Microgrids
Wiley-IEEE Press (Verlag)
978-1-119-89085-0 (ISBN)
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
| Erscheinungsdatum | 01.03.2024 |
|---|---|
| Reihe/Serie | IEEE Press Series on Power and Energy Systems |
| Sprache | englisch |
| Gewicht | 1964 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Maschinenbau | |
| ISBN-10 | 1-119-89085-3 / 1119890853 |
| ISBN-13 | 978-1-119-89085-0 / 9781119890850 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
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