is described by the block diagram of Fig. 12.15. It is implemented through the following steps with the aim to determine the appropriate switching state of the VSI that minimizes a predefined cost function J.

FIGURE 12.15 Block diagram of the FCS-MPC algorithm.

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441

1. Define the cost function J(k). Basically, this cost function is chosen to minimize the quadratic error between the grid currents and their references such that  2  2 ref JðkÞ ¼ iref ðk þ 1Þ i ðk þ 1Þ þ i ðk þ 1Þ i ðk þ 1Þ (12.43) ga gb ga gb Notice that additional performance criteria could be added in this function such as the minimization of the common mode voltage (CMV) for transformer less grid-connected inverters. 2. Compute the appropriate references of the grid currents iref ga ðk þ1Þ and iref gb ðk þ1Þ for the sampling time (k þ 1). 3. Measurement of the grid currents and voltages at the PCC iga ðkÞ, igb ðkÞ, va ðkÞ, and vb ðkÞ at the actual sample time (k). 4. From each possible switching state of the two-level VSI shown in Table 12.2, we predict the ab components of the grid currents at the sample time (k þ 1) using the following equation based on the discrete model of the VSI:

 3 2 R Ts " # iga ðkÞ 1  Ts þ ðvinva ðkÞ va ðkÞÞ L L 7 6 iga ðk þ 1Þ 7 (12.44) ¼6

 5 4 igb ðk þ 1Þ R Ts igb ðkÞ 1  Ts þ ðvinvb ðkÞ vb ðkÞÞ L L where Ts is the sample period, R and L are the input filter resistance and inductance, respectively.

TABLE 12.2 Eight possible switching states of the VSI and the corresponding poles voltages vinva ðkÞ and vinvb ðkÞ. Switching state S11 S21 S31

vinva ðkÞ

vinvb ðkÞ

OFF OFF OFF

0

0

ON OFF OFF

ð2=3Þ vdc pffiffiffi ð1= 3 Þvdc pffiffiffi ð1= 3 Þvdc

0

0

ON OFF ON

ð 2=3Þvdc pffiffiffi ð1= 3 Þvdc pffiffiffi ð1= 3 Þvdc

ON ON ON

0

0

ON ON OFF OFF ON OFF OFF ON ON OFF OFF ON

ð1 =3Þvdc ð1 =3Þvdc

ð1 =3Þvdc ð1 =3Þvdc

442 PART | IX Smart grids

TABLE 12.3 Main features of the control methods. Current control techniques VOC in a double dq synchronous reference frame

Advantages

Drawbacks

-

High performance in steadystate operation and for steps changes of reference values Control flexibility of current components

-

Ease of implementation High performance in steadystate operation and for steps changes of reference values

-

Ease of implementation Fast dynamic response to mitigate current peaks

-

VOC in the stationary ab reference frame

-

FCS-MPC

-

-

-

-

Complexity of implementation Slow dynamic response during serious grid faults Slow dynamic response during serious grid faults Sensitivity to grid frequency variations and discretization errors for real-time implementation Larger computational effort to obtain the optimal control action Fragility to system’s parameters variation Variable switching frequency operation

5. For the eight predicted values of the grid currents computed in the former step we compute the cost function J given in Eq. (12.43). Thereafter we choose the switching state that provides the optimal value of J. This switching state is applied at the next sample time, i.e., (k þ 1). We deduce also the poles voltages vinva ðkÞ and vinvb ðkÞ that will be used in Eq. (12.44) to predict the grid currents iga ðk þ1Þ and igb ðk þ1Þ for the next iteration of the algorithm. Notice that the FCS-MPC is suitable for the control of VSI under grid voltage sags because of its fast dynamic response due to the use of only one switching state, i.e., it avoids the slow dynamic response caused by the pwm modulator. However, this technique needs an important computation effort to determine the optimal switching state; it is also vulnerable to the variation of the system’s parameters. Table 12.3 hereafter summarizes the main features of the three current control methods reviewed in this chapter.

5. Conclusion This chapter provided a detailed review of different voltage sags caused by grid faults and several voltage support strategies. It reviewed also three current

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control techniques developed with the aim to meet fault ride through requirements. The main features of the reviewed control methods including their advantages and drawbacks have been also discussed. It is certain that the FCSMPC is the most appropriate current control technique to mitigate current peaks occurring during grid faults especially for medium- and high-rated power plants operating with low switching frequencies. However, many efforts are still needed to improve its steady-state performance and to reduce its fragility to system’s parameters variation.

References [1] [2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

W. Hemetsberger, M. Schmela, G. Chianetta, Global Market Outlook for Solar Power 2020e2024”, Solar Power Europe, 2020. A. Etxegarai, P. Eguia, E. Torres, A. Iturregi, V. Valverde, Review of Grid Connection Requirements for Generation Assets in Weak Power Grid, Renewable and Sustainable Energy Reviews, vol. 41, 2015, pp. 1501e1514, https://doi.org/10.1016/j.rser.2014.09.030. ISSN 1364-0321. L. Liu, H. Li, Y. Xue, W. Liu, Decoupled active and reactive power control for large-scale grid-connected photovoltaic systems using cascaded modular multilevel converters, in: IEEE Transactions on Power Electronics, vol. 30, 2015, pp. 176e187, https://doi.org/ 10.1109/TPEL.2014.2304966. D. Eltigani, S. Masri, Challenges of Fintegrating Renewable Energy Sources to Smar Tgrids: A Review, Renewable and Sustainable Energy Reviews, vol. 52, 2015, pp. 770e780, https://doi.org/10.1016/j.rser.2015.07.140. ISSN 1364-0321. F. Benyamina, A. Benrabah, F. Khoucha, M.F. Zia, Y. Achour, M. Benbouzid, Online current limiting-based control to improve fault ride-through capability of grid-feeding inverters, Elec. Power Syst. Res. 201 (2021) 107524, https://doi.org/10.1016/ j.epsr.2021.107524. ISSN 0378-7796. R. Raghavendran, J.P. Roselyn, D. Devaraj, Development and performance analysis of intelligent fault ride through control scheme in the dynamic behaviour of grid connected DFIG based wind systems, Energy Rep. 6 (2020) 2560e2576, https://doi.org/10.1016/ j.egyr.2020.07.015. ISSN 2352-4847. ¨ . Go¨ksu, R. Teodorescu, C.L. Bak, F. Iov, P.C. Kjær, Instability of wind turbine converters O during current injection to low voltage grid faults and PLL frequency based stability solution, in: IEEE Transactions on Power Systems, vol. 29, 2014, pp. 1683e1691, https:// doi.org/10.1109/TPWRS.2013.2295261. M.A. Saqib, A.Z. Saleem, Power-quality Issues and the Need for Reactive-Power Compensation in the Grid Integration of Wind power,Renewable and Sustainable Energy Reviews, vol. 43, 2015, pp. 51e64, https://doi.org/10.1016/j.rser.2014.11.035. ISSN 13640321. M. Madrigal, B.H. Rocha, A contribution for characterizing measured three-phase unbalanced voltage sags algorithm, in: IEEE Transactions on Power Delivery, vol. 22, 2007, pp. 1885e1890, https://doi.org/10.1109/TPWRD.2007.893438. M.H.J. Bollen, Algorithms for characterizing measured three-phase unbalanced voltage dips, in: IEEE Transactions on Power Delivery, vol. 18, 2003, pp. 937e944, https://doi.org/ 10.1109/TPWRD.2003.813879.

444 PART | IX Smart grids [11] V. Ignatova, P. Granjon, S. Bacha, Space vector method for voltage dips and swells analysis, in: IEEE Transactions on Power Delivery, vol. 24, 2009, pp. 2054e2061, https://doi.org/ 10.1109/TPWRD.2009.2028787. [12] M.P. Kazmierkowski, M. Jasinski, G. Wrona, DSP-based control of grid-connected power converters operating under grid distortions, in: IEEE Transactions on Industrial Informatics, vol. 7, 2011, pp. 204e211, https://doi.org/10.1109/TII.2011.2134856. [13] C57. 12.20-2005 e IEEE Standard for Overhead-type Distribution Transformers, 500 kVA and Smaller: High Voltage, 34 500 V and below; Low Voltage, 7970/13 800Y V and below. [14] D. Gallo, C. Landi, M. Luiso, Accuracy analysis of algorithms adopted in voltage dip measurements, in: IEEE Transactions on Instrumentation and Measurement, vol. 59, 2010, pp. 2652e2659, https://doi.org/10.1109/TIM.2010.2045256. [15] P.G. Kini, R.C. Bansal, R.S. Aithal, A novel approach toward interpretation and application of voltage unbalance factor, in: IEEE Transactions on Industrial Electronics, vol. 54, 2007, pp. 2315e2322, https://doi.org/10.1109/TIE.2007.899935. [16] K. Ma, W. Chen, M. Liserre, F. Blaabjerg, Power controllability of a three-phase converter with an unbalanced AC source, in: IEEE Transactions on Power Electronics, vol. 30, 2014, pp. 1591e1604, https://doi.org/10.1109/TPEL.2014.2314416. [17] S. Alepuz, et al., Control strategies based on symmetrical components for grid-connected converters under voltage dips, in: IEEE Transactions on Industrial Electronics, vol. 56, 2009, pp. 2162e2173, https://doi.org/10.1109/TIE.2009.2017102. [18] P. Piya, M. Ebrahimi, M. Karimi-Ghartemani, S.A. Khajehoddin, fault ride-through capability of voltage-controlled inverters, in: IEEE Transactions on Industrial Electronics, vol. 65, 2018, pp. 7933e7943, https://doi.org/10.1109/TIE.2018.2803765. [19] A. Camacho, M. Castilla, J. Miret, R. Guzman, A. Borrell, Reactive power control for distributed generation power plants to comply with voltage limits during grid faults, in: IEEE Transactions on Power Electronics, vol. 29, 2014, pp. 6224e6234, https://doi.org/ 10.1109/TPEL.2014.2301463. [20] A. Camacho, M. Castilla, J. Miret, L.G. de Vicun˜a, R. Guzman, Positive and negative sequence control strategies to maximize the voltage support in resistiveeinductive grids during grid faults, in: IEEE Transactions on Power Electronics, vol. 64, 2018, pp. 5362e5373, https://doi.org/10.1109/TPEL.2017.2732452. [21] A. Luna, et al., Grid voltage synchronization for distributed generation systems under grid fault conditions, in: IEEE Transactions on Industry Applications, vol. 51, 2015, pp. 3414e3425, https://doi.org/10.1109/TIA.2015.2391436. [22] M. Nasiri, J. Milimonfared, S.H. Fathi, A review of low-voltage ride-through enhancement methods for permanent magnet synchronous generator based wind turbines, Renew. Sustain. Energy Rev. 47 (2015) 399e415, https://doi.org/10.1016/j.rser.2015.03.079. ISSN 13640321. [23] C.A. Busada, S. Gomez Jorge, A.E. Leon, J.A. Solsona, Current controller based on reduced order generalized integrators for distributed generation systems, in: IEEE Transactions on Industrial Electronics, vol. 59, 2012, pp. 2898e2909, https://doi.org/10.1109/ TIE.2011.2167892. [24] M. Hamouda, H.F. Blanchette, K. Al-Haddad, Unity power factor operation of indirect matrix converter tied to unbalanced grid, in: IEEE Transactions on Power Electronics, vol. 31, 2016, pp. 1095e1107, https://doi.org/10.1109/TPEL.2015.2421480.

A short review of grid voltage sags Chapter | 12 [25]

[26]

[27]

[28]

[29]

[30]

[31]

[32]

445

X. Guo, W. Liu, X. Zhang, X. Sun, Z. Lu, J.M. Guerrero, Flexible control strategy for grid-connected inverter under unbalanced grid faults without PLL, in: IEEE Transactions on Power Electronics, vol. 30, 2015, pp. 1773e1778, https://doi.org/10.1109/ TPEL.2014.2344098. A. Camacho, M. Castilla, J. Miret, J.C. Vasquez, E. Alarcon-Gallo, Flexible voltage support control for three-phase distributed generation inverters under grid fault, in: IEEE Transactions on Industrial Electronics, vol. 60, 2013, pp. 1429e1441, https://doi.org/10.1109/ TIE.2012.2185016. X. Guo, X. Zhang, B. Wang, W. Wu, J.M. Guerrero, Asymmetrical grid fault ride-through strategy of three-phase grid-connected inverter considering network impedance impact in low-voltage grid, in: IEEE Transactions on Power Electronics, vol. 29, 2014, pp. 1064e1068, https://doi.org/10.1109/TPEL.2013.2278030. March 2014. S. Vazquez, et al., Model predictive control: a review of its applications in power electronics, in: IEEE Industrial Electronics Magazine, vol. 8, 2014, pp. 16e31, https://doi.org/ 10.1109/MIE.2013.2290138. M. Hamdi, M. Hamouda, L. Sbita, K. Al-Haddad, FCS-MPC for grid-tied three-phase threelevel NPC inverter with experimental validation, in: 2017 International Conference on Green Energy Conversion Systems (GECS), 2017, pp. 1e6, https://doi.org/10.1109/ GECS.2017.8066246. S. Vazquez, J. Rodriguez, M. Rivera, L.G. Franquelo, M. Norambuena, Model predictive control for power converters and drives: advances and trends, in: IEEE Transactions on Industrial Electronics, vol. 64, 2017, pp. 935e947, https://doi.org/10.1109/ TIE.2016.2625238. Z. Zhang, O. Babayomi, T. Dragicevic, R. Heydari, C. Garcia, J. Rodriguez, R. Kennel, Advances and opportunities in the model predictive control of microgrids: Part Ieprimary layer, Int. J. Electr. Power Energy Syst. 134 (2022) 107411, https://doi.org/10.1016/ j.ijepes.2021.107411. ISSN 0142-0615. A. Calle-Prado, S. Alepuz, J. Bordonau, J. Nicolas-Apruzzese, P. Corte´s, J. Rodriguez, Model predictive current control of grid-connected neutral-point-clamped converters to meet low-voltage ride-through requirements, in: IEEE Transactions on Industrial Electronics, vol. 62, 2015, pp. 1503e1514, https://doi.org/10.1109/TIE.2014.2364459.

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Part X

Sustainability, policies, and regulations

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Chapter 13

Sustainable renewable energy policies and regulations, recent advances, and challenges Michail Tsangas1, Antonis A. Zorpas1 and Mejdi Jeguirim2 1 Laboratory of Chemical Engineering and Engineering Sustainability, Faculty of Pure and Applied Sciences, Open University of Cyprus, Latsia, Nicosia, Cyprus; 2The Institute of Materials Science of Mulhouse (IS2M), University of Haute Alsace, University of Strasbourg, CNRS, Mulhouse, France

1. Introduction According to the Intergovernmental Panel on Climate Change, climate change is already affecting people, ecosystems, and livelihoods all around the world. Although a 2 C maximum temperature increases goal, further to the Paris Agreement [1] seems more common, limiting warming to 1.5 C is possible, but it would require unprecedented transitions in all aspects of society. One of these is to significantly increase renewable energy share up to 70%e85% of electricity consumption in 2050. Moreover, policy arenas, governance structures, and robust institutions are key enabling conditions for transformative climate action [2]. Policy makers consider renewable energy as one of the potential solutions to climate change, energy security, and sustainable growth [3]. Organization for Economic Co-operation and Development (OECD) claims that sustainable energy systems are totally based on renewable energy sources [4]. Moreover, United Nations (UN), in September of 2015, have adopted 17 goals for sustainable development, known as Sustainable Development Goals (SDGs). Among them, SDG number seven aims to ensure access to affordable, reliable, sustainable, and modern energy for all. Moreover, it is crucial to achieve the 2 C global warming goal safeguarding human wellbeing and economic growth [5]. Energy is basic for all sectors of contemporary economy, supporting all the economic activities. Moreover, in case current trends continue, it is projected that the energy demand around the world is going to double by 2050 [6]. Renewable energy is named a number of energy resources available to man on Earth [7]. There are six different types. Wind energy, which is generated by the Renewable Energy Production and Distribution. https://doi.org/10.1016/B978-0-323-91892-3.00009-1 Copyright © 2022 Elsevier Inc. All rights reserved.

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kinetic energy of air movement, using wind turbines. Solar energy which is generated by the sun radiation when photovoltaic or solar thermal systems are used. Hydro power which is generated from the water potential at the high level. Bioenergy comes from organic materials of plants, trees, crops, and animals. Geothermal energy where the earth heat is extracted out in order to generate power and at the end, the marine, and ocean energy which come from the tides, the waves, the currents, the thermal energy of the oceans, and the salinity gradients [8]. There is a significant potential of such energy around the world [7], able to substitute fossil fuel energy production which dominates present energy systems. RES are connected to some adverse environmental impacts, for example, noise and risks for wild birds [9], loss of land, visual intrusion, impact to esthetics, impact on ecosystems, use of toxic and flammable materials and slight health risks from manufacture [10,11], toxicity to humans, photochemical oxidant formation, formation and exploitation of particulate matters (PM2.5, PM10), radiation, terrestrial acidification, eutrophication, ecotoxicity, agricultural and urban land occupation, natural land transformation but also water and fossil sources depletion, impact to climate change due to emissions by biogas and ozone depletion [12]. However, at the same time, they present several positive aspects to the environment, the society, and the economy. They are sustainable, secure, and safe. They enable the decarbonization of the economic growth, they refrain from geopolitical risks, and they are connected with low accident risk. Moreover, they can be supplied even in rural remote areas. Therefore, their development satisfies the requirements for sustainable energy. They contribute to the reduction of fossil fuel use and the mitigation of global warming. So they can be used as a tool for production of sustainable energy [13]. Well developed, executed, and managed RES have the ability to enable many countries to meet their environmental goals from the perspective of consumption and production with little or not at all, environmental pollution or hazards [14]. Moreover, RES integration is one of the most important energy-policy challenges of our times [15]. Sustainable development is the development that “meets the needs of the present without compromising the ability of future generations to meet their own needs” [16]. Nowadays, the concept of sustainable development is represented in legally binding texts at international, European, and national levels [17]. According to UN, “to achieve sustainable development and a higher quality of life for all people, States should reduce and eliminate unsustainable patterns of production and consumption and promote appropriate demographic policies.” In this concept, states shall enact effective environmental legislation [18]. Sustainability is possible, only when a significant potential of RES, multiple of the current energy needs, is available [19]. Moreover, RES seem to be an untapped potential [16]. It would, however, be unbalanced to put sustainable development only into a green perspective. The core aim of sustainable development is to reach intergenerational and intragenerational equity.

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In the latter case, the aim is to reach equity between the poor and the rich, thereby recognizing that developing countries are in need of economic growth. The real challenge of sustainable development is to find a proper balance between environmental, social, and economic concerns. This is reflected in Principle three of the Rio Declaration: The right to development must be fulfilled so as to equitably meet developmental and environmental needs of present and future generations [17]. In order to achieve a new orientation of the framework program, a new sustainability-oriented thematic agenda and a new governance approach are required [20]. Sustainable development and climate change mitigation are crucial, so the optimization of the energy planning is very important [21]. Moreover, energy planning, including the integration of sustainable energies shall be supported by policies and legislation [22]. The article 6 of the Paris Agreement sets the foundations of the climate action policies. Relevantly, three main policy areas are discussed. Any overachievements on the commitments of one country to be sell to another; a new carbon market, like the system was created under the Kyoto Protocols and the adoption of nonmarket approaches [23]. Besides, the implementation of energy policies unavoidably affects the microlevel behavior of enterprises and affect, in sequence, their financial performance [24]. In this framework, UN, European Union (EU), as United States of America (USA), China, and almost all the countries all over the world adopt policies and legislative tools to shape their energy planning and energy goals and to regulate and support the integration of RES in their energy mix. The implementation of such tools is affected by several factors, so they may be effective or not. In this framework, this chapter reviews the recent advances in sustainable renewable energy policies and regulations and investigates the relevant challenges.

2. Energy planning policy advances UN is an international organization which was founded in 1945 and has 193 Member States [25]. Its work includes the support of sustainable development and climate action. The organization further to its general assembly work organizes specific summits where Member States discuss and adopt agreements and introduce global targets. In 2009, United Nations Environment Program (UNEP) called for a Green New Deal according to which renewable energy should be prioritized [26]. Since sustainable development and climate action are connected and both are vital for the present and the future prosperity of humanity, this targeting will also help to reduce climate change. Moreover, within the climate action, the UNs supported the negotiations for the climate change, which led to the Paris Agreement on climate change in 2015 [27]. The central aim of the agreement is to strengthen the global response to the threat of climate change. An additional aim is to reinforce the ability of countries to confront the impacts will be caused [28]. Reflecting the growing understanding

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that this will offer a best way forward to improve the lives of people around the world, the organization launched a sustainable development agenda. Therefore, after the 1978 Agenda 21 and the Millennium Development Goals, which were adopted in 2000, UN in 2015, adopted the ambitious 2030 “Agenda for Sustainable Development,” which among 17 SDGs, included specific goals for climate action [28,29]. Specifically, SDG number 13, that is, “Take urgent action to combat climate change and its impacts” requires renewable energy targets to be further developed. According to a scientific blueprint issued by UNEP, renewable energy technologies, along with improved energy efficiency in buildings and elsewhere, will be very important. Therefore, the governments must develop laws and policies to enable greater public and private investments in RES generation and distribution [30]. Moreover, SDG number seven, that is, “Ensure access to affordable, reliable, sustainable and modern energy for all” require to increase significantly the share of renewable energy in the global energy mix by 2030 [31]. Nevertheless, countries which adopt the agreements are called to prepare their own planning and policies in order to achieve the specific targets set in the framework of the SDGs. However, the international climate agreements like these of UN offer only the direction. The energy policy regarding energy systems vary from one country to the other. Who are the main actors, what the policies include and how they are governed, are still national responsibilities and decisions [32]. EU is constituted by 27 member European countries and is based on the rule of law, meaning that every of its action is based on treaties [33]. Sustainable development is referred in its legislative framework. Although in the founding Treaty of Rome, the only statement related to the environmental protection was “the harmonization of environmental legislation and uniformity in the fight against certain forms of aid, so that technical barriers to the free circulation of goods would not arise due to different national links” [34,35], in 1991, the Treaty of Maastricht mentioned “sustainable and noninflationary growth respecting the environment” and “the fostering of sustainable economic and social development of the developing countries, and more particularly the most disadvantaged among them.” Moreover, the Treaty of Amsterdam in 1998 named sustainable development as one objective of the European integration [17]. Since current policies are able to achieve only 60% reductions of greenhouse gas (GHG) emissions by 2050 from 1990 levels, nowadays, the recently introduced European Green Deal aims to respond to the escalating climate crisis by achieving net zero emissions by 2050. This indicates the need for increased ambition [36]. According to the Treaty on the Functioning of the European Union, one of the goals of the Union energy policy is to promote renewable forms of energy. Therefore, a common framework for the promotion of RES has been established in the Union by the directive (EU) 2018/2001. This includes a binding target of at least a share of 27% of the energy consumption to be covered by renewable sources by 2030. It also rules on financial support for electricity

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from RES, on selfconsumption of such electricity, on the use of energy from renewable sources in the heating and cooling sector and in the transport sector, on regional cooperation between Member States, and between them and third countries, on guarantees of origin, on administrative procedures and on information and training are laid down. Also, sustainability and GHG emissions saving criteria for biofuels, bio liquids, and biomass fuels are established [37]. In this framework, member states are directed to adopt relevant goals and implement support schemes for their achievement. Moreover, measures to promote all types of RES are suggested including waste to energy, in the framework of circular economy promotion. It is also recognized that each country has different potential for different types of RES and interconnections within the scope of cost minimization are also included, when generally the cost affordability of RES to the people is one of the directive principals. To ensure the directive implementation, member states are called to prepare and adopt action plans and report the progress to the EU. In 2019, EU announced the new European Green Deal, which includes a clear vision for how to achieve climate neutrality by 2050. It aims EU to implement United Nations Development Program and SDGs by 2030, and to pull together actions and policies to achieve a successful and just transition toward a sustainable future [35]. More specifically, the Deal aims to put the EU on a pathway to reach at least 55% of Green House Gases release reduction by 2030 and requires bold action to accelerate the energy supply decarbonization. Therefore, the demand for clean power production could increase the need for deployment of either new or existed RES technologies like wind power and solar photovoltaics, as they have one of the lowest electricity generation costs [38]. Although many details of the proposals in the European Green Deal have to be worked out, it shows clearly that EU intents to be a leader by cutting rapidly its own emissions and using its financial resources, knowledge, and influence to encourage other nations to increase their climate actions [36]. The United States of America have recently reentry to the Paris Agreement process [23]. After a long period of not agreement, current administration plans again the adoption of the goals by the country. However, the economy of the country is depended on easy and plentiful cheap oil, coal, and natural gas. Although global warming and energy security concerns make the need for increase of the RES use generally accepted, among the politicians and the public, it seems that an energy transition away from fossil fuel would be economically and politically expensive for the country. The Energy Policy Act in 2005, and the Energy Independence and Security Act of 2007 reconfirmed continuous dependence of the country to the fossil fuel with the aim that energy efficiency and long-term transition to renewable energy sources would secure continued economic growth [39]. Energy policy in the USA involves federal, state, and local governmental actions for the production, distribution, and consumption of fossil as well as renewable energy. In this framework, a minimum amount of biofuel in transportation fuel is required since 2005 and

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as of May 2017, federal policies to promote renewable energy use such as loan guarantees, tax credits, and federal grants have been adopted [40]. However, recently a New Green Deal has also been introduced as a comprehensive program to combine the mitigation of the climate change with the elimination of economic inequality. One of the items, among others, that are spelled in the proposal, is 100% renewable electricity as a tool for zero emissions [41]. China has adopted several energy policies over the past 3 decades. These address different goals for green development including renewable energy development and deployment. The policies mainly target to the industrial sector which consume about the 70% of the power in the country [42,43]. They include factor of input, technical support, subsidies for renewable energy and regulations [44]. Besides China, Japan and Korea have also adopted several policy instruments to implement SDGs including authoritative instruments, incentive instruments, symbolic and advisory instruments, and capacity building instruments [45]. In May 2019, in Canada, the Pact for a New Green Deal has been launched, where the participants called among others for 100% renewable energy by 2030 [46]. In the same way, other major countries in America like Brazil, Argentina, and Mexico have in place policies that include RES as a tool for GHG emissions reduction [43,47]. Moreover, developing countries adopt policies and regulations for RES enhancement either to meet SDGs but more importantly to face current energy crisis [48].

3. Renewable energy policy challenges The sustainability of the renewable energy industry is depended on many factors. Except the climate change action, energy demand, energy security, energy access, and green jobs creation agenda can drive it forward. On the other hand, public opposition and inadequate funding for investments can hold it back [49]. Consequently, RES policy forming faces a number of challenges that have to be considered in order to be effective. Sustainability involves the management of economic, technological, institutional, natural, and social resources to ensure the needs of present and future generations [50]. Since it is generally accepted that sustainability has to consider and to be simultaneously supported by an environmental, an economic, and a social pillar, energy policy and legislation forming for sustainable development has similarly to be ensured that are extended to all three of them. Moreover, technical issues and developments have to be taken into account as well as political particularities. A popular analysis tool is the PESTEL (or PESTLE) analysis. The concept of the tool is that considering the political, economic, social, technical, environmental, and legal environment of an organization, the external environment or issues that could have an impact on its operations are identified [51,52]. Therefore, the challenges for energy policies for energy planning, including RES promotion and implementation to be complete and effective,

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can be analyzed within five elements of the context, that is, the political, the environmental, the social, the technical, and the economic. Issues regarding the legal context can be included in the political environment analysis.

3.1 Political challenges Currently not all the countries have implemented policies for RES [43]. Therefore, the first challenge is all the countries to adopt them. Especially, leading nations like the USA, which abstained for several years, have to be involved and substantially committed again in the common effort. However, across the developed world there are already well-developed policies for the integration of renewable energy in the energy mix. Nevertheless, such policies are new for developing countries and regions [53]. UN is a global organization with member states belonging both in developed and developing world and introduce global sustainability policies and goals including the SDGs. Nevertheless, the adoption of relevant policies and the implementation of the required measures in developing countries seems to face special barriers. Limited availability of information, limited experience, limited institutional commitment, limited cooperation, lack of adequate push of senior level, and low priority of RES are among the obstacles [54]. Moreover, some legal and regulatory issues like the lack of legislative instruments by the regulatory agencies to achieve the renewable energy policy target, lack of independence of institution structure, and the lack of regulatory assessment may be some other of the key reasons for the difficulties [53]. As has been observed by EU experience, research and innovation policy is also important for the achievement of the SDGs [20]. Therefore, another challenge is RES promotion policies to be closely supported by an adequate research and innovation legislative framework. In addition, although Renewable Energy is less likely to be a reason for conflict comparing to fossil fuel, they are still connected with the resource curse, especially during the transition. Bioenergy systems have higher potential to cause conflicts than the wind, hydro, or solar electricity. In order to prevent the problem and to minimize the risk, policies shall ensure that the transition will be a part of an inclusive sustainable development and the livelihood of the local actors will not be threatened [55]. Development of RES in a decentralized way with opportunities to local communities to participate is also considered as important for the sector sustainability [55]. Furthermore, stability of policies is also important for the long-term expansion and success of RES exploitation [32,55].

3.2 Economic challenges Core principal of sustainable development is the equity between rich and poor. Although in developed countries investments on RES are well established and

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financially supported [32], this is not always ensured in developing countries, where for instance, investors lose confidence in the governments to sustain the renewable energy goals [53]. It is observed that long-term, stable support schemes for RES, which allow multiple actors to invest, are very important. These both ensure the participation and benefit of local communities by the RES implementation [55] and the interest and continuous participation of investors. Although currently not all the countries have policies for renewable energy, many countries have adopted RES supporting instruments. These include direct investment tools like funding and investments to infrastructure, fiscal incentives, like feed-in tariffs, tax relief, taxes and loans, and market based instruments like green certificates, GHG allowances [43]. It is established that the most implemented RES supporting generation policy, that is, the feed-in tariff is effective [56]. However, another challenge for policy forming is RES financial support schemes not to benefit only large investors. Policies and legislation shall lower investment uncertainty, avoid a distortion of energy investment law toward specific flexibility options and technologies, and reduce the complexity of the legislation [15]. It is proved that the impact of the adoption of different energy policies is not homogeneous across the economy. For example, although energy efficiency measures in the buildings sector may boost the construction sector lead to negative effects in the output of the energy sector due to reduced fuel consumption [57]. Therefore, it is important policy makers to carefully select the energy planning measures, in order the negative effects to be prevented. Moreover, RES projects, in the medium term positively, affect the economic growth. However, in the literature, exist examples of negative macroeconomic impacts of renewable energy policies [57,58]. Another issue shall be mentioned is that taxation policy correlates with RES development. The higher the environmental taxes, the lower the intention to invest in green technologies [56]. In addition, according to the Paris Agreement principals, each country succeeds to achieve an energy target can sell this overachievement to another [23] usually in terms of GHG emissions. This creates challenges for policy making. Countries with more developed economies and ability to implement green energy projects could take advantage of this broadening the financial gap with nondeveloped countries, or the latter to delay the development in order to minimize their environmental footprint, instead of exploiting their renewable energy potential to achieve energy goals. There are three alternative approaches to the capitalist growth economy. The Green New Deal, which mainly concerns the green economy, proposing to restructure the industrial production to an ecological way. The degrowth approach which raises fundamental questions for the relationship of material prosperity to the individual and social well-being and the solidarity economy, the principals of which involve the direct implementation of the principles of selfdetermination and cooperation [59]. Green New Deal seems to be a

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dominating trend in developed capitalist growth economies, including USA and EU. However, it is a challenge to decide which of the four approaches shall be considered in the RES developing policies.

3.3 Social challenges New green jobs creation is a main issue that usually is mentioned as one benefit of RES development. Nevertheless, this is not always the case. For instance, it has been claimed that jobs creation by wind power is limited and the number of new position is depended on labor intensity of each country. Therefore, each project shall be assessed within the different institutional framework and labor market, the time, and technology if this is comparable [60]. Moreover, created jobs shall be ensured that are good jobs. But, this is not always the case, as research suggests that deficiencies on unionization or gender diversity are observed, when the participation and benefit of indigenous people by energy projects implementation shall be ensured [46] or not at least be threaten [55]. Participation of women in the RES implementation, especially when ecofeminism claims that there is a beneficial womenenaturenexus, shall also be considered [59]. Society resistance to RES establishment is also commonly met. Significant social opposition, even conflicts, among the indigenous communities, mainly against wind power and large-scale projects have been observed and thoroughly studied [61e63]. The different factors of the phenomenon are complex, when emotion seems to have a main role [63]. Landscape impacts and esthetics degradation seem to be other persistence causes, especially when public perception is taken into consideration [64]. Moreover, areas with high renewable energy potential, often present other overlapping uses of natural resources, including livelihoods and biodiversity [62] leading local communities to strongly deny the RES exploitation, especially when this seems to compete and alternate present situation. This has also to be considered in combination with the risk, participation, and benefit of local communities, not to be ensured [55]. Therefore, all above challenges shall be considered by the policy makers for RES development. Another contemporary issue that dominates the global trends and has to be taken into consideration is the current COVID-19 pandemic crisis. Its intensity is threatening the social, economic, and environment progress toward the achievement of the SDGs. The negative impacts of the situation are commonly observed but some positives and improvement to the environment are also in place [65,66]. Therefore, some sustainability targets are negatively affected, when in contrary the achievement of some others including SDG number 13 is facilitated [65]. This, of course, creates major challenges including complacent and freezing or even stoppage of targets implementation plans. Therefore, proportional policy and legislative actions have to be considered. For instance,

458 PART | X Sustainability, policies, and regulations

EU recovery and resilience to the pandemic funding facilities, aiming to create jobs and response to the immediate damage, could be used for RES integration increase [38].

3.4 Technical challenges The role of RES for the sustainable development is essential. Their development is promoted and their exploitation is in the core of the action plans promoted by the policies and the legislation for the achievement of relevant targets. However, there are some technical issues that have to be considered. Material requirements to construct and establish required RES projects are high and the impact of the development such projects to the mining and mineral availability could be significant leading to medium- and long-term supply shortages. Therefore, the governments and the companies should incorporate policies in energy planning to avoid resource depletion. These could for instance include legislation for the conservation and the extension of the equipment life used for renewable production through recycling and maintenance [67]. Although renewable energy is abundant, there are several technical and logistics difficulties for its exploitation. Its availability and suitability for use is affected by several factors including spatial [68], time, and technological. Moreover, many renewable energy technologies have human health and livelihood implications that endanger the lives and wellbeing of those already most vulnerable to the impacts of climate change and environmental justice have to be ensured in RES promotion policies [69]. However, technology for renewable production in terms of equipment, methods, and techniques evolves and get optimized rapidly [8,70e72] enabling its further and continuously expanding use. Renewable energy storage technologies also progress [73], offering choices and solutions for the renewable energy availability over time restrictions. These issues have as well to be considered and policies and legislation shall include relevant provisions for the best choice implementation for any case.

3.5 Environmental challenges It has already been mentioned that, RES are connected to adverse environmental impacts. Noise, loss of land or transformation of its use, visual intrusion, impact to esthetics, impact on ecosystems, use of toxic and flammable materials, health risks from manufacture and toxicity to humans, photochemical oxidant formation, formation and exploitation of particulate matters, radiation, terrestrial acidification, eutrophication, ecotoxicity, water and fossil sources depletion and impact to climate change due to emissions by biogas and ozone depletion are among the potential damages could be caused to the

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environment by the increase of renewable energy projects construction and operation [9e12]. All these shall be firstly prevented and secondly confronted by a robust legislative framework. The Environmental Impact Assessment (EIA) is a process that intends to ensure the management of both the real and the potential environmental impacts of specific projects [74] including renewable energy projects. Since the benefit of the application of the process depends on the context it takes place in Ref. [74] its integration in the RES promotion policies seems to be a challenge for the effective treatment of environmental impacts may be caused by the increase of renewable energy use. Moreover, long suggestions for the integration of the SDGs and EIA either linking of them have already been formulated with expectations of mutual benefits [75,76].

3.6 Summary of challenges A summary of the challenges of RES policy and legislation according to the five examined context elements is presented in Table 13.1.

TABLE 13.1 Challenges for RES integration policies and legislation. Element

Challenges

Political

l l l l l l

Economic

l l l

l l l l l l l l

Social

l l

l l l

All countries to adopt RES promotion policies New policies for developing countries and regions Barriers at developing countries Need for research and innovation policy Risk of conflict Stability of policies Equity between rich and poor Long term stability of RES support schemes Participation and economic benefit of indigenous people and local communities Benefit of large investors Uncertainty and complexity of investment laws Distortion of laws to not flexible options Negative effects of choices Negative macroeconomic impacts of renewable energy policies Taxation policies Rationality of overachievements trading Selection of economic system approach Jobs creation Participation and benefit of indigenous people and local communities Gender equality in participation and benefit Society resistance to RES projects COVID-19 pandemic Continued

460 PART | X Sustainability, policies, and regulations

TABLE 13.1 Challenges for RES integration policies and legislation.dcont’d Element

Challenges

Technical

l l

Environmental

l l l

Material requirements and availability for RES Technical and logistics difficulties for RES exploitation Environmental impacts of RES projects EIA effectiveness SDGs and EIA integration

4. Conclusion and recommendations Climate change is widely recognized as one of the most important concerns of our world and a significant threat for the prosperity of the humanity. However, it is not the only one. Traditional issues like poverty, wars, and other emerged more recently like scarcity of natural sources, pollution, and inequality led the global community to look for solutions and common actions. These led the UN, which is the main exponent of the global cooperation, to introduce the sustainability concept and to promote a number of resolutions, agreements, and sustainability goals to promote and establish it all over the world in order not only to confront the contemporary problems of the humanity, but to ensure intergenerational and intragenerational equity as well [17]. Moreover, urgent need for actions against current crisis like COVID-19 pandemic made this approach and the global cooperation more necessary. Individual member states, following above approach, adopted their policies and legislation to promote the required action plans to this direction. RES development was subsequently included as a key tool for sustainable development. In order to exploit the advantages for the environment, the economy and the society that are connected to renewable energy, including the lower GHG emissions and limited contribution to the global warming, many of the action plans to achieve sustainability targets comprise the integration of RES in either the international, national, or local energy mix. However, there are several challenges that are recognized and have to be taken into consideration. These can be approached, spotted, and analyzed further to the political, economic, social, technical, and environmental context. The concerns are plenty and cover a wide range of topics that policy makers and legislators have to consider. The effectiveness of the tools, the assurance of justice in all levels, the participation and benefit of all stakeholders including the weakest ones, the introduction, and promotion of effective choices are among the issues that have to be taken into account when a RES promotion policy is decided or a relevant legislation is adopted for implementation.

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Therefore, based on the above analysis, the following recommendations for policy makers and legislators can be formed. l

l

l

l l

l

l

l

l

Developed and richer countries to lift the main financial burden for RES development. A cooperation nexus of developed with developing countries to be widely established. Economic, social and environmental equity to be in the core of the policies and to be ensured by the legislation. Financial benefits from RES projects to be ensured that are diffused. RES related research and development results to be openly communicated and available. SDG targets action plans and RES promotion policies and legislation to be combined with the urgent action against the current pandemic. The implementation of the required tools for environmental management for RES projects, like EIA, to be solid. Global community to be more involved and monitor local policy making procedures and a homogeneity considering special circumstances. RES promotion policies to be in line with a holistic environmental protection approach.

It is clear that as the action against the climate change threat has to be global, all countries have to participate and no one should wait others to lead and take its share of responsibility. However, in this effort, the responsibilities are common but are individual too. Therefore, above challenges have to be considered in order effective RES promotion policies to be specific and effective for each case.

References [1]

[2] [3] [4] [5] [6]

M.T. Gunfaus, H. Waisman, Assessing the adequacy of the global response to the Paris Agreement: toward a full appraisal of climate ambition and action, Earth Syst. Gov. 8 (2021) 100102. V. Masson-Delmotte, P. Zhai, H.-O. Po¨rtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, IPCC report Global warming of 1.5 C 2, IPCCeSr15, 2018, pp. 17e20. R.B. Swain, A. Karimu, Renewable electricity and sustainable development goals in the EU, World Dev. 125 (2020) 104693. OECD Institutionalising Sustainable Development, vol. 36, OECD, 2007, ISBN 9789264018877. N.C. O, H. Kim, Towards the 2 C goal: achieving sustainable development goal (SDG) 7 in DPR Korea, Resour. Conserv. Recycl. 150 (2019) 104412. B. Atems, C. Hotaling, The effect of renewable and nonrenewable electricity generation on economic growth, Energy Pol. 112 (2018) 111e118.

462 PART | X Sustainability, policies, and regulations [7] B. Sorensen, Renewable Energy Physics, Engineering, Environmental Impacts, Economics & Planning, fourth ed., Academic Press, Oxford, 2011, ISBN 9780123750259. [8] N.K. Roy, A. Das, Prospects of Renewable Energy Sources, 2018, ISBN 9789811072871. [9] R. Saidur, N.A. Rahim, M.R. Islam, K.H. Solangi, Environmental impact of wind energy, Renew. Sustain. Energy Rev. 15 (2011) 2423e2430. [10] T. Tsoutsos, N. Frantzeskaki, V. Gekas, Environmental impacts from the solar energy technologies, Energy Pol. 33 (2005) 289e296. [11] R. Chiabrando, E. Fabrizio, G. Garnero, The territorial and landscape impacts of photovoltaic systems: definition of impacts and assessment of the glare risk, Renew. Sustain. Energy Rev. 13 (2009) 2441e2451. [12] M. Poeschl, S. Ward, P. Owende, Environmental impacts of biogas deployment - Part II: life Cycle Assessment of multiple production and utilization pathways, J. Clean. Prod. 24 (2012) 184e201. [13] A.A. Zorpas, M. Tsangas, M. Jeguirim, L. Limousy, J.N. Pedreno, Evaluation of renewable energy sources (solar, wind, and biogas) established in Cyprus in the framework of sustainable development, Fresenius Environ. Bull. 26 (2017) 5529e5536. [14] A.A. Alola, S. Akadiri, Saint Clean energy development in the United States amidst augmented socioeconomic aspects and country-specific policies, Renew. Energy 169 (2021) 221e230. [15] E.M. La¨ndner, A. Ma¨rtz, M. Scho¨pf, M. Weibelzahl, From energy legislation to investment determination: shaping future electricity markets with different flexibility options, Energy Pol. 129 (2019) 1100e1110. [16] WCED the Brundtland Report: “Our Common Future.”, 1987. [17] H. Heinrichs, P. Martens, G. Michelsen, A. Wiek, Sustainability Science an Introduction, 2016, ISBN 9780511794469. [18] A./C.O.N.F. United Nations, in: 151/26/Vol.I: Rio declaration on environment and development, Rep. United Nations Conf. Environ. Dev., I, 1992, pp. 1e5. [19] P. Zweifel, A. Praktiknjo, G. Erdmann, Energy Economics, 2017, ISBN 9781351626200. [20] N. Kastrinos, K.M. Weber, Sustainable development goals in the research and innovation policy of the European Union, Technol. Forecast. Soc. Change 157 (2020) 120056. [21] J.P. Vazhayil, R. Balasubramanian, Hierarchical multi-objective optimization of India’s energy strategy portfolios for sustainable development, Int. J. Energy Sect. Manag. 6 (2012) 301e320. [22] M.M. Akrofi, B.A.A. Akanbang, Integrating sustainable energies into local government plans in Ghana, Sci. African 12 (2021) e00764. [23] J. Morgan, H. Patoma¨ki, Planetary good governance after the Paris Agreement: the case for a global greenhouse gas tax, J. Environ. Manag. 292 (2021) 112753. [24] C. Liu, J. Fang, R. Xie, Energy policy and corporate financial performance: evidence from China’s 11th five-year plan, Energy Econ. 93 (2021) 105030. [25] United Nations, About Us Available online: https://www.un.org/en/about-us/. (Accessed 17 June 2021). [26] UNEP “Global green new deal: policy brief, in: United Nations Environ. Program. 19, 2009, pp. 185e193. [27] J. Delbeke, A. Runge-Metzger, Y. Slingenberg, J. Werksman, The paris agreement, in: Towards a Clim. Eur. Curbing Trend, 24e45, 2019. [28] United Nations Support Sustainable Development and Climate Action. Available online: https:// www.un.org/en/our-work/support-sustainable-development-and-climate-action. (Accessed 17 June 2021).

Sustainable renewable energy policies Chapter | 13 [29] [30] [31] [32] [33] [34] [35] [36] [37]

[38] [39] [40] [41] [42]

[43] [44] [45] [46]

[47]

[48] [49] [50]

463

United Nations THE 17 GOALS. Available online: https://sdgs.un.org/goals. (Accessed 27 June 2021). United Nations, Environment Programme Making Peace with Nature, 2021, ISBN 9789280738377. United Nations Goals 7. Available online: https://sdgs.un.org/goals/goal7. (Accessed 28 June 2021). A. Proka, M. Hisschemo¨ller, D. Loorbach, Transition without conflict? Renewable energy initiatives in the Dutch energy transition, Sustainability 10 (2018). EU. EU Treaties Available online: https://europa.eu/european-union/law/treaties_en. (Accessed 16 June 2021). European Economic Community, Treaty of Rome (1957). A.A. Zorpas, Strategy development in the framework of waste management, Sci. Total Environ. 716 (2020) 137088. A. Haines, P. Scheelbeek, European Green Deal: a major opportunity for health improvement, Lancet 395 (2020) 1327e1329. European Parliament Directive (EU) 2018/2001 of the European Parliament and of the Council on the promotion of the use of energy from renewable sources, Off. J. Eur. Union (2018) 82e209. I. Kougias, N. Taylor, G. Kakoulaki, A. Ja¨ger-Waldau, The role of photovoltaics for the European Green Deal and the recovery plan, Renew. Sustain. Energy Rev. 144 (2021) 1e8. G. Bang, Energy security and climate change concerns: triggers for energy policy change in the United States? Energy Pol. 38 (2010) 1645e1653. Ballotpedia Energy policy in the United States. Available online: https://ballotpedia.org/ Energy_policy_in_the_United_States. (Accessed 28 June 2021). R. Galvin, N. Healy, The Green New Deal in the United States: what it is and how to pay for it, Energy Res. Social Sci. 67 (2020). J. Zeng, W. Tong, T. Tang, How do energy policies affect industrial green development in China: renewable energy, energy conservation, or industrial upgrading? Chinese J. Popul. Resour. Environ. 18 (2) (2021) 79e86. G. Muhammed, N. Tekbiyik-Ersoy, Development of renewable energy in China, USA, and Brazil: a comparative study on renewable energy policies, Sustainability 12 (2020) 1e30. Y. Kong, C. Feng, J. Yang, How does China manage its energy market? A perspective of policy evolution, Energy Pol. 147 (2020) 111898. H. Xie, J. Wen, Y. Choi, How the SDGs are implemented in Chinada comparative study based on the perspective of policy instruments, J. Clean. Prod. 291 (2021) 125937. J.L. MacArthur, C.E. Hoicka, H. Castleden, R. Das, J. Lieu, Canada’s Green New Deal: forging the socio-political foundations of climate resilient infrastructure? Energy Res. Social Sci. 65 (2020) 101442. E.C. Pischke, B. Solomon, A. Wellstead, A. Acevedo, A. Eastmond, F. De Oliveira, S. Coelho, O. Lucon, From Kyoto to Paris: measuring renewable energy policy regimes in Argentina, Brazil, Canada, Mexico and the United States, Energy Res. Social Sci. 50 (2019) 82e91. R.A. Atuguba, F.X.D. Tuokuu, Ghana’s renewable energy agenda: legislative drafting in search of policy paralysis, Energy Res. Social Sci. 64 (2020) 101453. M. Mendonc¸a, S. Lacey, F. Hvelplund, Stability, participation and transparency in renewable energy policy: lessons from Denmark and the United States, Polic. Soc. 27 (2009) 379e398. W.C. Valenti, J.M. Kimpara, B. de L. Preto, P. Moraes-Valenti, Indicators of sustainability to assess aquaculture systems, Ecol. Indicat. 88 (2018) 402e413.

464 PART | X Sustainability, policies, and regulations [51] Team FME PESTLE Analysis, Strategy Skills, 2013. [52] M. Tsangas, M. Jeguirim, L. Limousy, A. Zorpas, The application of analytical hierarchy process in combination with Pestel-SWOT analysis to assess the hydrocarbons sector in Cyprus, Energies 12 (5) (2019), 791. [53] N.A. Obeng-Darko, Why Ghana will not achieve its renewable energy target for electricity. Policy, legal and regulatory implications, Energy Pol. 128 (2019) 75e83. [54] A.O. Adelaja, Barriers to national renewable energy policy adoption: insights from a case study of Nigeria, Energy Strateg. Rev. 30 (2020) 100519. [55] A. Ma˚nsson, A resource curse for renewables? Conflict and cooperation in the renewable energy sector, Energy Res. Social Sci. 10 (2015) 1e9. [56] A. Carfora, R.V. Pansini, G. Scandurra, The role of environmental taxes and public policies in supporting RES investments in EU countries: barriers and mimicking effects, Energy Pol. 149 (2021) 112044. [57] C. Taliotis, E. Giannakis, M. Karmellos, N. Fylaktos, T. Zachariadis, Estimating the economy-wide impacts of energy policies in Cyprus, Energy Strateg. Rev. 29 (2020) 100495. [58] U. Lehr, J. Nitsch, M. Kratzat, C. Lutz, D. Edler, Renewable energy and employment in Germany, Energy Pol. 36 (2008) 108e117. [59] C. Bauhardt, Solutions to the crisis? The green new deal, degrowth, and the solidarity economy: alternatives to the capitalist growth economy from an ecofeminist economics perspective, Ecol. Econ. 102 (2014) 60e68. [60] L. Aldieri, J. Grafstro¨m, K. Sundstro¨m, C.P. Vinci, Wind power and job creation, Sustainability 12 (2020) 1e23. [61] N. Martinez, Resisting renewables: the energy epistemics of social opposition in Mexico, Energy Res. Social Sci. 70 (2020) 101632. [62] S. Lakhanpal, Contesting renewable energy in the global south: a case-study of local opposition to a wind power project in the Western Ghats of India, Environ. Dev. 30 (2019) 51e60. [63] N. Cass, G. Walker, Emotion and rationality: the characterisation and evaluation of opposition to renewable energy projects, Emot. Sp. Soc. 2 (2009) 62e69. [64] R. Ioannidis, D. Koutsoyiannis, A review of land use, visibility and public perception of renewable energy in the context of landscape impact, Appl. Energy 276 (2020) 115367. [65] S. Suriyankietkaew, COVID-19 Impacts and Sustainability Strategies for Regional Recovery in Southeast Asia: Challenges and Opportunities, 2021. [66] P. Loizia, I. Voukkali, G. Chatziparaskeva, J. Navarro-Pedren˜o, A.A. Zorpas, Measuring the level of environmental performance on coastal environment before and during the covid-19 pandemic: a case study from Cyprus, Sustainability 13 (2021) 1e25. [67] G. Calvo, A. Valero, Strategic mineral resources: availability and future estimations for the renewable energy sector, Environ. Dev (2021) 100640. [68] A. Angelis-Dimakis, M. Biberacher, J. Dominguez, G. Fiorese, S. Gadocha, E. Gnansounou, G. Guariso, A. Kartalidis, L. Panichelli, I. Pinedo, et al., Methods and tools to evaluate the availability of renewable energy sources, Renew. Sustain. Energy Rev. 15 (2011) 1182e1200. [69] A.M. Levenda, I. Behrsin, F. Disano, Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies, Energy Res. Social Sci. 71 (2021) 101837. [70] B.P. Singh, S.K. Goyal, P. Kumar, Solar pv cell materials and technologies: analyzing the recent developments, Mater. Today Proc. 43 (2021) 2843e2849.

Sustainable renewable energy policies Chapter | 13 [71] [72] [73]

[74]

[75]

[76]

465

K. Johansen, Blowing in the wind: a brief history of wind energy and wind power technologies in Denmark, Energy Pol. 152 (2021) 112139. A. Anderson, B. Rezaie, Geothermal technology: trends and potential role in a sustainable future, Appl. Energy 248 (2019) 18e34. K.M. Tan, T.S. Babu, V.K. Ramachandaramurthy, P. Kasinathan, S.G. Solanki, S.K. Raveendran, Empowering smart grid: a comprehensive review of energy storage technology and application with renewable energy integration, J. Energy Storage 39 (2021) 102591. C. Roos, D.P. Cilliers, F.P. Retief, R.C. Alberts, A.J. Bond, Regulators’ perceptions of environmental impact assessment (EIA) benefits in a sustainable development context, Environ. Impact Assess. Rev. 81 (2020) 106360. E. Ravn Boess, L. Kørnøv, I. Lyhne, M.R. Partida´rio, Integrating SDGs in environmental assessment: unfolding SDG functions in emerging practices, Environ. Impact Assess. Rev. 90 (2021). L. Kørnøv, I. Lyhne, J.G. Davila, Linking the UN SDGs and environmental assessment: towards a conceptual framework, Environ. Impact Assess. Rev. 85 (2020) 106463.

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Index Page numbers followed by “f ” indicate figures, “t” indicate tables, and “b” indicate boxes

A Abrasive resistance, pellets, 148 Amorphous silicon (PV) cells, 111e112, 111f Artificial intelligence techniques, 391 Artificial neural network (ANN), 19, 389 Autoregressive integrated moving average (ARIMA) model, 391, 397e398, 398f

B Battery energy storage system (BESS), 312 Bioenergy, 449e450 Biomass based power production biomass pellets-based power (BPBP) generation, 177 cofiring experiment experimental setup, 173, 175f mill outlet temperature (MOT), 174 SOx and NOx emissions, 174e175, 176f specific fuel consumption (SFC), 174 tested fuels, 176t combined heat and power (CHP) plants, 175e177 data and figures, 178t pellet structure, 180f tradeoff solutions., 177e179 wood pellets, 177 Biomass pellets-based power (BPBP) generation, 177 Biomass pellets production biomass feedstock, 141e142, 143te145t biomass pellets, 140 biomass production, 139 combustion, 140 fluidized beds (FB) combustion, 140e141 gasification process, 140 pelletization process, 146e147 pellets characterization, 150te151t abrasive resistance, 148 bulk density, 147 chemical bonds, 149 chemical properties, 149 combustion/thermal properties, 148

elemental analysis, 149 mechanical properties, 147e148 particle distribution, 147 pellets characterization, 147 physical properties, 147 porosity, 147 surface morphology, 149 water resistance/porosity index, 147 pellets combustion. See Pellets combustion pyrolysis, 140 wood combustion process, 140, 141f wood pellets, 139e140 Borehole stimulation, 278e279 Bruggeman’s thermal conductivity models, 10e11

C Calorific value, pellets, 148 Carbon nanofluids, 19e22, 21f Catalytic supercritical water gasification heterogeneous catalysts, 212e215 homogeneous catalysts, 211e212 Cenerg model, 118 Cleuson-Dixence project, 306 Closed loop transfer control system, 84 Combined heat and power (CHP) plants, 175e177 Combustion rate (CR), pellets, 148 Communal and industrial use combustion technologies fuel properties, 166 experimental setup, 166, 166f operating conditions and emission factors, 166e170, 169t particle mass size distributions, 170, 170f particulate matter (PM) emissions ash-forming elements release, 171, 172f bark-based pellets, 170e171 bottom ashes composition, 171 chemical composition and mass closure, 170, 171f fuel index, 171e172

467

468 Index Communal and industrial use combustion technologies (Continued ) size distributions, 170f tested pellets, 166 Concentrated photovoltaic (PV) cells, 112, 112f Concentrated solar collectors. See Hybrid nanofluids (HNFs) Concentrated solar power (CSP), 4, 4f Conventional nanofluids (CNF), 7 Copper oxide/water (Cu2O/W) nanofluid, 19 Covalent functionalized-graphene nanoplatelets (CF-GNPs), 9 Covalent functionalized-MWCNTs (CF-MWCNTs), 9 Crystalline silicon photovoltaic (PV) cells, 110e111, 111f Cut-off temperature, heat transfer fluids (HTFs), 344 Cycling operation, thermocline tank, 344

D Dam heightening, 303e304 DC/DC boost converter, 75e76 Delta inverter, photovoltaic systems configuration, 87 control strategy, 88e94 DC bus voltage regulation, 89e90 experimental results developed test bench, 101f ePWM blocks, 101f microcontroller, 100 phase to neutral output voltage waveforms, 102f phase-to-phase output voltage waveforms, 102f R-L load currents iabc, 102f Simulink model, 100, 100f switching frequency, 99e100 output, 88, 89f reactive current control, 90 simulation results active and reactive power, 96, 96f DC bus voltage, 96f harmonics distribution, 99f parameters, 95t voltage and current, 98f SPWM control technique comparative study, 92e94 modulating functions, 93t phase to neutral and phase to phase voltages, 92t

Sandoval SPWM strategy, 91 sinusoidal modulation technique, 91 structure, 86e87 Direct absorption PTC (DAPTC), 38 Distributed power generation systems (DPGS) configurations, 415, 416f fault ride through (FRT) requirement, 416e417 massive installed power, 415 penetration level, 415 reactive current requirement vs. grid voltage, 417f steady-state operation, 416e417 three-phase voltage source inverter (VSI), 415 voltage source inverter (VSI). See Voltage source inverter (VSI) Domestic use combustion, pellets pellets boilers boilers efficiency, 161, 161f CO emission, 158e161, 159f, 162f combustion efficiency, 158, 158f, 164, 164f domestic pellets boiler, 157e158 dust emissions, 160f NOx emission, 159f, 160e161, 162f olive mill wastewater (OMW), 163e164 particle emissions, 163, 163f particulate matter (PM) emissions, 165, 165f principal component analysis, 165e166 SO2 emissions, 162e163 wood pellet stoves CO emissions factors, 153e154 design, 156, 157f formaldehyde (HCHO) factors, 153e154 furnace design, 156e157 gaseous emissions, 153e155, 153f, 155f methane (CH4), 153e154 modern pellet stove, 149e152, 152f particulate matter (PM) emissions, 154e156, 156f pellets quality, 152e153 small-scale pellet stoves, 149e152 thermal pretreatment, 154 torrefaction, 156 Double exponential real model (DERM) output current, 116 two-diode representation, 116f

Index

E Econometric models, 403e405 multiple linear regression (MLR), 400 NARX technique, 400e401, 402f Electrical model single-diode representation, 115f two-diode representation, 116f Electric load forecasting (ELF) classical techniques’ design, 391 efficiency assessment, 392 hybrid model, 391 hybrid techniques, 391e392 input features, 390 long-term electric load forecasting (LTELF), 390 medium term electric load forecasting (MTELF), 390 short term electric load forecasting (STELF), 390 Tunisian electricity consumption autoregressive integrated moving average (ARIMA) model, 397e398 CO2 emissions impact, 395e396, 396f dataset, 393e396 econometric models, 399e401 gross domestic product impact, 395 influencing factors, 393e396 literature review, 404t load pattern, 393 nonlinear autoregressive neuronal network (NAR), 399 performance measurement criteria, 401e403 population impact, 394 simulation results, 403e409 telecommunication technologies impact, 396 time series approaches, 396e399 Enclosed-type evacuated U-tube, 21e22, 21f Energy planning policy advances China, 454 European Union European Green Deal, 453 sustainable development, 452 Treaty of Amsterdam, 452 Treaty of Maastricht, 452 Union energy policy, 452e453 United Nations (UN), 451e452 United States of America, 453e454 Enhanced geothermal system (EGS) borehole stimulation, 278e279 chemical stimulation, 279e281

469

economic viability, 275 environmental aspects groundwater protection and scalings, 291 induced seismicity, 291e292 life cycle analysis, 290 geothermal plant, 276f global deep geothermal energy Basel (Switzerland), 285e286 Fenton Hill HDR project, 283 geothermal plants distribution, 283f Japanese HDR Hijiori project, 284e285 Rosemanowes Quarry (United Kingdom), 284 Soultz-sous-Foreˆts (France), 285 heat exchanger, 275 vs. hot dry rock (HDR) process, 274e275, 287e288 vs. hydrothermal energy, 273e274 monitoring, 281 natural gas and oil fracking, 289e290 permeable fracture network, 275 reservoir creation hydraulic fracturing, 275e276 hydraulic shearing, 277 hydraulic stimulation, 275e276 shear crack expansion, 277 Environmental Impact Assessment (EIA), 459 European Green Deal, 453 Evacuated tube solar collectors (ETSC) carbon nanofluids, 19e22, 21f hybrid/combination nanofluids, 22, 23te31t metal nanofluids, 11e14 metal oxide nanofluids Al2O3 nanofluid, 16e17 CeO2/water, 18 copper oxide/water (Cu2O/W) nanofluid, 19 CuO/water nanofluids, 14e16 MgO/water nanofluid, 17e18, 18f single-phase and discrete ordinary models, 14e16 TiO2/distilled water nanofluid, 17 WO3/water nanofluid, 18e19 ZnO/Etylene Glycol-PW (ZnO/EG-PW) nanofluid, 17 three-dimensional numerical simulation, 14e16 working fluids, 11

470 Index Exergy efficiency, thermocline packed bed thermal energy storage system, 342 Exhausted olive solid waste (EOSW), 163e164 Extension-based concept (EGS), 288e289

F Fenton Hill HDR project, 283 Finite control set model predictive control (FCS-MPC) block diagram, 440f cost function, 441 operation principle, 440e442 two-level VSI, switching state, 441, 441t Finned surface solar air heaters (SAHs), 47f Fixed Broadband Subscriptions (FBS), 396, 397f Fixed Telephone lines Subscriptions (FTS), 396, 397f Flat plate solar collector (FPSC) drawbacks, 8 hybrid nanofluid, 9, 10f flow rate, 10f MgO/MWCNTs and CuO/MWCNTs HNFs, 8e9 nanodiamond-cobalt oxide (ND-Co3O4), 10f reviewed research, 12te13t SiC-MWCNT/ethylene glycol nanofluid circulation, 10 thermal efficiency, 10 water-based nanofluids, 10e11 nanofluids, 8e9 performance, 8e11 thermal efficiency, 8e9, 9f Fluidized bed reactor, 202f Fluidized beds (FB) combustion, 140e141 Fortescue transformation matrix, 418

G Gasification process, 140 Geothermal energy, 449e450 Green New Deal, 456e457 Grid connected photovoltaic (PV) system conventional DC/AC inverter control strategy, 83e86 DC bus voltage regulation, 84e86 mathematic model, 81e82 power circuit, 81f reactive current regulation, 83e84 structure, 81

current, 75 DC/DC boost converter, 73, 75e76 components, 75 MPPT controls, 76 operating sequences, 76 perturb and observe (P&O) algorithm, 76, 77f PV cell parameters, 78t simulation results, 76 DC output voltage, 80f delta inverter configuration, 87 control strategy, 88e94 DC bus voltage regulation, 89e90 experimental results, 98e101 output, 88, 89f reactive current control, 90 simulation results, 94e98 SPWM control technique, 91e94 structure, 86e87 equivalent circuit, 74f experimental technical parameters, 75 I-V and P-V characteristics, 78f irradiation, 79, 80f temperature, 77, 79f output current, 75 PV module output power, 80f PV panel model, 74 simulation results, 76 solar cell modeling, 74 structure, 73f Grid-connected photovoltaic system (PVS), 107 Grid tied photovoltaic system (PVS), 113e114, 114f

H Hardware-in-the-loop (HIL) test, 126e128 Heat convection loss, thermocline tank, 339 Heat radiation loss, thermocline tank, 339 Heat transfer fluid (HTF), 5, 7, 333e334, 336t Heterogeneous-heat thermocline packed-bed (HHTPB) system configuration cases, 357, 359f 1D enthalpy-method D-C model, 359 design parameters, 358t SHTPB and LHTPB system limitation, 357 vs. single-layered rock media system, 359 Homogeneous catalysts, 211e212 Hot dry rock (HDR), 274e275, 288e289. See also Enhanced geothermal system (EGS)

Index Human-induced Earthquake Database (HiQuake), 291e292 Hybrid nanofluids (HNFs) concentrated solar collectors Al2O3-TiO2/Syltherm 800, 33e34 alumina and tungsten oxide-Therminol VP1, 34 collector efficiency, 33f direct absorption PTC (DAPTC), 38 mono nanofluid, 22e32 parabolic trough collector (PTC), 34, 35f reviewed research, 36te37t Reynolds number, 33f schematics, 32f thermal efficiency, 35f three-dimensional numerical model, 34 turbulators, 35e38 evacuated tube solar collectors (ETSC), 22, 23te31t flat plate solar collector (FPSC), 8e9, 10f Hydraulic fracturing technology, 274e276 Hydraulic shear, 276 Hydrogen production conventional gasification, 189e190 drawback, 189 pyrolysis, 189e190 supercritical water gasification batch reactors, 198e199 biomass, 192e195 catalysts, 210e215 continuous reactors, 199e202 feed concentration, 205e207 pilot scale process, 202e203 pressure effect, 208e210 reaction mechanism, 196e197 residence time, 207e208 supercritical state, 190 temperature effect, 203e204 water properties, 190e192 Hydropower plants (HPPs) modernization with battery energy storage system (BESS), 312 benefits, 302e303 dam heightening, 303e304 digitalization and flow forecast, 311e312 efficiency after refurbishing runner seal components, 308t average efficiency gain, 310 best efficiency point (BEP), 307e309 draft tubes modifications, 307e308

471

Francis turbine efficiency, 307e309, 307t improvement, part load, 309e311 variable speed, 310e311 water passage component refurbishment, 307e309 environmental and practical considerations, 313e315 flexibility, 302e303 with floating photovoltaics (FPV), 312e313 inflow increase and larger equipment, 306e307 nonpowered dams (NPDs), 301e302 PV panels, 313 refurbishment, 302 retrofitting, 302 waterways and penstocks cleaning methods, 304e305 friction loss reduction, 304 headrace tunnel diameter, 305 new parallel waterway system, 305e306 tunnel lining rehabilitation, 305 Hydrothermal Diamond Anvil Cell (HDAC), 199, 201f Hydrothermal gasification. See also Supercritical water gasification process hydrogen consumption reactions, 197 inorganic salt precipitation, 218 methanation and hydrogenation reactions, 197 reactor design, 218 steam reforming, 196 Water Gas Shift, 197

I Ignition time, pellets, 148 Impregnated exhausted olive solid waste (IEOSW), 163e164 Information and communication technologies (ICTs), 389 Inlet temperature, heat transfer fluids (HTFs), 344

J Japanese HDR Hijiori project, 284e285 Jordan electrical energy production, 235f energy generating capacity, 236t energy status, 234

472 Index Jordan (Continued ) location, 229 renewable energy resources, 235e237 statistics and indicators, 231t wind direction, 231e232 wind speed and potentials annual mean and cubic wind speed, 242, 242t electrical industry, 263 energy cost, 246, 248f energy flux, 242t energy production, 246e249, 249t mean monthly and annual wind speed, 241t mean power density, 242, 242f meteorological wind speed data, 249e250 National Renewable Energy Action Plan (NREAP), 264 pilot and commercial projects, 257e262 Rayleigh parameters, 246t theoretical capacity factor, 248f Weibull and Rayleigh distributions, 245e246, 246f Weibull parameters, 247t wind map, 240, 240f wind turbine models, 242, 243t, 245, 245f

L Latent heat storage, 330 Latent-heat thermocline packed-bed (LHTPB) system multilayered latent-heat thermocline, 354e357 single-layered latent-heat thermocline, 351e354 Laufenburg power plant, 306e307 Life cycle analysis (LCA), enhanced geothermal system (EGS), 290 Linear regression (LR), 389 Long-term electric load forecasting (LTELF), 390

M Mass flow rate, heat transfer fluids (HTFs), 343 Matlab/Simulink PV simulator interface, 122 Mauvoisin II project, 306 Maximum power point tracking (MPPT) control method, 118e120

Mean Absolute Error (MAE), 401e402 Mean absolute percentage error (MAPE), 391, 401e403 Mean Absolute Scaled Error (MASE), 401e402 Medium term electric load forecasting (MTELF), 390 Mill outlet temperature (MOT), 174 Mobile Cellular Subscriptions (MCS), 396, 397f Model predictive control (MPC), 438e442 Modified mix number (MIX), 341 Multilayered latent-heat thermocline cascaded systems, 356, 356f heat transfer, 354 thermal performance, 354 three-stage, 356e357 Multilayered sensible-heat thermocline, 350e351, 351f Multilayer Perceptron model, 19 Multiple linear regression (MLR), 400

N Nanodiamond-cobalt oxide (ND-Co3O4), 10f Nanofluids technical applications, 8 thermal conductivity, 8 thermophysical characteristics, 8 National Renewable Energy Action Plan (NREAP), 264 Nonlinear autoregressive neuronal network (NAR) technique, 399, 399f Nonpowered dams (NPDs), 301e302

O Olive mill wastewater (OMW)-based pallets, 163e164 One- and two-dimension two-phase dispersion-concentric model (1,2D-2P D-C), 363e364 One-dimension one-phase (1D-1P), 361e362 One-dimension three-phase (1D-3P) model, 364e365 One-dimension two-phase Schumann’s model (1D-2P Schumann’s model), 362e363 One-diode model, 121, 121f Organic photovoltaic (PV) cells, 112, 112f

P Palestine climate, 233

Index energy status, 237 Gaza Strip (GS), 233e234 location, 232e233 political situation, 232e233 renewable energy resources, 238 statistics and indicators, 231t territories, 233 West Bank (WB), 233e234 wind speed and potentials annual mean, 256t average wind speed and power density, 254e256, 256t Gamesa G128e4.5 MW turbine, 255t Gaza strip, 252e253, 252f literature review, 257, 258t locations, 251 monthly wind speed, 251fe252f numerical weather prediction model, 251 power and energy densities, 256t and power density, Jerusalem, 257f renewable energy strategy, 264, 264t simulation study, 251e252 Weibull parameters, 250, 250t, 253f, 256t wind energy projects, 262e263 wind resources, 251 Pelletization process drying step, 146 mixing and conditioning step, 146 pellet mills, 146e147, 147f pellet quality and size, 146 stages, 146f Pellet mill system, 147f Pellets combustion biomass based power production biomass pellets-based power (BPBP) generation, 177 cofiring experiment, 173e175 combined heat and power (CHP) plants, 175e177 data and figures, 178t pellet structure, 180f tradeoff solutions, 177e179 wood pellets, 177 combined heat and power production, 172e173, 173f, 174t communal and industrial use combustion technologies, 166e172 domestic use combustion pellets boilers, 157e166 wood pellet stoves, 149e157

473

Perovskite photovoltaic (PV) cells, 112, 112f Perturb and observe (P&O) algorithm, 76, 77f Petrothermal energy. See also Enhanced geothermal system (EGS) Germany, electricity generation, 286e287 hot dry rock (HDR) process, 274 vs. hydrothermal systems, 273 Phase change material (PCM) fillers, 46 capsules melting process, 333f cost of, 333 density variation, 331 encapsulated, 331e333 organic, 331e333 phase transition, 330 solid-liquid PCM fillers, 332t solid-liquid transition, 330 stored energy, 330e331 “sup-cooling” phenomenon, 331 temperature profiles, 331f Photovoltaic (PV) cells concentrated, 112, 112f crystalline silicon cells, 110e111, 111f first generation, 110e111 inorganic thin film silicon and amorphous silicon PV cells, 111e112, 111f organic, 112, 112f perovskite, 112, 112f second generation, 111e112 third generation, 112, 112f Photovoltaic (PV) emulator controller validation, 126e128 energy source system, 120 experimental test bench, 130e132, 132f FPGA implementation benefits, 121 hardware-in-the-loop (HIL) test, 126e128 model choice Matlab/Simulink PV simulator interface, 122 one-diode model, 121, 121f two-diode model, 121, 121f real hardware platform, 130, 131f real-time (RT) digital simulation, 125e126 reference and emulated values, 125t synoptic diagram buck converter transfer functions, 122e124 minimum low-pass filter parameters, 122 simulation results, 124 two-diode model, 122 Photovoltaic-powered thermoelectric heat pumping solar air heaters (SAHs) absorber plate, 52e53, 54f

474 Index Photovoltaic-powered thermoelectric heat pumping solar air heaters (SAHs) (Continued ) airflow rate, 57 cumulative efficiency, 58 cumulative heat collection, 57 cumulative heat losses, 57 energy balance, 55f flat-plate SAH, 52e53 heat loss coefficient, 57 heat removal factor, 58 indoor experiments energy efficiency, 60e61, 60f estimated heat loss coefficient, 61, 61f heat collection, 59, 59f heat collection rate, 59e60, 60f heat loss factor, 61e62 setup, 56f temperature profiles, 58e59, 58f instantaneous thermal energy efficiency, 57e58 outdoor experiment airflow rate, 63e64 heat collection, 63f heat loss coefficient and heat losses, 63f irradiance, 62f setup, 55e56, 56f performance parameters, 55 simulated irradiance, 55 solar air heater (SAH) materials, 53t solar collector, 52f solar energy profile, 55 TE and PV modules specifications, 54t temperature difference, 56 thermal collector, 53f Photovoltaic system (PVS) control methods, 118e120 energy production, 109 field tests, 107e108 grid-connected generator, 107 grid tied system, 113e114, 114f models Cenerg model, 118 double exponential real model (DERM), 116e117 mathematical models, 115 Sandia model, 117e118 single exponential real model (SERM), 115e116 panel configuration structures, 110f photovoltaic cells technologies crystalline silicon cells, 110e111, 111f

inorganic thin film silicon and amorphous silicon PV cells, 111e112, 111f third generation, 112, 112f stand-alone system, 107 static and dynamic parameters extraction, 118 topologies, 113 total installed capacity, 4f Porous media solar air heaters (SAHs), 47f Pyrolysis, 140, 189e190

Q Quadrature voltage, 83 Quartz capillary reactor, 198, 200f

R Radiation heat loss, 339 Reactive current control, delta inverter, 90 Renewable energy, 449e450 Renewable energy policy challenges economic challenges, 455e457, 459te460t environmental challenges, 458e459, 459te460t new green jobs creation, 457 PESTEL analysis, 454e455 political challenges, 455, 459te460t social challenges, 457e458, 459te460t sustainability, 454 technical challenges, 458, 459te460t Renewable energy sources (RES), 107 energy planning, 451 environmental impacts, 450 Jordan, 235e237 Palestine, 238 sustainable development, 450e451 Root Mean Squared Error (RMSE), 401e402 Rosemanowes Quarry (United Kingdom) HDR project, 284

S Sandia model, 117e118 Schumann’s model, 362e363 Seebeck effect, 49 Sensible-heat thermocline packed-bed (SHTPB) system multilayered sensible-heat thermocline, 350e351

Index single-layered sensible-heat thermocline, 348e350 Sensible material fillers, 329e330, 329t Shatter index [SI], 147e148 Single-diode representation, electrical model, 115f Single exponential real model (SERM) current and voltage evolution, 115 diode saturation current, 115e116 single-diode representation, 115f Single-layered sensible-heat thermocline, 348e350 Smart grid framework, long-term load forecasting. See Electric load forecasting (ELF) Solar air heaters (SAHs) design, 45e49 energy efficiency, 47 energy storage, 46 exergy efficiency, 47 glazing, 46 heat transfer, 46 modified absorbing surface, 47f performance improvement. See Photovoltaic-powered thermoelectric heat pumping solar air heaters (SAHs) phase change materials (PCMs), 46 photovoltaic thermal-thermoelectric (PVT) air collector mass flow rate, 48 sketch, 48f steady-state simulation models, 49 roughness, 46 surface modification, 46e47 V-corrugated surface, 47f Solar energy, 449e450 Solar energy markets, 4 Solar energy system designs, 45e49 Solar system classification, 5f Solar thermal (ST) collectors absorber coating, 6 bibliometric analysis, 7e8 classification, 5 conventional nanofluids (CNF), 7 electrodeposition, 6 enhancement, 5e8 heat transfer fluid (HTF), 7 nanofluid, 6 total installed capacity, 4f Solar tracking systems, 113, 113f Solid-liquid phase change material (PCM) fillers, 332t

475

Soultz-sous-Foreˆts European research project, 279e281. See also Enhanced geothermal system (EGS) Specific fuel consumption (SFC), 174 Square-corrugated surface solar air heaters (SAHs), 47f StefaneBoltzmann law, 339 Stratification number (Str), 340 Supercritical water gasification, hydrogen production biomass, 192e195, 196t agro-food residues, 195, 195f cellulose, 192e194, 194f hemicellulose, 194, 194f lignins, 194, 194f maple sawdust, 192 critical temperature and pressure, 190 hydrogen consumption reactions, 197 methanation and hydrogenation reactions, 197 operating parameters catalysts, 210e215 feed concentration, 205e207 pressure, 208e210 residence time, 207e208 temperature, 203e204 reactors batch process, 198e199 continuous process, 199e202 continuous tubular reactor, 201f fluidized bed reactor, 202f hydrothermal gasification, 198f pilot scale process, 202e203 steam reforming, 196 supercritical state, 190 supercritical water properties advantage, 192 diffusion coefficient, 190e191 physical properties, 192, 193t water density, 191e192 water phase diagram, 191f Water Gas Shift, 197 Support vector machines (SVMs), 389

T Tank diameter-to-height ratio, 344 Thermal energy, 449e450 Thermocline packed bed thermal energy storage system charging and discharging, 327f

476 Index Thermocline packed bed thermal energy storage system (Continued ) concentrated solar power (CSP) plant applications, 325e326, 326f cost of materials, 334t energy demand, 325 experimental validation cases, 366e371, 369t geometrical parameters capsule shell thickness, 347 flow diffuser and buffer and inlet position, 347 particle shape, 345, 346f particle size, 345 porosity and packing structure, 345 tank diameter-to-height ratio, 344 heat transfer fluids (HTFs), 333e334, 336t heterogeneous-heat thermocline packed-bed (HHTPB) system, 357e360 latent-heat thermocline packed-bed (LHTPB) system, 351e357 numerical models, 367te368t assumptions, 360 single-phase model, 361e362 three-phase model, 364e366 two-phase models, 362e364 one-tank system, 326e327 operational parameters, 343e344 performance evaluation cost, 342 global thermodynamic efficiencies, 341e342 heat loss, 337e340 indicators, 335e342, 338t pressure drop, 335e337 thermal stratification level, 340e341 physical phenomena, 327e328 renewable power needs, 325 sensible-heat thermocline packed-bed (SHTPB) system, 348e351 single-media systems, 325e326 solar energy, 325 solid fillers phase change material fillers, 330e333 sensible material fillers, 329e330, 329t thermal energy storage (TES) system, 325 thermocline degradation, 327 two-tank system, 326e327 types, 347e360, 348f wall and insulation, 334e335

Thermocline thickness, 341 Thermoelectric generators (TEGs), 50 Thermoelectric-integrated solar energy systems hybrid PV-TEM system cooling, 50, 51f hybridization, 52 power generation, 50, 50f solar air heaters (SAHs). See Photovoltaic-powered thermoelectric heat pumping solar air heaters (SAHs) structure, 51e52 supply and control, 51f Peltier devices, 49 Seebeck effect, 49 thermoelectric modules (TEMs), 49 Thermoelectric modules (TEMs), 49 Thermogravimetric analysis, pellets, 148 Thermophysical properties common tank body materials, 337t heat transfer fluids (HTFs), 336t solid-liquid PCM fillers, 332t Thin film photovoltaic (PV) cells, 111e112, 111f Three-phase model one- and two-dimension three-phase dispersion-concentric model (1,2D-3P D-C), 365e366 one-dimension three-phase (1D-3P) model, 364e365 two-dimension three-phase (2D-3P) model, 365 Torrefaction, 154 Two-dimension one-phase (2D-1P), 362 Two-dimension two-phase model (2D-2P), 363 Two-diode model, 121, 121f Two phase models one- and two-dimension two-phase dispersion-concentric model (1,2D-2P D-C), 363e364 one-dimension two-phase Schumann’s model, 362e363 two-dimension two-phase model (2D-2P), 363

U United Nations Environment Program (UNEP), 451e452

Index

V V-corrugated surface solar air heaters (SAHs), 47f VERENA type pilot flow sheet, 202e203, 203f Voltage source inverter (VSI) current control methods ab stationary reference frame, 437e438 control principle, 435 conventional power circuit, 435f double dq synchronous reference frame, 435e437 features, 442t finite control set model predictive control, 438e442 voltage sags active and reactive power oscillations, 425 characteristics and propagation, 422, 423t delta/star connection, transformer, 420e421 duration, 417 equivalent circuit, 419f Fortescue transformation matrix, 418, 420e422 phasor diagram, 420, 421fe423f propagation phenomenon, 417 sag parameter, 419 sequence network interconnection, 419, 420f transient overcurrent peaks, 425 unbalanced, 419 voltage components, fault point, 419 voltage source inverter (VSI), 418, 418f voltage unbalance factor, 422e424, 424f voltage support oriented strategy constraints and formulation, 427e430 injected reactive power and grid current, 427e430, 433e435 purely inductive grid impedance, 425e430 resistive-inductive grid impedance, 431e435

W Wall heat storage/release, thermocline tank, 339e340, 340f

477

Water-based nanofluids, 10e11 Wind energy, 449e450 Jordan annual mean and cubic wind speed, 242, 242t electrical industry, 263 energy cost, 246, 248f energy flux, 242t energy production, 246e249, 249t mean monthly and annual wind speed, 241t mean power density, 242, 242f meteorological wind speed data, 249e250 National Renewable Energy Action Plan (NREAP), 264 pilot and commercial projects, 257e262 Rayleigh parameters, 246t theoretical capacity factor, 248f Weibull and Rayleigh distributions, 245e246, 246f Weibull parameters, 247t wind map, 240, 240f wind turbine models, 242, 243t, 245, 245f Palestine annual mean, 256t average wind speed and power density, 254e256, 256t Gamesa G128e4.5 MW turbine, 255t Gaza strip, 252e253, 252f literature review, 257, 258t locations, 251 monthly wind speed, 251fe252f numerical weather prediction model, 251 power and energy densities, 256t and power density, Jerusalem, 257f renewable energy strategy, 264, 264t simulation study, 251e252 Weibull parameters, 250, 250t, 253f, 256t wind energy projects, 262e263 wind resources, 251 Wood combustion process, 140, 141f

X Xilinx System Generator (XSG) tools, 108

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