Cyber–Physical Power System (CPPS): A review on measures and optimization methods of system resilience
Gongyu WU1, Zhaojun S. LI2()
1. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China 2. Department of Industrial Engineering and Engineering Management, Western New England University, Springfield, MA 01119, USA
The Cyber–Physical Power System (CPPS) is one of the most critical infrastructure systems in a country because a stable and secure power supply is a key foundation for national and social development. In recent years, resilience has become a major topic in preventing and mitigating the risks caused by large-scale blackouts of CPPSs. Accordingly, the concept and significance of CPPS resilience are at first explained from the engineering perspective in this study. Then, a review of representative quantitative assessment measures of CPPS resilience applied in the existing literature is provided. On the basis of these assessment measures, the optimization methods of CPPS resilience are reviewed from three perspectives, which are mainly focused on the current research, namely, optimizing the recovery sequence of components, identifying and protecting critical nodes, and enhancing the coupling patterns between physical and cyber networks. The recent advances in modeling methods for cascading failures within the CPPS, which is the theoretical foundation for the resilience assessment and optimization research of CPPSs, are also presented. Lastly, the challenges and future research directions for resilience optimizing of CPPSs are discussed.
. [J]. Frontiers of Engineering Management, 2021, 8(4): 503-518.
Gongyu WU, Zhaojun S. LI. Cyber–Physical Power System (CPPS): A review on measures and optimization methods of system resilience. Front. Eng, 2021, 8(4): 503-518.
Savings due to simultaneous collocated recovery jobs
Wu et al. (2020)
Coupled (multi-state)
Directed
Quantitative
Multiple modes, multiple resources
Tab.3
Reference
System type
Problem
Assessment perspective
Special factor involved
Xu et al. (2018)
Single
Single node
Topology-based
k-shell decomposition and structure hole
Yang et al. (2019)
Single
Single node
Topology-based
Integrate three classical topology centralities
Chen et al. (2020)
Single
Node set
Topology-based
Nonconvex mixed-integer quadratic programming
Adebayo et al. (2018a)
Single
Single node
Electrical characteristic and topology-based
Network structural theory participation factor and voltage critical bus index
Liu et al. (2018)
Single
Single node
Electrical characteristic and topology-based
Voltage anti-interference and influence abilities
Kang et al. (2018)
Single
Single node
Electrical characteristic and topology-based
Giant efficiency subgraph of the power network
Yang et al. (2020a)
Single
Single node
Electrical characteristic and topology-based
Electric cactus structure
Fan et al. (2018)
Coupled
Single node
Electrical characteristic and topology-based
Hyper-network model of the substation auto system
Fan et al. (2020)
Coupled
Single node
Electrical characteristic and topology-based
Physical topology, transport, and service layers
Tab.4
Reference
Coupling dependency
Optimization strategy
Special factor involved
Chen et al. (2015)
“One-to-one” undirected
Overall coupling preferences
Coupling patterns based on node loads
Golnari and Zhang (2015)
Directed
Overall coupling preferences
Coupling patterns based on the node degree
Liu et al. (2020)
“One-to-one” undirected
Overall coupling preferences
Average propagation latency and relative coupling correlation coefficient
Wang et al. (2018)
“One-to-one” undirected
Overall coupling preferences
Degree distribution and the intensification effect on cascading failure propagations
Schneider et al. (2011)
“One-to-one” undirected
Branch swapping
Retain conductance distribution and transport properties
Peng et al. (2020)
“One-to-one” undirected
Branch swapping
Seven strategies based on three classical centralities
Kazawa and Tsugawa (2020)
“One-to-one” undirected
Branch addition
Seven strategies based on the node degree and the degree–degree difference
Wang et al. (2020b)
Partial “one-to-one” undirected
Branch addition
Uniformity of the node degree
Cui et al. (2018)
Directed
Branch addition
Both intra-layer and dependence branches
Yang et al. (2020b)
“One-to-one” undirected
Branch reduction
Unbalanced dependence branch
Tab.5
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