Microgrids

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 xxixList of Contributors xxxiPreface xxxixAcknowledgments xli1 Introduction 1Peng Zhang1.1 Background 11.2 Reader’s Manual 22 AI-Grid: AI-Enabled, Smart Programmable Microgrids 7Peng Zhang, Yifan Zhou, Scott A. Smolka, Scott D. Stoller, Xin Wang, Rong Zhao, Tianyun Ling, Yucheng Xing, Shouvik Roy, and Amol Damare2.1 Introduction 72.2 AI-Grid Platform 82.3 AI-Enabled, Provably Resilient NM Operations 92.4 Resilient Modeling and Prediction of NM States Under Uncertainty 122.5 Runtime Safety and Security Assurance for AI-Grid 202.6 Software Platform for AI-Grid 412.7 AI-Grid for Grid Modernization 552.8 Exercises 55References 553 Distributed Power Flow and Continuation Power Flow for Steady-State Analysis of Microgrids 59Fei Feng, Peng Zhang, and Yifan Zhou3.1 Background 593.2 Individual Microgrid Power Flow 603.3 Networked Microgrids Power Flow 643.4 Numerical Tests of Microgrid Power Flow 713.5 Exercises 78References 784 State and Parameter Estimation for Microgrids 81Yuzhang Lin, Yu Liu, Xiaonan Lu, and Heqing Huang4.1 Introduction 814.2 State and Parameter Estimation for Inverter-Based Resources 824.3 State and Parameter Estimation for Network Components 944.4 Conclusion 1024.5 Exercise 1034.6 Acknowledgment 103References 1035 Eigenanalysis of Delayed Networked Microgrids 107Lizhi Wang, Yifan Zhou, and Peng Zhang5.1 Introduction 1075.2 Formulation of Delayed NMs 1075.3 Delayed NMs Eigenanalysis 1105.4 Case Study 1115.5 Conclusion 1155.6 Exercises 115References 1166 AI-Enabled Dynamic Model Discovery of Networked Microgrids 119Yifan Zhou and Peng Zhang6.1 Preliminaries on ODE-Based Dynamical Modeling of NMs 1196.2 Physics-Data-Integrated ODE Model of NMs 1246.3 ODE-Net-Enabled Dynamic Model Discovery for Microgrids 1266.4 Physics-Informed Learning for ODE-Net-Enabled Dynamic Models 1306.5 Experiments 1326.6 Summary 1396.7 Exercises 139References 1397 Transient Stability Analysis for Microgrids with Grid-Forming Converters 141Xuheng Lin and Ziang Zhang7.1 Background 1417.2 System Modeling 1427.3 Metric for Transient Stability 1467.4 Microgrid Transient Stability Analysis 1477.5 Conclusion and Future Directions 1517.6 Exercises 152References 1528 Learning-Based Transient Stability Assessment of Networked Microgrids 155Tong Huang8.1 Motivation 1558.2 Networked Microgrid Dynamics 1568.3 Learning a Lyapunov Function 1588.4 Case Study 1628.5 Summary 1648.6 Exercises 164References 1649 Microgrid Protection 167Rômulo G. Bainy and Brian K. Johnson9.1 Introduction 1679.2 Protection Fundamentals 1679.3 Typical Microgrid Protection Schemes 1809.4 Challenges Posed by Microgrids 1829.5 Examples of Solutions in Practice 1879.6 Summary 1929.7 Exercises 192References 19410 Microgrids Resilience: Definition, Measures, and Algorithms 197Zhaohong Bie and Yiheng Bian10.1 Background of Resilience and the Role of Microgrids 19710.2 Enhance Power System Resilience with Microgrids 19910.3 Future Challenges 21610.4 Exercises 216References 21711 In Situ Resilience Quantification for Microgrids 219Priyanka 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 21911.2 STL-Enabled In Situ Resilience Evaluation 22011.3 Case Study 22211.4 Conclusion 22711.5 Exercises 22711.6 Acknowledgment 227References 22712 Distributed Voltage Regulation of Multiple Coupled Distributed Generation Units in DC Microgrids: An Output Regulation Approach 229Tingyang Meng, Zongli Lin, Yan Wan, and Yacov A. Shamash12.1 Introduction 22912.2 Problem Statement 23012.3 Review of Output Regulation Theory 23212.4 Distributed Voltage Regulation in the Presence of Time-Varying Loads 23912.5 Simulation Results 24112.6 Conclusions 26112.7 Exercises 26112.8 Acknowledgment 262References 26213 Droop-Free Distributed Control for AC Microgrids 265Sheik M. Mohiuddin and Junjian Qi13.1 Cyber-Physical Microgrid Modeling 26513.2 Hierarchical Control of Islanded Microgrid 26713.3 Droop-Free Distributed Control with Proportional Power Sharing 27113.4 Droop-Free Distributed Control with Voltage Profile Guarantees 27313.5 Steady-State Analysis for the Control in Section 13.4 27713.6 Microgrid Test System and Control Performance 27913.7 Steady-State Performance Under Different Loading Conditions and Controller Settings 28213.8 Exercises 284References 28414 Optimal Distributed Control of AC Microgrids 287Sheik M. Mohiuddin and Junjian Qi14.1 Optimization Problem for Secondary Control 28714.2 Primal–Dual Gradient Based Distributed Solving Algorithm 29114.3 Microgrid Test Systems 29714.4 Control Performance on 4-DG System 29814.5 Control Performance on IEEE 34-Bus System 30014.6 Exercises 304References 30415 Cyber-Resilient Distributed Microgrid Control 307Pouya Babahajiani and Peng Zhang15.1 Push-Sum Enabled Resilient Microgrid Control 30715.2 Employing Interacting Qubits for Distributed Microgrid Control 313References 33016 Programmable Crypto-Control for Networked Microgrids 335Lizhi Wang, Peng Zhang, and Zefan Tang16.1 Introduction 33516.2 PCNMs and Privacy Requirements 33616.3 Dynamic Encrypted Weighted Addition 34016.4 DEWA Privacy Analysis 34316.5 Case Studies 34516.6 Conclusion 35416.7 Exercises 355References 35517 AI-Enabled, Cooperative Control, and Optimization in Microgrids 359Ning Zhang, Lingxiao Yang, and Qiuye Sun17.1 Introduction 35917.2 Energy Hub Model in Microgirds 36017.3 Distributed Adaptive Cooperative Control in Microgrids 36117.4 Optimal Energy Operation in Microgrids Based on Hybrid Reinforcement Learning 36917.5 Conclusion 38417.6 Exercises 384References 38518 DNN-Based EV Scheduling Learning for Transactive Control Framework 387Aysegul Kahraman and Guangya Yang18.1 Introduction 38718.2 Transactive Control Formulation 38818.3 Proposed Deep Neural Networks in Transactive Control 39118.4 Case Study 39218.5 Simulation Results and Discussion 39418.6 Conclusion 39618.7 Exercises 398References 39819 Resilient Sensing and Communication Architecture for Microgrid Management 401Yuzhang Lin, Vinod M. Vokkarane, Md. Zahidul Islam, and Shamsun Nahar Edib19.1 Introduction 40119.2 Resilient Sensing and Communication Network Planning Against Multidomain Failures 40419.3 Observability-Aware Network Routing for Fast and Resilient Microgrid Monitoring 41219.4 Conclusion 42019.5 Exercises 420References 42220 Resilient Networked Microgrids Against Unbounded Attacks 425Shan Zuo, Tuncay Altun, Frank L. Lewis, and Ali Davoudi20.1 Introduction 42520.2 Adaptive Resilient Control of AC Microgrids Under Unbounded Actuator Attacks 42720.3 Distributed Resilient Secondary Control of DC Microgrids Against Unbounded Attacks 43720.4 Conclusion 44920.5 Acknowledgment 45120.6 Exercises 451References 45321 Quantum Security for Microgrids 457Zefan Tang and Peng Zhang21.1 Background 45721.2 Quantum Communication for Microgrids 45921.3 The QKD Simulator 46321.4 Quantum-Secure Microgrid 46721.5 Quantum-Secure NMs 47121.6 Experimental Results 47421.7 Future Perspectives 48121.8 Summary 48321.9 Exercises 483References 48422 Community Microgrid Dynamic and Power Quality Design Issues 487Phil Barker, Tom Ortmeyer, and Clayton Burns22.1 Introduction 48722.2 Potsdam Resilient Microgrid Overview 48822.3 Power Quality Parameters and Guidelines 49022.4 Microgrid Analytical Methods 49822.5 Analysis of Grid Parallel Microgrid Operation 49922.6 Fault Current Contributions and Grounding 51522.7 Microgrid Operation in Islanded Mode 52922.8 Conclusions and Recommendations 55122.9 Exercises 55222.10 Acknowledgment 553References 55323 A Time of Energy Transition at Princeton University 555Edward T. Borer, Jr.23.1 Introduction 55523.2 Cogeneration 55623.3 The Magic of The Refrigeration Cycle 56023.4 Capturing Heat, Not Wasting It 56223.5 Multiple Forms of Energy Storage 56523.6 Daily Thermal Storage – Chilled or Hot Water 56923.7 Seasonal Thermal Storage – Geoexchange 57123.8 Moving to Renewable Electricity as the Main Energy Input 57423.9 Water Use Reduction 57523.10 Closing Comments 57724 Considerations for Digital Real-Time Simulation, Control-HIL, and Power-HIL in Microgrids/DER Studies 579Juan F. Patarroyo, Joel Pfannschmidt, K. S. Amitkumar, Jean-Nicolas Paquin, and Wei li24.1 Introduction 57924.2 Considerations and Applications for Real-Time Simulation 58024.3 Considerations and Applications of Control Hardware-in-the-Loop 59324.4 Considerations and Applications of Power Hardware-in-the-Loop 60224.5 Concluding Remarks 61224.6 Exercises 612References 61325 Real-Time Simulations of Microgrids: Industrial Case Studies 615Hui Ding, Xianghua Shi, Yi Qi, Christian Jegues, and Yi Zhang25.1 Universal Converter Model Representation 61525.2 Practical Microgrid Case 1: Aircraft Microgrid System 61725.3 Practical Microgrid Case 2: Banshee Power System 62025.4 Summary 63025.5 Exercises 630References 63026 Coordinated Control of DC Microgrids 633Weidong Xiao and Jacky Xiangyu Han26.1 dc Droop 63426.2 Hierarchical Control Scheme 63926.3 Average Voltage Sharing 63926.4 Bus Line Communication 64526.5 Summary 65126.6 Exercises 654References 65427 Foundations of Microgrid Resilience 655William W. Anderson, Jr. and Douglas L. Van Bossuyt27.1 Introduction 65527.2 Background/Problem Statement 65627.3 Defining Resilience 65727.4 Resilience Analysis Examples 66227.5 Discussion and Future Work 67127.6 Conclusion 67227.7 Acknowledgments 67227.8 Exercises 673References 67728 Reliability Evaluation and Voltage Control Strategy of AC–DC Microgrid 681Qianyu Zhao, Shouxiang Wang, Qi Liu, Zhixin Li, Xuan Wang, and Xuan Zhang28.1 Introduction 68128.2 Typical Topology Evaluation of AC–DC Microgrid 68228.3 Coordinated Optimization for the AC–DC Microgrid 69028.4 Case Study 69628.5 Actual Project Construction 70728.6 Conclusion 70828.7 Exercises 710References 71029 Self-Organizing System of Sensors for Monitoring and Diagnostics of a Modern Microgrid 713Michael Gouzman, Serge Luryi, Claran Martis, Yacov A. Shamash, and Alex Shevchenko29.1 Introduction 71329.2 Structures for Building Modern Microgrids 71329.3 Requirements for the Monitoring and Diagnostics System of Modern Microgrids 71529.4 Communication Systems in Microgrids 71629.5 Sensors 71729.6 Network Topology Identification Algorithm 72129.7 Implementation 72529.8 Exercise 725References 72730 Event Detection, Classification, and Location Identification with Synchro-Waveforms 729Milad Izadi and Hamed Mohsenian-Rad30.1 Introduction 72930.2 Event Detection 73230.3 Event Classification 73730.4 Event Location Identification 74330.5 Applications 75630.6 Exercises 757References 75831 Traveling Wave Analysis in Microgrids 761Soumitri Jena and Peng Zhang31.1 Introduction 76131.2 Background Theories 76131.3 Challenges for TW Applications in Microgrid 76331.4 Proposed Traveling Wave Protection Scheme 76531.5 Performance Analysis 77431.6 Conclusion 78131.7 Exercises 781References 78332 Neuro-Dynamic State Estimation of Microgrids 785Fei Feng, Yifan Zhou, and Peng Zhang32.1 Background 78532.2 Preliminaries of Physics-Based DSE 78632.3 Neuro-DSE Algorithm 78632.4 Self-Refined Neuro-DSE 79032.5 Numerical Tests of Neuro-DSE 79232.6 Exercises 798References 79933 Hydrogen-Supported Microgrid toward Low-Carbon Energy Transition 801Jianxiao Wang, Guannan He, and Jie Song33.1 Introduction 80133.2 Hydrogen Production in Microgrid Operation 80233.3 Hydrogen Utilization in Microgrid Operation 80533.4 Case Studies 81033.5 Exercises 81233.6 Acknowledgement 813References 81334 Sharing Economy in Microgrid 815Jianxiao Wang, Feng Gao, Tiance Zhang, and Qing Xia34.1 Introduction 81534.2 Aggregation of Distributed Energy Resources in Energy Markets 81634.3 Aggregation of Distributed Energy Resources in Energy and Capacity Markets 81934.4 Case Studies 82434.5 Exercises 82934.6 Acknowledgement 830References 83035 Microgrid: A Pathway to Mitigate Greenhouse Impact of Rural Electrification 831Jianxiao Wang, Haiwang Zhong, and Jing Dai35.1 Introduction 83135.2 System Model 83235.3 Case Studies 83835.4 Discussion 84535.5 Exercises 84635.6 Acknowledgement 847References 84736 Operations of Microgrids with Meshed Topology Under Uncertainty 849Mikhail A. Bragin, Bing Yan, Akash Kumar, Nanpeng Yu, and Peng Zhang36.1 Self-sufficiency and Sustainability of Microgrids Under Uncertainty 84936.2 Microgrid Model: Proactive Operation Optimization Under Uncertainties 85336.3 Solution Methodology 85436.4 Conclusions 85836.5 Exercises 859References 86037 Operation Optimization of Microgrids with Renewables 863Bing Yan, Akash Kumar, and Peng Zhang37.1 Introduction 86337.2 Existing Work 86437.3 Mathematical Modeling 86537.4 Solution Methodology 87037.5 Exercises 871References 872Index 875