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Resilience enhancement of renewable cyber–physical power system against malware attacks

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  • Xu, Sheng
  • Tu, Haicheng
  • Xia, Yongxiang

Abstract

The widespread application of cyber technologies and Renewable Energy Sources (RESs) has gradually transformed traditional power systems into renewable Cyber–Physical Power Systems (CPPSs), which are increasingly threatened by malware attacks. In this paper, we develop an original and novel simulation framework with consideration of both malware attack process and the uncertainty of RESs to quantitatively analyze the resilience of renewable CPPS. Based on the framework, we consider different stages of the resilience process and propose corresponding prevention and restoration methods to enhance the resilience of the system. The efficacy and applicability of our proposed methods are demonstrated in a test renewable CPPS formed by coupling the IEEE 39 Bus System with a scale-free communication network. Experimental results reveal that accurate RES output forecast and a disassortative communication network can improve the resilience of renewable CPPS against malware attacks.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:229:y:2023:i:c:s0951832022004495
    DOI: 10.1016/j.ress.2022.108830
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    1. Varbella, Anna & Gjorgiev, Blazhe & Sansavini, Giovanni, 2023. "Geometric deep learning for online prediction of cascading failures in power grids," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
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    3. Erdal Irmak & Ersan Kabalci & Yasin Kabalci, 2023. "Digital Transformation of Microgrids: A Review of Design, Operation, Optimization, and Cybersecurity," Energies, MDPI, vol. 16(12), pages 1-58, June.
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