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Authoritative, highly comprehensive guide on how emerging technologies can address various challenges in different sectors of smart cyber-physical power systems
As the world shifts towards smarter and more resilient energy systems, cyber-physical power systems (CPSs) represent a critical step in modernizing the power infrastructure. Smart Cyber-Physical Power Systems, Volume 1: Fundamental Concepts, Challenges, and Solutions, offers an in-depth exploration of the fundamental concepts, structures, and major challenges that underlie these complex systems. It covers the essential theories and frameworks that drive the integration of digital technologies with physical power systems, including smart grids, microgrids, and the Internet of Energy.
This volume addresses a range of crucial topics, from global demand response strategies and microgrid architectures to smart energy management in cities and advanced distributed control strategies. Additionally, it highlights key challenges such as ensuring resiliency, protecting against cyberattacks, and maintaining reliability in the face of rapid technological advancements.
Experts from around the world contribute to this volume, sharing vital insights into the transformation of traditional power systems into adaptive, cyber-physical networks. Their focus on the growing importance of privacy, security, and data analytics makes this book a critical resource for anyone involved in power system research, offering essential tools to navigate and shape the future landscapes of energy systems.
Whether you're a researcher, engineer, or industry professional, this volume provides the foundational knowledge needed to understand the evolving landscape of smart cyber-physical power systems and the significant challenges they face.
Join us on a journey through the landscape of Smart Cyber-Physical Power Systems (CPPSs), where cutting-edge solutions meet the challenges of today and forge the energy paradigms of tomorrow, driven by AI/ML, Big Data, Blockchain, IoT, Quantum Computing, Information Theory, Edge Computing, Metaverse, DevOps, and more.
Ali Parizad, PhD, is a Postdoctoral Associate at the Advanced Research Institute (ARI) of Virginia Polytechnic Institute and State University, VA, USA. Leveraging his extensive academic background, he served as a Senior Data Scientist in the IDA Data Science & Machine Learning (DSML) Department at Shell Energy. He holds the position of Staff Power Systems Machine Learning Engineer at Thinklabs AI, where he tackles critical challenges in power systems with cutting-edge AI applications.
Hamid Reza Baghaee, PhD, is an Associate Research Professor at Amirkabir University of Technology, Tehran, Iran.
Saifur Rahman, PhD, is the founding director of the Advanced Research Institute at Virginia Tech, where he is the Joseph R. Loring Professor of Electrical and Computer Engineering.
About the Editors xxv
List of Contributors xxix
Foreword (John D. McDonald) xxxvii
Foreword (Massoud Amin) xxxix
Preface for Volume 1: Smart Cyber-Physical Power Systems: Fundamental Concepts, Challenges, and Solutions xliii
Acknowledgments xlv
1 Overview of Smart Cyber-Physical Power Systems: Fundamentals, Challenges, and Solutions 1Ali Parizad, Hamid Reza Baghaee, and Saifur Rahman
1.1 Introduction 1
1.2 Structural Overview and Roadmap of the Book 1
1.3 General Concepts of the Cyber-Physical Systems 7
1.4 Cyber-Physical Energy and Power Systems (CPEPSS) 16
1.5 From Conventional Distribution Networks to Smart Grids 21
1.6 Smart Grid Ecosystem (From Smart Buildings to Smart Grid) 42
1.7 Cybersecurity in Modern Power Systems 54
1.8 Conclusions 63
References 64
2 Global Demand Response Status: Potentials, Barriers, and Solutions 71Sanchari Deb, Elahe Doroudchi, Sergio Motta, Matti Aro, and Amir Safdarian
2.1 Background 71
2.2 Global Status of DR Programs 72
2.3 AI and ML Applications in DR 75
2.4 Case Study 77
2.5 Discussion 81
References 81
3 Smart Power/Energy Management and Optimization in Microgrids 85Talal Saleh, Omar Mohamed, Seyed Farhad Zandrazavi, and Miadreza Shafie-khah
3.1 Introduction 85
3.2 Materials and Methods 86
3.3 Simulation and Results 91
3.4 Discussion 94
3.5 Conclusions 95
References 96
4 Smart City Energy Infrastructure as a Cyber-Physical System of Systems: Planning, Operation, and Control Processes 99Mahdi Nozarian, Alireza Fereidunian, and Masoud Barati
4.1 Introduction 99
4.2 Cyber-Physical System of Systems 100
4.3 Cyber-Physical System of System Application Domains 103
4.4 Smart City Cyber-Physical System of Systems 106
4.5 Smart City Energy Cyber-Physical System of Systems 109
4.6 Planning, Operation, and Control Process in Smart City Energy Cyber-Physical System of Systems 112
4.7 Emergence in Smart City Energy Cyber-Physical System of Systems 115
4.8 Conclusions 116
References 117
5 Metaverse Local Energy Market in Smart City: A Descriptive Model and Strategic Development Analysis 125Mohammad Ghafourian Nasiri, Zahra Iranpour Mobarakeh, Mahdi Nozarian, Alireza Fereidunian, Sabrieh Choobkar, and Hossein Jobran
5.1 Introduction 125
5.2 Background 126
5.3 Concepts 127
5.4 Case Study: Local Energy Market in Metaverse 129
5.5 Discussions and Conclusions 132
References 133
6 Cooperative and Distributed Control Strategies of Microgrids 135Mahmood Jamali and Mahdieh S. Sadabadi
6.1 Introduction 135
6.2 Fault-Tolerant Secondary Control Schemes in Islanded AC Microgrids 137
6.3 Finite-Time Fault-Tolerant Voltage Control 140
6.4 Case Studies 143
6.5 Concluding Remarks 148
References 149
7 Interconnected Microgrid Systems: Architecture, Hierarchical Control, and Implementation 151Tung Lam Nguyen, Yu Wang, Ha Thi Nguyen, and Tran The Hoang
7.1 Introduction 151
7.2 Architecture 152
7.3 Hierarchical Control of Interconnected MGs 153
7.4 The Multi-Agent System 157
7.5 The Implementation on a Real-Time Cyber-Physical Testbed 158
7.6 Conclusions 164
References 165
8 Internet of Energy, and Internet of Microgrids (IoE, IoM) 167Jonatas Boas Leite and Mladen Kezunovic
8.1 Introduction 167
8.2 Interfacing of the IoT Node for Self-Healing Strategies 168
8.3 Performance Assessment Results 176
8.4 Concluding Remarks 183
References 183
9 Voltage Regulation and Reactive Power Optimization for Integration of Distributed Energy Resources into Smart Grids 187Firdous Ul Nazir, Bikash C. Pal, and Rabih A. Jabr
9.1 Introduction 187
9.2 Traditional Volt/Var Control 188
9.3 Network Model 189
9.4 Chance-Constrained Volt/Var Control 190
9.5 Solution Algorithm 192
9.6 Results 195
9.7 Approximate Load Models for Advanced VVC Functions 197
9.8 Binomial Approximation Method 198
9.9 Linear Regression Method 199
9.10 Results 200
9.11 Conservation Voltage Reduction 202
9.12 Conclusions 202
References 203
10 The Role of Data Analysis in Hosting Capacities of Distribution Power Systems for Electric Vehicles 207Alireza Ghadertootoonchi, Mehdi Davoudi, Mohaddeseh Koochaki, and Moein Moeini-Aghatie
Nomenclature 207
10.1 EVs' Power Demand Forecast Methods 208
10.2 Review of EVs' Energy Management Strategies 212
10.3 Uncertainties Regarding EVs and Their Impact on the Power Networks 217
10.4 Data Analyses Application in Technical Issues of EVs 225
10.5 Concluding Remarks 235
References 236
11 Energy Efficiency in Smart Buildings Through IoT Sensor Integration 247Saifur Rahman and Ali Parizad
11.1 Introduction 247
11.2 Building Automation Solution Landscape 252
11.3 Bemoss Tm Features 253
11.4 Targeted Buildings and Loads 256
11.5 BEMOSS TM Architecture 261
11.6 BEMOSS TM Auxiliary Functions 266
11.7 Multiple-protocol Interoperability 267
11.8 Test Results 268
11.9 BEMOSS TM Platform for Campus Applications 289
11.10 Conclusion 290
11.11 Exploring Other Capabilities of the BEMOSS TM Platform 290
References 290
12 Optimal Dispatch of Smart Energy System Based on Cyber-Physical-Social Integration 293Jizhong Zhu, Ziyu Chen, Wanli Wu, and Chenke He
12.1 Introduction 293
12.2 CPSS Model 294
12.3 The Cooperative Operation in V2G 302
12.4 Framework of a Charging Station with Battery Swapping Mode 307
12.5 Conclusion 313
References 313
13 Power Distribution Systems Self-Healing 315Konrad Schmitt, Manohar Chamana, Meisam Mahdavi, Stephen Bayne, and Luciane Neves
13.1 Introduction 315
13.2 Historical Notes 316
13.3 Self-Healing Concept 319
13.4 Mathematical Formulation 323
13.5 Case Studies 330
13.6 Concluding Remarks 338
References 339
14 Resiliency, Reliability, and Security of Cyber-Physical Power System 343Mohsen Chegnizadeh, Mahmoud Fotuhi-Firuzabad, and Sajjad Fatahian dehkordi
Abbreviations 343
14.1 Introduction and Motivation 344
14.2 Conceptual and Definitional Studies 346
14.3 Application of Machine Learning in Power Systems 350
14.4 Case Study 355
14.5 Conclusion 360
Acknowledgments 360
References 360
15 Cyberattacks on Power Systems 365Alfan Presekal, Vetrivel Subramaniam Rajkumar, Alexandru Stefanov, Kaikai Pan, and Peter Palensky
15.1 Introduction 365
15.2 Cyber Kill Chain 366
15.3 Review of Major Cyberattacks 368
15.4 Taxonomy of Cyberattacks on Power Grids 374
15.5 Impact of Cyberattacks on Power Grids 389
15.6 Study Case and Simulation Results 391
15.7 Conclusion 393
Acknowledgement 394
List of Acronyms 396
References 398
16 Vulnerabilities of Machine Learning Algorithms to Adversarial Attacks for Cyber-Physical Power Systems 405Tapadhir Das, Raj Mani Shukla, Mohammed Ben-Idris, and Shamik Sengupta
16.1 Introduction 405
16.2 Vulnerabilities of ML Algorithms to Adversarial Attacks 407
16.3 Theoretical Foundations and Applications of Adversarial Attacks 412
16.4 Attack Models Under Different Scenarios Including Full, Limited, and No Knowledge About the Target Model 414
16.5 Real-Life Practical Adversarial Example Generation and Implementation in CPPS 417
16.6 Protection Strategies Against Adversarial Attacks 418
16.7 Conclusion and Recommendation 421
References 422
17 Synchrophasor Data Anomaly Detection for Wide-Area Monitoring and Control in Cyber-Power Systems 425A.K. Srivastava, S. Pandey, A. Ahmed, S. Basumalik, and S.K. Sadanandan
17.1 Introduction 425
17.2 Synchrophasor-Based Wide-Area Monitoring and Control 426
17.3 Synchrophasor Data Flow, Anomalies, and Impacts 427
17.4 Synchrophasor Anomalies Detection and Classification (SyADC) 429
17.5 Quality-Aware Synchrophasor-Based Monitoring and Control Applications 441
17.6 Summary 445
Acknowledgements 446
References 446
18 Application of State Observers and Filters in Protection and Cyber-Security of Power Grids 451Mohammadmahdi Asghari, Amir Ameli, Mohsen Ghafouri, and Mohammad N. Uddin
18.1 Introduction 451
18.2 State-Space Model of Systems 452
18.3 Properties of State-Space Models 454
18.4 State Observers and Filters 455
18.5 Application of Observers and Filters in Improving the Authenticity and Accuracy of Measured Data 467
18.6 Case Study 1: Attack Detection and Identification for Automatic Generation Control Systems 469
18.7 Case Study 2: Developing Wide-Band Current Transformers for Traveling-wave-based Protection 480
18.8 Case Study 3: Fault Diagnosis in Transformers Using LPV Observers 489
18.9 Conclusion 498
References 498
19 Anomaly Detection and Mitigation in Cyber-Physical Power Systems Based on Hybrid Deep Learning and Attack Graphs 505Alfan Presekal, Alexandru Stefanov, Vetrivel Subramaniam Rajkumar, and Peter Palensky
Abbreviations 505
19.1 Power Grid Cyber Resilience 506
19.2 Operational Technologies and Secure Communication Protocols 508
19.3 Cyber-Physical System Co-Simulation and Cyber Ranges 512
19.4 Network Security Controls 516
19.5 Hybrid Deep Learning for Anomaly Detection in Power System OT Networks 521
19.6 Hybrid Deep Learning Model for Anomaly Detection 522
19.7 Attack Graph for Situational Awareness 525
19.8 Cyber Attack Case Studies 527
19.9 Conclusions 531
Acknowledgments 531
References 532
20 Attack Detection and Countermeasures at Edge Devices 539Fahim Ahmed and Md Tanvir Arafin
20.1 Introduction 539
20.2 Attack Surfaces for Edge Devices 540
20.3 Security Issues and Common Attacks in Edge Devices 543
20.4 Attack Detection Techniques and Countermeasures 547
20.5 Conclusions and Future Research Directions 550
Acknowledgments 550
References 551
21 Privacy-Preserving Outage Detection in Modern Distribution Grids: Challenges and Opportunities 555Chenhan Xiao, Yizheng Liao, and Yang Weng
21.1 Introduction 555
21.2 Preliminaries 557
21.3 Privacy-Aware Line Outage Detection with Boosted Performance 559
21.4 Validation on Extensive Outage Scenarios with Real-World Data 565
21.5 Conclusions 572
References 572
22 Transactive Energy Management and Distribution System Reform Using Market Concepts 575Amr A. Mohamed, Bala Venkatesh, Carlos Sabillon, and Ali Golriz
Nomenclature 575
22.1 Introduction 576
22.2 Proposed TEM Market Platform 578
22.3 Demonstrative Case Studies 583
22.4 Conclusion Remarks and Prospects for the Future 590
References 591
Appendix 22.A Line Segment Data of the 34-bus Test System (ohms) 593
23 Transactive Energy Systems in Decentralized Autonomous Renewable Energy Communities 597Riccardo Trevisan, Emilio Ghiani, Marco Galici, Susanna Mocci, and Fabrizio Pilo
23.1 Introduction 597
23.2 RECs as DAOs 599
23.3 Toward the Tokenization of the Governance 602
23.4 Conclusions 612
References 612
24 Transactive Coordination Paradigm for Efficient Charging Management of Plug-in Electric Vehicles in Future Distribution Networks 617Hossein Saber, Hossein Ranjbar, and Moein Moeini-Aghtaie
24.1 Introduction 617
24.2 Transportation Electrification 618
24.3 Demand-Side Management Approaches 620
24.4 Examples of TE Model Worldwide Projects 622
24.5 TE Paradigm in Charging Management of EVs 625
24.6 Conclusions and Future Works 630
References 631
25 Optimal Peer-to-Peer Energy Trading Using Machine Learning: Architecture, Strategies, and Algorithms 635Nadya Noorfatima and Jaesung Jung
25.1 Introduction 635
25.2 P2P Energy Trading Architecture 636
25.3 ml Operation in P2P Energy Trading 646
25.4 Simulation 650
25.5 Conclusion 654
References 654
26 Optimal Peer-to-Peer Power Sharing in DC Islanded Microgrids 657Rabia Khan and Noel N. Schulz
26.1 Introduction 657
26.2 Modeling of Islanded DC Microgrid System 659
26.3 Optimal Power Flow Problem Formulation of DC Islanded Microgrid System 662
26.4 Results and Discussion 664
26.5 Conclusion and Future Work 673
Acknowledgment 675
Bibliography 675
27 Blockchain-Based Energy Trading Employing Hyperledger and Anomaly Detection Algorithms 679Zejia Jing, Ali Parizad, and Saifur Rahman
27.1 Introduction 679
27.2 Literature Review 680
27.3 Anomaly Detection 688
27.4 Blockchain-Based Anomaly Detection Case Study 703
27.5 Conclusion 709
References 710
28 Optimal Coordination of VSC-Interfaced Subsystems to Safeguard the Frequency Performance of Cyber-Physical Power Systems 715Georgios Giannakopoulos, Arcadio Perilla Guerra, José Luis Rueda Torres, and Peter Palensky
28.1 Motivation and Scope of the Chapter 715
28.2 The HVDC-HVAC Cyber-Physical Test Power System 716
28.3 Statement of the Optimization of FFC for PEI 719
28.4 Solution by Mean-Variance Optimization 720
28.5 Simulation Analysis 722
28.6 Concluding Reflections 724
References 725
Index 727
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