Cao / Li / Liu Cyber-Physical Energy and Power Systems

Modeling, Analysis and Application
1. Auflage 2019
ISBN: 978-981-15-0062-6
Verlag: Springer Nature Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 224 Seiten

This book discusses recent advances in cyber-physical power systems (CPPS) in the modeling, analysis and applications of smart grid. It introduces a series of models, such as an analysis of interaction between the power grid and the communication network, differential protection in smart distribution systems, data flow for VLAN-based communication in substations, a co-simulation model for investigating the impacts of cyber-contingency and distributed control systems as well as the analytical techniques used in different parts of cyber physical energy systems. It also discusses methods of cyber-attack on power systems, particularly false data injection. The results presented are a comprehensive summary of the authors' original research conducted over a period of 5 years. The book is of interest to university researchers, R&D engineers and graduate students in power and energy systems.

Yijia Cao received the undergraduate degree from Xi'an Jiaotong University, Xi'an, China, in 1988, and the M.Sc. and Ph.D. degrees from the Huazhong University of Science and Technology (HUST), Wuhan, China, in 1991 and 1994, respectively. From 1994 to 2000, he was a Visiting Research Fellow and a Research Fellow with Loughborough University, Liverpool University, and the University of the West England, U.K. From 2000 to 2001, he was a Full Professor with HUST, and from 2001 to 2008, he was a Full Professor with Zhejiang University, China, where he was appointed as the Deputy Dean of the College of Electrical Engineering in 2005. He is currently a Full Professor and the Vice President of Hunan University, Changsha, China. Dr. Cao is an Associate Editor of IET Cyber-Physical Systems: Theory & Applications. His main research interests are smart grid dispatch, power system security and stability control, and the application of intelligent systems in power systems.
Yong Li received the B.Sc. degrees in 2004 from Hunan University, Changsha, China, where he performed the Ph.D. study due to December 2008. Since 2009, he worked as a research associate at the Institute of Energy Systems, Energy Efficiency and Energy Economics (ie3), TU Dortmund University, Dortmund, Germany, where he received his second Ph.D. degree in 2012. Since September 2012, he is a Research Fellow with The University of Queensland, Brisbane, Australia. Currently, he is a Full Professor of electrical engineering with Hunan University. Dr. Li is a member of the Editorial Board of IET Generation, Transmission, and Distribution and an Associate Editor of IET Power Electronics. His main research interests include power system stability analysis and control, ac/dc energy conversion systems and equipment, analysis and control of power quality, and HVDC and FACTS technologies.
Xuan Liu is is a professor at the College of Electrical and Information Engineering, Hunan University. His main research interests include power systems operation, optimization and security analysis.

Christian Rehtanz received the Diploma degree in electrical engineering in 1994 and the Ph.D. degree in 1997 from the TU Dortmund University, Dortmund, Germany. In 2000, he was with ABB Corporate Research, Switzerland and in 2003, he was the Head of Technology of the Global ABB Business Area Power Systems. In 2005, he was the Director of ABB Corporate Research in China. Since 2007, he has been a Full Professor and the Head of Institute of Energy Systems, Energy Efficiency and Energy Economics, TU Dortmund University. His research activities include technologies for transmission and distribution network enhancement and congestion relief like stability assessment, wide-area monitoring, protection, and coordinated FACTS- and HVDC-control.

Autoren/Hrsg.

Cao, Yijia

Li, Yong

Liu, Xuan

Rehtanz, Christian

Inhaltsverzeichnis

1;Preface;5
1.1;Outlines;6
2;Acknowledgements;9
3;Contents;10
4;1 Introduction;16
4.1;1.1 Status Quo and Trends of the Fusion of Cyber and Power Systems;16
4.2;1.2 Simulation and Evaluation Methods and Its Application in CPEPS;18
4.2.1;1.2.1 Power, Communication, and Information System Simulation;19
4.2.2;1.2.2 Simulation Control;20
4.3;1.3 Interaction of CPEPS and Related Analysis Methods;21
4.3.1;1.3.1 Interaction Between Energy and Information Flows;21
4.3.2;1.3.2 Analysis Methods;22
4.4;1.4 Challenges of Power System Control and Protection in CPEPS;24
4.5;1.5 Challenges of Cyber Systems in CPEPS;25
4.5.1;1.5.1 Mass Data Processing and Cluster Analysis;25
4.5.2;1.5.2 Architecture of Communication Network;26
4.5.3;1.5.3 Information Transmission Technology;27
4.5.4;1.5.4 Security of CPEPS;27
4.6;1.6 Summary;28
4.7;References;28
5;2 Modeling and Analysis Techniques of Interdependent Network;31
5.1;2.1 Overview of Cascading Failure in Interdependent Network;31
5.2;2.2 Modeling for Interdependent Network;32
5.3;2.3 Model for Communication Network;35
5.3.1;2.3.1 Complex Network Background;35
5.3.2;2.3.2 Topological Models of Communication Network;36
5.3.3;2.3.3 Information Network Routing Strategy;39
5.4;2.4 Analysis of Blackout Caused by Interdependent Network;40
5.4.1;2.4.1 Cascading Failure Analysis Based on Interdependent Network;40
5.4.2;2.4.2 Dynamic Power Flow in Power System;41
5.4.3;2.4.3 Cascading Failure Simulation;43
5.5;2.5 Case Studies;44
5.6;2.6 Summary;48
5.7;References;48
6;3 Cascading Failure Analysis of Cyber-Physical Power System with Multiple Interdependency and Control Threshold;50
6.1;3.1 Introduction;50
6.2;3.2 Modeling of the Cascading Failure in CPEPS with Control Threshold;52
6.2.1;3.2.1 Cascading Failure with One-to-Multiple Interdependency;52
6.2.2;3.2.2 Cascading Failure with Control Threshold;54
6.3;3.3 Robustness Evaluation of CPEPS in Cascading Failure;55
6.4;3.4 Case Studies;59
6.4.1;3.4.1 Impacts of Different Interdependent Links;60
6.4.2;3.4.2 Impacts of Different Control Threshold;62
6.5;3.5 Summary;65
6.6;References;65
7;4 Impacts of EPON-Based Communication Networks on Differential Protection of Smart Distribution Networks;68
7.1;4.1 Overview of Differential Protection Algorithms;69
7.1.1;4.1.1 Principle of Current Differential Protection (CDP);69
7.1.2;4.1.2 Principle of Directional Comparison Pilot Protection;70
7.1.3;4.1.3 Principle of Backup Differential Protection;71
7.2;4.2 Calculation Process of Differential Protection Based on EPON;72
7.2.1;4.2.1 Calculation Process;72
7.2.2;4.2.2 Long Distance Communication of EPON;72
7.2.3;4.2.3 Communication Delay;72
7.3;4.3 Impact Analysis of EPON on Differential Protection;74
7.3.1;4.3.1 Impact Paths of EPON on Differential Protection;74
7.3.2;4.3.2 Impact of Time Synchronization Error;74
7.3.3;4.3.3 Impact of Polling Period;78
7.4;4.4 Modeling of Physical and Communication System;78
7.5;4.5 Impact Analysis by Co-simulation;81
7.5.1;4.5.1 Case 1: Phase-to-Phase Short-Circuit Fault;81
7.5.2;4.5.2 Case 2: Phase-to-Ground High-Impedance Fault;83
7.6;4.6 Summary;84
7.7;References;85
8;5 Modeling and Simulation of Data Flow for VLAN-Based Substation Communication System;87
8.1;5.1 Introduction of VLAN Technology;87
8.2;5.2 Theoretical Models of Data Flow;89
8.2.1;5.2.1 Modeling for Cyclic Data Flow;89
8.2.2;5.2.2 Modeling for Stochastic Data Flow;91
8.2.3;5.2.3 Modeling for Burst Data Flow;92
8.3;5.3 Analysis of Data Flow in a Substation;94
8.3.1;5.3.1 Typical Structure for Substation System;94
8.3.2;5.3.2 Data Flow for Substation Communication System;95
8.4;5.4 Case Studies;99
8.4.1;5.4.1 Case I: Evaluation of VLAN Scheme;100
8.4.2;5.4.2 Case II: Impacts of System Fault on Network Performance;104
8.4.3;5.4.3 Case III: Comparison of Ring and Star Topologies;106
8.4.4;5.4.4 Case IV: Impacts of Ring Broken on Network Performance;108
8.5;5.5 Summary;112
8.6;References;112
9;6 Reliability Analysis of Cyber-Physical Systems in Substation;114
9.1;6.1 Interactions Between Cyber Layer and Physical Layer in Substation;114
9.1.1;6.1.1 Simplified Model of the Substation System;115
9.1.2;6.1.2 Interaction Framework of the Cyber-Physical Substation;116
9.2;6.2 Model Quantifying the Interactions;117
9.3;6.3 Reliability Analysis of the Cyber-Physical Substation;119
9.3.1;6.3.1 Indices of Cyber-Physical Substation Reliability;119
9.3.2;6.3.2 Reliability Simulation Method;119
9.4;6.4 Case Studies;120
9.4.1;6.4.1 CPIM of the Reliability the Cyber-Physical Substation;120
9.4.2;6.4.2 Reliability Analysis Results;126
9.4.3;6.4.3 Effects of Delay Rates;126
9.5;6.5 Summary;127
9.6;References;128
10;7 Self-sustainable Community of Electricity Prosumers in Distribution System;129
10.1;7.1 Self-sustainable Community for Electricity Prosumer;129
10.1.1;7.1.1 Characteristics of Self-sustainable Community for Electricity Prosumer;129
10.2;7.2 Simulation Framework for Self-sustainable Prosumer-Based Energy Community;131
10.2.1;7.2.1 Framework of Self-sustainable Community Simulation;131
10.2.2;7.2.2 Multi-agents Simulation Structure for Distribution Network;133
10.3;7.3 Modeling for Micro-player;134
10.3.1;7.3.1 Modeling for Prosumer’s Physical Behavior;134
10.3.2;7.3.2 Modeling for Prosumer’s Social Behavior;136
10.3.3;7.3.3 Modeling for Prosumer’s Self-organized Trade;137
10.3.4;7.3.4 Modeling for Participation to Local Community Market;138
10.4;7.4 Modeling for Macro-player;139
10.5;7.5 Case Studies;141
10.5.1;7.5.1 Impacts of Different Balancing Premium Schemes;142
10.5.2;7.5.2 The Impacts of Prosumer’s Inherent Characteristics;145
10.6;7.6 Summary;146
10.7;References;147
11;8 Simplified Co-simulation Model for Investigating Impacts of Cyber-Contingency;149
11.1;8.1 Overview of Simulation Method;149
11.2;8.2 Impacts of Cyber Contingencies;151
11.2.1;8.2.1 Classification of Cyber Contingencies;152
11.2.2;8.2.2 End-to-End Features of Cyber Contingencies;153
11.3;8.3 Information Flow-Based Co-simulation Model;154
11.3.1;8.3.1 Power, Decision-Making and Sensing and Communication Layers’ Simulation;154
11.3.2;8.3.2 Time Synchronization and Data Exchange of Simulation;158
11.3.3;8.3.3 Assessment of Cyber Contingencies;159
11.4;8.4 Case Studies;160
11.4.1;8.4.1 Verifying Simulation Method of Transmitted Data;161
11.4.2;8.4.2 Cyber-Contingency Assessment;166
11.5;8.5 Summary;169
11.6;References;170
12;9 JADE-Based Information Physical System Co-simulation Environment for Smart Distribution Networks;172
12.1;9.1 Distributed Control Joint Simulation Environment for Distribution Network;173
12.1.1;9.1.1 Architecture;173
12.1.2;9.1.2 Time Synchronization Mechanism;174
12.1.3;9.1.3 Processing of Event Chain;175
12.2;9.2 Description of the Design Methods in Distributed Controllers;176
12.2.1;9.2.1 Simulation Environment of Distributed Controller;176
12.2.2;9.2.2 Implementation of Controller;177
12.2.3;9.2.3 Negotiation Between Controllers;178
12.3;9.3 Case Studies;179
12.3.1;9.3.1 A Distributed Protection Algorithm Based on Local Outlier Factor;179
12.3.2;9.3.2 Description of Co-simulation;180
12.3.3;9.3.3 Performance Validation;181
12.4;9.4 Summary;184
12.5;References;184
13;10 Local False Data Injection Attacks with Incomplete Network Information;186
13.1;10.1 False Data Injection for State Estimation;186
13.1.1;10.1.1 State Estimation of Power System;187
13.1.2;10.1.2 Complex Network Background;188
13.2;10.2 Modeling of Local Data Attacks;190
13.2.1;10.2.1 Related Work;190
13.2.2;10.2.2 New Modeling of False Data Injection Attacks;191
13.3;10.3 Impacts of Network Connectivity;195
13.3.1;10.3.1 Disconnection Case 1;196
13.3.2;10.3.2 Disconnection Case 2;196
13.3.3;10.3.3 Disconnection Case 3;197
13.4;10.4 Feasibility of Attack Vectors;197
13.5;10.5 Case Studies;201
13.6;10.6 Summary;207
13.7;References;207
14;11 Optimal Attack Strategy on Power System;209
14.1;11.1 Definitions of Terms;209
14.2;11.2 Modeling of Attacking Regions;210
14.2.1;11.2.1 Definition of LR Attacks;210
14.3;11.3 Optimal Attacking Region;213
14.3.1;11.3.1 Algorithm of Determining a Feasible Attacking;215
14.3.2;11.3.2 Expansion Strategy;216
14.3.3;11.3.3 Determine Attack Measurements;216
14.4;11.4 Case Studies;217
14.4.1;11.4.1 Case 1: The Attacker Intends to Attack Load Bus 1;218
14.4.2;11.4.2 Case 2: The Attacker Intends to Attack Load Bus 12;220
14.5;11.5 Summary;223
14.6;References;223