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Microgrids
Theory and Practice
von Peng Zhang
Verlag: Wiley
Reihe: IEEE Press Power and Energy Sy
Gebundene Ausgabe
ISBN: 978-1-119-89085-0
Erschienen am 26.03.2024
Sprache: Englisch
Format: 254 mm [H] x 178 mm [B] x 49 mm [T]
Gewicht: 1837 Gramm
Umfang: 944 Seiten

Preis: 138,50 €
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Klappentext
Biografische Anmerkung
Inhaltsverzeichnis

Understand microgrids and networked microgrid systems

Microgrids are interconnected groups of energy sources that operate together, capable of connecting with a larger grid or operating independently as needed and network conditions require. They can be valuable sources of energy for geographically circumscribed areas with highly targeted energy needs, and for remote or rural areas where continuous connection with a larger grid is difficult. Microgrids' controllability makes them especially effective at incorporating renewable energy sources.

Microgrids: Theory and Practice introduces readers to the analysis, design, and operation of microgrids and larger networked systems that integrate them. It brings to bear both cutting-edge research into microgrid technology and years of industry experience in designing and operating microgrids. Its discussions of core subjects such as microgrid modeling, control, and optimization make it an essential short treatment, valuable for both academic and industrial study. Readers will acquire the skills needed to address existing problems and meet new ones as this crucial area of power engineering develops.

Microgrids: Theory and Practice also features:

  • Incorporation of new cyber-physical system technologies for enabling microgrids as resiliency resources
  • Theoretical treatment of a wide range of subjects including smart programmable microgrids, distributed and asynchronous optimization for microgrid dispatch, and AI-assisted microgrid protection
  • Practical discussion of real-time microgrids simulations, hybrid microgrid design, transition to renewable microgrid networks, and more

Microgrids: Theory and Practice is ideal as a textbook for graduate and advanced undergraduate courses in power engineering programs, and a valuable reference for power industry professionals looking to address the challenges posed by microgrids in their work.



Peng Zhang, Ph.D, is Professor of Electrical and Computer Engineering and an Affiliate Professor of Computer Science and Applied Mathematics and Statistics at Stony Brook University, New York. He is a Senior Member of the IEEE and has published widely on microgrids and networked microgrid systems.



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


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