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Front. Eng    2021, Vol. 8 Issue (4) : 503-518    https://doi.org/10.1007/s42524-021-0163-3
REVIEW ARTICLE
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
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Abstract

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.
Keywords Cyber–Physical Power System      resilience assessment      resilience optimization      cascading failure modeling     
Corresponding Author(s): Zhaojun S. LI   
Just Accepted Date: 25 May 2021   Online First Date: 21 June 2021    Issue Date: 01 November 2021
 Cite this article:   
Gongyu WU,Zhaojun S. LI. Cyber–Physical Power System (CPPS): A review on measures and optimization methods of system resilience[J]. Front. Eng, 2021, 8(4): 503-518.
 URL:  
https://academic.hep.com.cn/fem/EN/10.1007/s42524-021-0163-3
https://academic.hep.com.cn/fem/EN/Y2021/V8/I4/503
Fig.1  Schematic of the structure of CPPSs.
Fig.2  Overall research roadmap for this paper.
Fig.3  Generic system performance transition curve of CPPSs under the occurrence of disturbances.
System type Coupling dependency Power flow calculation Cyber node Reference
Single (binary) – Complex network-based – Chen et al. (2014)
Single (binary) – DC-power flow-based – Liu and Li (2016)
Single (binary) – AC-power flow-based – Li et al. (2018b)
Single (multi-state) – AC-power flow-based – Wu and Li (2019)
Coupled (binary) Undirected Ignored Same type Buldyrev et al. (2010)
Coupled (binary) Undirected AC-power flow-based Same type Zang et al. (2019)
Coupled (binary) Directed Ignored Same type Huang et al. (2013)
Coupled (binary) Directed DC-power flow-based Two types Wang et al. (2016b)
Coupled (binary) Directed AC-power flow-based Three levels Guo et al. (2019)
Coupled (multi-state) Directed AC-power flow-based Three levels Wu et al. (2020)
Tab.1  Evolution of the modeling methods of CPPS cascading failures and corresponding representative methods
Reference Type Stages or nodes involved in Fig. 3 Speed Uncertainty Assessment factor
Shinozuka et al. (2004) Discrete C, D Considered Ignored Single
Henry and Ramirez-Marquez (2012) Discrete A, C, D Ignored Ignored Single
Francis and Bekera (2014) Discrete A, C, D Considered Ignored Single
Bruneau and Reinhorn (2007) Continuous All three stages Considered Ignored Single
Ouyang and Dueñas-Osorio (2012) Continuous All three stages Considered Ignored Single
Fang et al. (2016) Continuous All three stages Considered Ignored Single
Ouyang et al. (2012) Continuous All three stages Considered Considered Single
Wu et al. (2020) Continuous All three stages Considered Considered Multiple
Tab.2  References analysis of CPPS resilience assessment measures
Reference System type Coupling dependency Method type Special factor involved
Ouyang et al. (2012) Single (binary) – Qualitative –
Ouyang and Duenas-Osorio (2014) Single (binary) – Qualitative DC-based power flow calculation
Figueroa-Candia et al. (2018) Single (binary) – Quantitative Risk analysis and investment
Fang et al. (2016) Single (binary) – Quantitative Two ranking metrics
Shi et al. (2019) Single (binary) – Quantitative Specific power supply path description model
Zhang et al. (2019) Single (binary) – Quantitative Reinforcement learning
Gao et al. (2016) Single (binary) – Quantitative Two-objective chance constrained program
Wei et al. (2020) Single (binary) – Quantitative Deep reinforcement learning
Jiang et al. (2020) Single (binary) – Quantitative Two-stage stochastic problem
Li et al. (2019b) Single (binary) – Quantitative Resource routing
Ouyang and Wang (2015) Coupled (binary) Undirected Quantitative Five weighting strategies
González et al. (2016) Coupled (binary) Undirected Quantitative Savings due to simultaneous collocated recovery jobs
Wu et al. (2020) Coupled (multi-state) Directed Quantitative Multiple modes, multiple resources
Tab.3  References analysis of CPPS resilience optimization methods based on the optimization of the recovery sequence of components
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  References analysis of CPPS resilience optimization methods based on the identification and protection of critical nodes
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  References analysis of CPPS resilience optimization methods based on the optimization of the coupling patterns between power and communication networks
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