About the Book
        
        Microgrids  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.
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
About the Author : 
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.