Microgrids : theory and practice / edited by Peng Zhang.

Contributor(s): Zhang, Peng, Dr [editor.]
Language: English Series: IEEE Press series on power and energy systems: 128.Publisher: Hoboken, New Jersey : John Wiley & Sons, Inc., [2024]Copyright date: ©2024Description: 1 online resource (xli, 896 pages) : illustrations (chiefly color)Content type: text Media type: computer Carrier type: online resourceISBN: 9781119890850; 9781119890881; 1119890888; 9781119890874; 111989087X; 9781119890867; 1119890861Subject(s): Microgrids (Smart power grids)Genre/Form: Electronic books.Additional physical formats: Print version:: MicrogridsDDC classification: 621.31 LOC classification: TK3105 | .M557 2024Online resources: Full text is available at Wiley Online Library Click here to view
Contents:
Table of Contents About the Editor xxix List of Contributors xxxi Preface xxxix Acknowledgments xli 1 Introduction 1 Peng Zhang 1.1 Background 1 1.2 Reader’s Manual 2 2 AI-Grid: AI-Enabled, Smart Programmable Microgrids 7 Peng Zhang, Yifan Zhou, Scott A. Smolka, Scott D. Stoller, Xin Wang, Rong Zhao, Tianyun Ling, Yucheng Xing, Shouvik Roy, and Amol Damare 2.1 Introduction 7 2.2 AI-Grid Platform 8 2.3 AI-Enabled, Provably Resilient NM Operations 9 2.4 Resilient Modeling and Prediction of NM States Under Uncertainty 12 2.5 Runtime Safety and Security Assurance for AI-Grid 20 2.6 Software Platform for AI-Grid 41 2.7 AI-Grid for Grid Modernization 55 2.8 Exercises 55 References 55 3 Distributed Power Flow and Continuation Power Flow for Steady-State Analysis of Microgrids 59 Fei Feng, Peng Zhang, and Yifan Zhou 3.1 Background 59 3.2 Individual Microgrid Power Flow 60 3.3 Networked Microgrids Power Flow 64 3.4 Numerical Tests of Microgrid Power Flow 71 3.5 Exercises 78 References 78 4 State and Parameter Estimation for Microgrids 81 Yuzhang Lin, Yu Liu, Xiaonan Lu, and Heqing Huang 4.1 Introduction 81 4.2 State and Parameter Estimation for Inverter-Based Resources 82 4.3 State and Parameter Estimation for Network Components 94 4.4 Conclusion 102 4.5 Exercise 103 4.6 Acknowledgment 103 References 103 5 Eigenanalysis of Delayed Networked Microgrids 107 Lizhi Wang, Yifan Zhou, and Peng Zhang 5.1 Introduction 107 5.2 Formulation of Delayed NMs 107 5.3 Delayed NMs Eigenanalysis 110 5.4 Case Study 111 5.5 Conclusion 115 5.6 Exercises 115 References 116 6 AI-Enabled Dynamic Model Discovery of Networked Microgrids 119 Yifan Zhou and Peng Zhang 6.1 Preliminaries on ODE-Based Dynamical Modeling of NMs 119 6.2 Physics-Data-Integrated ODE Model of NMs 124 6.3 ODE-Net-Enabled Dynamic Model Discovery for Microgrids 126 6.4 Physics-Informed Learning for ODE-Net-Enabled Dynamic Models 130 6.5 Experiments 132 6.6 Summary 139 6.7 Exercises 139 References 139 7 Transient Stability Analysis for Microgrids with Grid-Forming Converters 141 Xuheng Lin and Ziang Zhang 7.1 Background 141 7.2 System Modeling 142 7.3 Metric for Transient Stability 146 7.4 Microgrid Transient Stability Analysis 147 7.5 Conclusion and Future Directions 151 7.6 Exercises 152 References 152 8 Learning-Based Transient Stability Assessment of Networked Microgrids 155 Tong Huang 8.1 Motivation 155 8.2 Networked Microgrid Dynamics 156 8.3 Learning a Lyapunov Function 158 8.4 Case Study 162 8.5 Summary 164 8.6 Exercises 164 References 164 9 Microgrid Protection 167 Rômulo G. Bainy and Brian K. Johnson 9.1 Introduction 167 9.2 Protection Fundamentals 167 9.3 Typical Microgrid Protection Schemes 180 9.4 Challenges Posed by Microgrids 182 9.5 Examples of Solutions in Practice 187 9.6 Summary 192 9.7 Exercises 192 References 194 10 Microgrids Resilience: Definition, Measures, and Algorithms 197 Zhaohong Bie and Yiheng Bian 10.1 Background of Resilience and the Role of Microgrids 197 10.2 Enhance Power System Resilience with Microgrids 199 10.3 Future Challenges 216 10.4 Exercises 216 References 217 11 In Situ Resilience Quantification for Microgrids 219 Priyanka Mishra, Peng Zhang, Scott A. Smolka, Scott D. Stoller, Yifan Zhou, Yacov A. Shamash, Douglas L. Van Bossuyt, and William W. Anderson Jr. 11.1 Introduction 219 11.2 STL-Enabled In Situ Resilience Evaluation 220 11.3 Case Study 222 11.4 Conclusion 227 11.5 Exercises 227 11.6 Acknowledgment 227 References 227 12 Distributed Voltage Regulation of Multiple Coupled Distributed Generation Units in DC Microgrids: An Output Regulation Approach 229 Tingyang Meng, Zongli Lin, Yan Wan, and Yacov A. Shamash 12.1 Introduction 229 12.2 Problem Statement 230 12.3 Review of Output Regulation Theory 232 12.4 Distributed Voltage Regulation in the Presence of Time-Varying Loads 239 12.5 Simulation Results 241 12.6 Conclusions 261 12.7 Exercises 261 12.8 Acknowledgment 262 References 262 13 Droop-Free Distributed Control for AC Microgrids 265 Sheik M. Mohiuddin and Junjian Qi 13.1 Cyber-Physical Microgrid Modeling 265 13.2 Hierarchical Control of Islanded Microgrid 267 13.3 Droop-Free Distributed Control with Proportional Power Sharing 271 13.4 Droop-Free Distributed Control with Voltage Profile Guarantees 273 13.5 Steady-State Analysis for the Control in Section 13.4 277 13.6 Microgrid Test System and Control Performance 279 13.7 Steady-State Performance Under Different Loading Conditions and Controller Settings 282 13.8 Exercises 284 References 284 14 Optimal Distributed Control of AC Microgrids 287 Sheik M. Mohiuddin and Junjian Qi 14.1 Optimization Problem for Secondary Control 287 14.2 Primal–Dual Gradient Based Distributed Solving Algorithm 291 14.3 Microgrid Test Systems 297 14.4 Control Performance on 4-DG System 298 14.5 Control Performance on IEEE 34-Bus System 300 14.6 Exercises 304 References 304 15 Cyber-Resilient Distributed Microgrid Control 307 Pouya Babahajiani and Peng Zhang 15.1 Push-Sum Enabled Resilient Microgrid Control 307 15.2 Employing Interacting Qubits for Distributed Microgrid Control 313 References 330 16 Programmable Crypto-Control for Networked Microgrids 335 Lizhi Wang, Peng Zhang, and Zefan Tang 16.1 Introduction 335 16.2 PCNMs and Privacy Requirements 336 16.3 Dynamic Encrypted Weighted Addition 340 16.4 DEWA Privacy Analysis 343 16.5 Case Studies 345 16.6 Conclusion 354 16.7 Exercises 355 References 355 17 AI-Enabled, Cooperative Control, and Optimization in Microgrids 359 Ning Zhang, Lingxiao Yang, and Qiuye Sun 17.1 Introduction 359 17.2 Energy Hub Model in Microgirds 360 17.3 Distributed Adaptive Cooperative Control in Microgrids 361 17.4 Optimal Energy Operation in Microgrids Based on Hybrid Reinforcement Learning 369 17.5 Conclusion 384 17.6 Exercises 384 References 385 18 DNN-Based EV Scheduling Learning for Transactive Control Framework 387 Aysegul Kahraman and Guangya Yang 18.1 Introduction 387 18.2 Transactive Control Formulation 388 18.3 Proposed Deep Neural Networks in Transactive Control 391 18.4 Case Study 392 18.5 Simulation Results and Discussion 394 18.6 Conclusion 396 18.7 Exercises 398 References 398 19 Resilient Sensing and Communication Architecture for Microgrid Management 401 Yuzhang Lin, Vinod M. Vokkarane, Md. Zahidul Islam, and Shamsun Nahar Edib 19.1 Introduction 401 19.2 Resilient Sensing and Communication Network Planning Against Multidomain Failures 404 19.3 Observability-Aware Network Routing for Fast and Resilient Microgrid Monitoring 412 19.4 Conclusion 420 19.5 Exercises 420 References 422 20 Resilient Networked Microgrids Against Unbounded Attacks 425 Shan Zuo, Tuncay Altun, Frank L. Lewis, and Ali Davoudi 20.1 Introduction 425 20.2 Adaptive Resilient Control of AC Microgrids Under Unbounded Actuator Attacks 427 20.3 Distributed Resilient Secondary Control of DC Microgrids Against Unbounded Attacks 437 20.4 Conclusion 449 20.5 Acknowledgment 451 20.6 Exercises 451 References 453 21 Quantum Security for Microgrids 457 Zefan Tang and Peng Zhang 21.1 Background 457 21.2 Quantum Communication for Microgrids 459 21.3 The QKD Simulator 463 21.4 Quantum-Secure Microgrid 467 21.5 Quantum-Secure NMs 471 21.6 Experimental Results 474 21.7 Future Perspectives 481 21.8 Summary 483 21.9 Exercises 483 References 484 22 Community Microgrid Dynamic and Power Quality Design Issues 487 Phil Barker, Tom Ortmeyer, and Clayton Burns 22.1 Introduction 487 22.2 Potsdam Resilient Microgrid Overview 488 22.3 Power Quality Parameters and Guidelines 490 22.4 Microgrid Analytical Methods 498 22.5 Analysis of Grid Parallel Microgrid Operation 499 22.6 Fault Current Contributions and Grounding 515 22.7 Microgrid Operation in Islanded Mode 529 22.8 Conclusions and Recommendations 551 22.9 Exercises 552 22.10 Acknowledgment 553 References 553 23 A Time of Energy Transition at Princeton University 555 Edward T. Borer, Jr. 23.1 Introduction 555 23.2 Cogeneration 556 23.3 The Magic of The Refrigeration Cycle 560 23.4 Capturing Heat, Not Wasting It 562 23.5 Multiple Forms of Energy Storage 565 23.6 Daily Thermal Storage – Chilled or Hot Water 569 23.7 Seasonal Thermal Storage – Geoexchange 571 23.8 Moving to Renewable Electricity as the Main Energy Input 574 23.9 Water Use Reduction 575 23.10 Closing Comments 577 24 Considerations for Digital Real-Time Simulation, Control-HIL, and Power-HIL in Microgrids/DER Studies 579 Juan F. Patarroyo, Joel Pfannschmidt, K. S. Amitkumar, Jean-Nicolas Paquin, and Wei li 24.1 Introduction 579 24.2 Considerations and Applications for Real-Time Simulation 580 24.3 Considerations and Applications of Control Hardware-in-the-Loop 593 24.4 Considerations and Applications of Power Hardware-in-the-Loop 602 24.5 Concluding Remarks 612 24.6 Exercises 612 References 613 25 Real-Time Simulations of Microgrids: Industrial Case Studies 615 Hui Ding, Xianghua Shi, Yi Qi, Christian Jegues, and Yi Zhang 25.1 Universal Converter Model Representation 615 25.2 Practical Microgrid Case 1: Aircraft Microgrid System 617 25.3 Practical Microgrid Case 2: Banshee Power System 620 25.4 Summary 630 25.5 Exercises 630 References 630 26 Coordinated Control of DC Microgrids 633 Weidong Xiao and Jacky Xiangyu Han 26.1 dc Droop 634 26.2 Hierarchical Control Scheme 639 26.3 Average Voltage Sharing 639 26.4 Bus Line Communication 645 26.5 Summary 651 26.6 Exercises 654 References 654 27 Foundations of Microgrid Resilience 655 William W. Anderson, Jr. and Douglas L. Van Bossuyt 27.1 Introduction 655 27.2 Background/Problem Statement 656 27.3 Defining Resilience 657 27.4 Resilience Analysis Examples 662 27.5 Discussion and Future Work 671 27.6 Conclusion 672 27.7 Acknowledgments 672 27.8 Exercises 673 References 677 28 Reliability Evaluation and Voltage Control Strategy of AC–DC Microgrid 681 Qianyu Zhao, Shouxiang Wang, Qi Liu, Zhixin Li, Xuan Wang, and Xuan Zhang 28.1 Introduction 681 28.2 Typical Topology Evaluation of AC–DC Microgrid 682 28.3 Coordinated Optimization for the AC–DC Microgrid 690 28.4 Case Study 696 28.5 Actual Project Construction 707 28.6 Conclusion 708 28.7 Exercises 710 References 710 29 Self-Organizing System of Sensors for Monitoring and Diagnostics of a Modern Microgrid 713 Michael Gouzman, Serge Luryi, Claran Martis, Yacov A. Shamash, and Alex Shevchenko 29.1 Introduction 713 29.2 Structures for Building Modern Microgrids 713 29.3 Requirements for the Monitoring and Diagnostics System of Modern Microgrids 715 29.4 Communication Systems in Microgrids 716 29.5 Sensors 717 29.6 Network Topology Identification Algorithm 721 29.7 Implementation 725 29.8 Exercise 725 References 727 30 Event Detection, Classification, and Location Identification with Synchro-Waveforms 729 Milad Izadi and Hamed Mohsenian-Rad 30.1 Introduction 729 30.2 Event Detection 732 30.3 Event Classification 737 30.4 Event Location Identification 743 30.5 Applications 756 30.6 Exercises 757 References 758 31 Traveling Wave Analysis in Microgrids 761 Soumitri Jena and Peng Zhang 31.1 Introduction 761 31.2 Background Theories 761 31.3 Challenges for TW Applications in Microgrid 763 31.4 Proposed Traveling Wave Protection Scheme 765 31.5 Performance Analysis 774 31.6 Conclusion 781 31.7 Exercises 781 References 783 32 Neuro-Dynamic State Estimation of Microgrids 785 Fei Feng, Yifan Zhou, and Peng Zhang 32.1 Background 785 32.2 Preliminaries of Physics-Based DSE 786 32.3 Neuro-DSE Algorithm 786 32.4 Self-Refined Neuro-DSE 790 32.5 Numerical Tests of Neuro-DSE 792 32.6 Exercises 798 References 799 33 Hydrogen-Supported Microgrid toward Low-Carbon Energy Transition 801 Jianxiao Wang, Guannan He, and Jie Song 33.1 Introduction 801 33.2 Hydrogen Production in Microgrid Operation 802 33.3 Hydrogen Utilization in Microgrid Operation 805 33.4 Case Studies 810 33.5 Exercises 812 33.6 Acknowledgement 813 References 813 34 Sharing Economy in Microgrid 815 Jianxiao Wang, Feng Gao, Tiance Zhang, and Qing Xia 34.1 Introduction 815 34.2 Aggregation of Distributed Energy Resources in Energy Markets 816 34.3 Aggregation of Distributed Energy Resources in Energy and Capacity Markets 819 34.4 Case Studies 824 34.5 Exercises 829 34.6 Acknowledgement 830 References 830 35 Microgrid: A Pathway to Mitigate Greenhouse Impact of Rural Electrification 831 Jianxiao Wang, Haiwang Zhong, and Jing Dai 35.1 Introduction 831 35.2 System Model 832 35.3 Case Studies 838 35.4 Discussion 845 35.5 Exercises 846 35.6 Acknowledgement 847 References 847 36 Operations of Microgrids with Meshed Topology Under Uncertainty 849 Mikhail A. Bragin, Bing Yan, Akash Kumar, Nanpeng Yu, and Peng Zhang 36.1 Self-sufficiency and Sustainability of Microgrids Under Uncertainty 849 36.2 Microgrid Model: Proactive Operation Optimization Under Uncertainties 853 36.3 Solution Methodology 854 36.4 Conclusions 858 36.5 Exercises 859 References 860 37 Operation Optimization of Microgrids with Renewables 863 Bing Yan, Akash Kumar, and Peng Zhang 37.1 Introduction 863 37.2 Existing Work 864 37.3 Mathematical Modeling 865 37.4 Solution Methodology 870 37.5 Exercises 871 References 872 Index 875
Summary: "A microgrid is a decentralized group of electricity sources and loads that normally operates, connected to and synchronous with the traditional wide area synchronous grid (macrogrid), but is able to disconnect from the interconnected grid and to function autonomously in "island mode" as technical or economic conditions dictate. Another use case is the off-grid application, it is called an autonomous, stand-alone or isolated microgrid. These microgrids are best served by local energy sources where power transmission and distribution from a major centralized energy source is too far and costly to execute. They offer an option for rural electrification in remote areas and on smaller geographical islands. As a controllable entity, a microgrid can effectively integrate various sources of distributed generation (DG), especially renewable energy sources (RES)."-- Provided by publisher.
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Includes bibliographical references and index.

Table of Contents
About the Editor xxix

List of Contributors xxxi

Preface xxxix

Acknowledgments xli

1 Introduction 1
Peng Zhang

1.1 Background 1

1.2 Reader’s Manual 2

2 AI-Grid: AI-Enabled, Smart Programmable Microgrids 7
Peng Zhang, Yifan Zhou, Scott A. Smolka, Scott D. Stoller, Xin Wang, Rong Zhao, Tianyun Ling, Yucheng Xing, Shouvik Roy, and Amol Damare

2.1 Introduction 7

2.2 AI-Grid Platform 8

2.3 AI-Enabled, Provably Resilient NM Operations 9

2.4 Resilient Modeling and Prediction of NM States Under Uncertainty 12

2.5 Runtime Safety and Security Assurance for AI-Grid 20

2.6 Software Platform for AI-Grid 41

2.7 AI-Grid for Grid Modernization 55

2.8 Exercises 55

References 55

3 Distributed Power Flow and Continuation Power Flow for Steady-State Analysis of Microgrids 59
Fei Feng, Peng Zhang, and Yifan Zhou

3.1 Background 59

3.2 Individual Microgrid Power Flow 60

3.3 Networked Microgrids Power Flow 64

3.4 Numerical Tests of Microgrid Power Flow 71

3.5 Exercises 78

References 78

4 State and Parameter Estimation for Microgrids 81
Yuzhang Lin, Yu Liu, Xiaonan Lu, and Heqing Huang

4.1 Introduction 81

4.2 State and Parameter Estimation for Inverter-Based Resources 82

4.3 State and Parameter Estimation for Network Components 94

4.4 Conclusion 102

4.5 Exercise 103

4.6 Acknowledgment 103

References 103

5 Eigenanalysis of Delayed Networked Microgrids 107
Lizhi Wang, Yifan Zhou, and Peng Zhang

5.1 Introduction 107

5.2 Formulation of Delayed NMs 107

5.3 Delayed NMs Eigenanalysis 110

5.4 Case Study 111

5.5 Conclusion 115

5.6 Exercises 115

References 116

6 AI-Enabled Dynamic Model Discovery of Networked Microgrids 119
Yifan Zhou and Peng Zhang

6.1 Preliminaries on ODE-Based Dynamical Modeling of NMs 119

6.2 Physics-Data-Integrated ODE Model of NMs 124

6.3 ODE-Net-Enabled Dynamic Model Discovery for Microgrids 126

6.4 Physics-Informed Learning for ODE-Net-Enabled Dynamic Models 130

6.5 Experiments 132

6.6 Summary 139

6.7 Exercises 139

References 139

7 Transient Stability Analysis for Microgrids with Grid-Forming Converters 141
Xuheng Lin and Ziang Zhang

7.1 Background 141

7.2 System Modeling 142

7.3 Metric for Transient Stability 146

7.4 Microgrid Transient Stability Analysis 147

7.5 Conclusion and Future Directions 151

7.6 Exercises 152

References 152

8 Learning-Based Transient Stability Assessment of Networked Microgrids 155
Tong Huang

8.1 Motivation 155

8.2 Networked Microgrid Dynamics 156

8.3 Learning a Lyapunov Function 158

8.4 Case Study 162

8.5 Summary 164

8.6 Exercises 164

References 164

9 Microgrid Protection 167
Rômulo G. Bainy and Brian K. Johnson

9.1 Introduction 167

9.2 Protection Fundamentals 167

9.3 Typical Microgrid Protection Schemes 180

9.4 Challenges Posed by Microgrids 182

9.5 Examples of Solutions in Practice 187

9.6 Summary 192

9.7 Exercises 192

References 194

10 Microgrids Resilience: Definition, Measures, and Algorithms 197
Zhaohong Bie and Yiheng Bian

10.1 Background of Resilience and the Role of Microgrids 197

10.2 Enhance Power System Resilience with Microgrids 199

10.3 Future Challenges 216

10.4 Exercises 216

References 217

11 In Situ Resilience Quantification for Microgrids 219
Priyanka Mishra, Peng Zhang, Scott A. Smolka, Scott D. Stoller, Yifan Zhou, Yacov A. Shamash, Douglas L. Van Bossuyt, and William W. Anderson Jr.

11.1 Introduction 219

11.2 STL-Enabled In Situ Resilience Evaluation 220

11.3 Case Study 222

11.4 Conclusion 227

11.5 Exercises 227

11.6 Acknowledgment 227

References 227

12 Distributed Voltage Regulation of Multiple Coupled Distributed Generation Units in DC Microgrids: An Output Regulation Approach 229
Tingyang Meng, Zongli Lin, Yan Wan, and Yacov A. Shamash

12.1 Introduction 229

12.2 Problem Statement 230

12.3 Review of Output Regulation Theory 232

12.4 Distributed Voltage Regulation in the Presence of Time-Varying Loads 239

12.5 Simulation Results 241

12.6 Conclusions 261

12.7 Exercises 261

12.8 Acknowledgment 262

References 262

13 Droop-Free Distributed Control for AC Microgrids 265
Sheik M. Mohiuddin and Junjian Qi

13.1 Cyber-Physical Microgrid Modeling 265

13.2 Hierarchical Control of Islanded Microgrid 267

13.3 Droop-Free Distributed Control with Proportional Power Sharing 271

13.4 Droop-Free Distributed Control with Voltage Profile Guarantees 273

13.5 Steady-State Analysis for the Control in Section 13.4 277

13.6 Microgrid Test System and Control Performance 279

13.7 Steady-State Performance Under Different Loading Conditions and Controller Settings 282

13.8 Exercises 284

References 284

14 Optimal Distributed Control of AC Microgrids 287
Sheik M. Mohiuddin and Junjian Qi

14.1 Optimization Problem for Secondary Control 287

14.2 Primal–Dual Gradient Based Distributed Solving Algorithm 291

14.3 Microgrid Test Systems 297

14.4 Control Performance on 4-DG System 298

14.5 Control Performance on IEEE 34-Bus System 300

14.6 Exercises 304

References 304

15 Cyber-Resilient Distributed Microgrid Control 307
Pouya Babahajiani and Peng Zhang

15.1 Push-Sum Enabled Resilient Microgrid Control 307

15.2 Employing Interacting Qubits for Distributed Microgrid Control 313

References 330

16 Programmable Crypto-Control for Networked Microgrids 335
Lizhi Wang, Peng Zhang, and Zefan Tang

16.1 Introduction 335

16.2 PCNMs and Privacy Requirements 336

16.3 Dynamic Encrypted Weighted Addition 340

16.4 DEWA Privacy Analysis 343

16.5 Case Studies 345

16.6 Conclusion 354

16.7 Exercises 355

References 355

17 AI-Enabled, Cooperative Control, and Optimization in Microgrids 359
Ning Zhang, Lingxiao Yang, and Qiuye Sun

17.1 Introduction 359

17.2 Energy Hub Model in Microgirds 360

17.3 Distributed Adaptive Cooperative Control in Microgrids 361

17.4 Optimal Energy Operation in Microgrids Based on Hybrid Reinforcement Learning 369

17.5 Conclusion 384

17.6 Exercises 384

References 385

18 DNN-Based EV Scheduling Learning for Transactive Control Framework 387
Aysegul Kahraman and Guangya Yang

18.1 Introduction 387

18.2 Transactive Control Formulation 388

18.3 Proposed Deep Neural Networks in Transactive Control 391

18.4 Case Study 392

18.5 Simulation Results and Discussion 394

18.6 Conclusion 396

18.7 Exercises 398

References 398

19 Resilient Sensing and Communication Architecture for Microgrid Management 401
Yuzhang Lin, Vinod M. Vokkarane, Md. Zahidul Islam, and Shamsun Nahar Edib

19.1 Introduction 401

19.2 Resilient Sensing and Communication Network Planning Against Multidomain Failures 404

19.3 Observability-Aware Network Routing for Fast and Resilient Microgrid Monitoring 412

19.4 Conclusion 420

19.5 Exercises 420

References 422

20 Resilient Networked Microgrids Against Unbounded Attacks 425
Shan Zuo, Tuncay Altun, Frank L. Lewis, and Ali Davoudi

20.1 Introduction 425

20.2 Adaptive Resilient Control of AC Microgrids Under Unbounded Actuator Attacks 427

20.3 Distributed Resilient Secondary Control of DC Microgrids Against Unbounded Attacks 437

20.4 Conclusion 449

20.5 Acknowledgment 451

20.6 Exercises 451

References 453

21 Quantum Security for Microgrids 457
Zefan Tang and Peng Zhang

21.1 Background 457

21.2 Quantum Communication for Microgrids 459

21.3 The QKD Simulator 463

21.4 Quantum-Secure Microgrid 467

21.5 Quantum-Secure NMs 471

21.6 Experimental Results 474

21.7 Future Perspectives 481

21.8 Summary 483

21.9 Exercises 483

References 484

22 Community Microgrid Dynamic and Power Quality Design Issues 487
Phil Barker, Tom Ortmeyer, and Clayton Burns

22.1 Introduction 487

22.2 Potsdam Resilient Microgrid Overview 488

22.3 Power Quality Parameters and Guidelines 490

22.4 Microgrid Analytical Methods 498

22.5 Analysis of Grid Parallel Microgrid Operation 499

22.6 Fault Current Contributions and Grounding 515

22.7 Microgrid Operation in Islanded Mode 529

22.8 Conclusions and Recommendations 551

22.9 Exercises 552

22.10 Acknowledgment 553

References 553

23 A Time of Energy Transition at Princeton University 555
Edward T. Borer, Jr.

23.1 Introduction 555

23.2 Cogeneration 556

23.3 The Magic of The Refrigeration Cycle 560

23.4 Capturing Heat, Not Wasting It 562

23.5 Multiple Forms of Energy Storage 565

23.6 Daily Thermal Storage – Chilled or Hot Water 569

23.7 Seasonal Thermal Storage – Geoexchange 571

23.8 Moving to Renewable Electricity as the Main Energy Input 574

23.9 Water Use Reduction 575

23.10 Closing Comments 577

24 Considerations for Digital Real-Time Simulation, Control-HIL, and Power-HIL in Microgrids/DER Studies 579
Juan F. Patarroyo, Joel Pfannschmidt, K. S. Amitkumar, Jean-Nicolas Paquin, and Wei li

24.1 Introduction 579

24.2 Considerations and Applications for Real-Time Simulation 580

24.3 Considerations and Applications of Control Hardware-in-the-Loop 593

24.4 Considerations and Applications of Power Hardware-in-the-Loop 602

24.5 Concluding Remarks 612

24.6 Exercises 612

References 613

25 Real-Time Simulations of Microgrids: Industrial Case Studies 615
Hui Ding, Xianghua Shi, Yi Qi, Christian Jegues, and Yi Zhang

25.1 Universal Converter Model Representation 615

25.2 Practical Microgrid Case 1: Aircraft Microgrid System 617

25.3 Practical Microgrid Case 2: Banshee Power System 620

25.4 Summary 630

25.5 Exercises 630

References 630

26 Coordinated Control of DC Microgrids 633
Weidong Xiao and Jacky Xiangyu Han

26.1 dc Droop 634

26.2 Hierarchical Control Scheme 639

26.3 Average Voltage Sharing 639

26.4 Bus Line Communication 645

26.5 Summary 651

26.6 Exercises 654

References 654

27 Foundations of Microgrid Resilience 655
William W. Anderson, Jr. and Douglas L. Van Bossuyt

27.1 Introduction 655

27.2 Background/Problem Statement 656

27.3 Defining Resilience 657

27.4 Resilience Analysis Examples 662

27.5 Discussion and Future Work 671

27.6 Conclusion 672

27.7 Acknowledgments 672

27.8 Exercises 673

References 677

28 Reliability Evaluation and Voltage Control Strategy of AC–DC Microgrid 681
Qianyu Zhao, Shouxiang Wang, Qi Liu, Zhixin Li, Xuan Wang, and Xuan Zhang

28.1 Introduction 681

28.2 Typical Topology Evaluation of AC–DC Microgrid 682

28.3 Coordinated Optimization for the AC–DC Microgrid 690

28.4 Case Study 696

28.5 Actual Project Construction 707

28.6 Conclusion 708

28.7 Exercises 710

References 710

29 Self-Organizing System of Sensors for Monitoring and Diagnostics of a Modern Microgrid 713
Michael Gouzman, Serge Luryi, Claran Martis, Yacov A. Shamash, and Alex Shevchenko

29.1 Introduction 713

29.2 Structures for Building Modern Microgrids 713

29.3 Requirements for the Monitoring and Diagnostics System of Modern Microgrids 715

29.4 Communication Systems in Microgrids 716

29.5 Sensors 717

29.6 Network Topology Identification Algorithm 721

29.7 Implementation 725

29.8 Exercise 725

References 727

30 Event Detection, Classification, and Location Identification with Synchro-Waveforms 729
Milad Izadi and Hamed Mohsenian-Rad

30.1 Introduction 729

30.2 Event Detection 732

30.3 Event Classification 737

30.4 Event Location Identification 743

30.5 Applications 756

30.6 Exercises 757

References 758

31 Traveling Wave Analysis in Microgrids 761
Soumitri Jena and Peng Zhang

31.1 Introduction 761

31.2 Background Theories 761

31.3 Challenges for TW Applications in Microgrid 763

31.4 Proposed Traveling Wave Protection Scheme 765

31.5 Performance Analysis 774

31.6 Conclusion 781

31.7 Exercises 781

References 783

32 Neuro-Dynamic State Estimation of Microgrids 785
Fei Feng, Yifan Zhou, and Peng Zhang

32.1 Background 785

32.2 Preliminaries of Physics-Based DSE 786

32.3 Neuro-DSE Algorithm 786

32.4 Self-Refined Neuro-DSE 790

32.5 Numerical Tests of Neuro-DSE 792

32.6 Exercises 798

References 799

33 Hydrogen-Supported Microgrid toward Low-Carbon Energy Transition 801
Jianxiao Wang, Guannan He, and Jie Song

33.1 Introduction 801

33.2 Hydrogen Production in Microgrid Operation 802

33.3 Hydrogen Utilization in Microgrid Operation 805

33.4 Case Studies 810

33.5 Exercises 812

33.6 Acknowledgement 813

References 813

34 Sharing Economy in Microgrid 815
Jianxiao Wang, Feng Gao, Tiance Zhang, and Qing Xia

34.1 Introduction 815

34.2 Aggregation of Distributed Energy Resources in Energy Markets 816

34.3 Aggregation of Distributed Energy Resources in Energy and Capacity Markets 819

34.4 Case Studies 824

34.5 Exercises 829

34.6 Acknowledgement 830

References 830

35 Microgrid: A Pathway to Mitigate Greenhouse Impact of Rural Electrification 831
Jianxiao Wang, Haiwang Zhong, and Jing Dai

35.1 Introduction 831

35.2 System Model 832

35.3 Case Studies 838

35.4 Discussion 845

35.5 Exercises 846

35.6 Acknowledgement 847

References 847

36 Operations of Microgrids with Meshed Topology Under Uncertainty 849
Mikhail A. Bragin, Bing Yan, Akash Kumar, Nanpeng Yu, and Peng Zhang

36.1 Self-sufficiency and Sustainability of Microgrids Under Uncertainty 849

36.2 Microgrid Model: Proactive Operation Optimization Under Uncertainties 853

36.3 Solution Methodology 854

36.4 Conclusions 858

36.5 Exercises 859

References 860

37 Operation Optimization of Microgrids with Renewables 863
Bing Yan, Akash Kumar, and Peng Zhang

37.1 Introduction 863

37.2 Existing Work 864

37.3 Mathematical Modeling 865

37.4 Solution Methodology 870

37.5 Exercises 871

References 872

Index 875

"A microgrid is a decentralized group of electricity sources and loads that normally operates, connected to and synchronous with the traditional wide area synchronous grid (macrogrid), but is able to disconnect from the interconnected grid and to function autonomously in "island mode" as technical or economic conditions dictate. Another use case is the off-grid application, it is called an autonomous, stand-alone or isolated microgrid. These microgrids are best served by local energy sources where power transmission and distribution from a major centralized energy source is too far and costly to execute. They offer an option for rural electrification in remote areas and on smaller geographical islands. As a controllable entity, a microgrid can effectively integrate various sources of distributed generation (DG), especially renewable energy sources (RES)."-- Provided by publisher.

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