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Reliability Evaluation of Smart Substation Based on Time-Varying Probabilistic Hybrid Attack Graph

Author

Listed:
  • Zhiyong Li

    (School of Automation, Central South University, Changsha 410083, China)

  • Wubin Wen

    (School of Automation, Central South University, Changsha 410083, China)

  • Rende Dai

    (Hunan Zhongda Design Institute Co., Ltd., Changsha 410205, China)

  • Wanting Xi

    (School of Automation, Central South University, Changsha 410083, China)

Abstract

A substation is the portion of a power grid that forms a link between the cyber system and the physical system. Reliability evaluation of smart substations based on a time-varying probabilistic hybrid attack graph (TVPHAG) is studied in this paper. First, the topology network of the smart substation is established, whose attributes are represented by probability. Then, in order to solve the problem of asynchrony in the cyber-physical system and the hybrid caused by heterogeneity, time-varying state equation in topology and cuts in algebra are introduced to TVPHAG. Based on TVPHAG, the evaluation of the reliability of cyber-physical systems with multiple equipment and multiple timescales is established. On this basis, the influences of physical conditions, cyberattacks, physical attacks, and cyber-physical attacks on substations are analyzed, respectively. Finally, the simulation shows that the method is effective in evaluating the reliability of smart substations, providing a new method for the evaluation of reliability.

Suggested Citation

  • Zhiyong Li & Wubin Wen & Rende Dai & Wanting Xi, 2022. "Reliability Evaluation of Smart Substation Based on Time-Varying Probabilistic Hybrid Attack Graph," Energies, MDPI, vol. 15(18), pages 1-15, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6724-:d:914973
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    References listed on IDEAS

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    1. Zhao, Yunfei & Huang, Linan & Smidts, Carol & Zhu, Quanyan, 2020. "Finite-horizon semi-Markov game for time-sensitive attack response and probabilistic risk assessment in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    2. Remigiusz Wisniewski, 2021. "Design of Petri Net-Based Cyber-Physical Systems Oriented on the Implementation in Field Programmable Gate Arrays," Energies, MDPI, vol. 14(21), pages 1-25, October.
    3. Sergey V. Buldyrev & Roni Parshani & Gerald Paul & H. Eugene Stanley & Shlomo Havlin, 2010. "Catastrophic cascade of failures in interdependent networks," Nature, Nature, vol. 464(7291), pages 1025-1028, April.
    4. Xiaohong Yin & Lin Li & Qiang Liu, 2022. "A Study on the Vulnerability Cascade Propagation of Integrated Energy Systems in the Transportation Industry Based on the Petri Network," Energies, MDPI, vol. 15(12), pages 1-12, June.
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