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Allocation of defensive and restorative resources in electric power system against consecutive multi-target attacks

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  • Wu, Yipeng
  • Chen, Zhilong
  • Dang, Junhu
  • Chen, Yicun
  • Zhao, Xudong
  • Zha, Lvying

Abstract

Because the infrastructure network itself has the characteristics of cascading failures, deliberate attackers will often take advantage of these internal dependencies to perform long-term multi-target strikes, which the paper calls consecutive multi-target attacks. This kind of continuous external destruction on the time scale will increase the chain effect of cascading failures within the system. Among these infrastructure networks, electric power systems are particularly critical, because most of the other infrastructures need electricity for their operation and management, and the cascading failure of the power network is more serious. Thus, this paper comprehensively considers external consecutive multi-target attacks and internal cascading failure propagation, establishes a defense-attack-recovery tri-level game optimization model, and study how to allocate defensive and restorative resources from a macro perspective to improve the strategic resilience of the power supply system. In order to solve the optimization model, the paper proposes a nested heuristic algorithm, and proposes a performance response function that combines the power flow operating characteristics and external failure events, and then uses the IEEE 39-bus network as a case study to verify the effectiveness of the model and algorithm.

Suggested Citation

  • Wu, Yipeng & Chen, Zhilong & Dang, Junhu & Chen, Yicun & Zhao, Xudong & Zha, Lvying, 2022. "Allocation of defensive and restorative resources in electric power system against consecutive multi-target attacks," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
  • Handle: RePEc:eee:reensy:v:219:y:2022:i:c:s0951832021006815
    DOI: 10.1016/j.ress.2021.108199
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    References listed on IDEAS

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    Cited by:

    1. Xiang, Yin, 2023. "Minimizing the maximal reliable path with a nodal interdiction model considering resource sharing," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
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    3. Tang, Daogui & Fang, Yi-Ping & Zio, Enrico, 2023. "Vulnerability analysis of demand-response with renewable energy integration in smart grids to cyber attacks and online detection methods," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    4. Li, Qing & Li, Mingchu & Tian, Yuan & Gan, Jianyuan, 2023. "A risk-averse tri-level stochastic model for locating and recovering facilities against attacks in an uncertain environment," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    5. Zhang, Xi & Liu, Dong & Tu, Haicheng & Tse, Chi Kong, 2022. "An integrated modeling framework for cascading failure study and robustness assessment of cyber-coupled power grids," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    6. Tu, Haicheng & Gu, Fengqiang & Zhang, Xi & Xia, Yongxiang, 2023. "Robustness analysis of power system under sequential attacks with incomplete information," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    7. Xu, Sheng & Tu, Haicheng & Xia, Yongxiang, 2023. "Resilience enhancement of renewable cyber–physical power system against malware attacks," Reliability Engineering and System Safety, Elsevier, vol. 229(C).

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