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

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.