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Resilience-based importance measure for ultra-high voltage converter stations under mainshock-aftershock sequences

Author

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  • Xue, Zhihang
  • Wang, Kai
  • Cao, Di
  • Zhou, Siyu
  • Liu, Yu

Abstract

Ultra-high voltage (UHV) converter stations are crucial for power systems, but their towering structures are highly vulnerable to earthquakes. It is, therefore, of great significance to enhance the resilience of the converter stations such that they can withstand and recover promptly from disruptions caused by earthquakes. Nevertheless, the uncertainties associated with earthquakes significantly hinder the post-earthquake recovery process, thus impacting importance ranking of the equipment in UHV converter stations. To address these uncertainties, this article proposes a new resilience-based importance (RBI) measure integrating vulnerability and recoverability under mainshock-aftershock sequences. Specifically, a roulette-wheel damage scenario generation method is adopted to generate equipment damage scenarios considering uncertainties. RBI measures considering cumulative damage effects from mainshock-aftershock sequences are calculated to evaluate equipment vulnerability and recoverability. The Copeland Score (CS) stochastic ranking method ranks equipment RBI, providing an optimal prioritization strategy for post-earthquake recovery. A case study of a ± 800 kV converter station demonstrates the proposed RBI method. Results show the RBI-based recovery strategy improves resilience by 10.4 % compared to traditional performance recovery importance (PRI) method. Neglecting aftershocks would result in approximately a 5.6 % overestimation of resilience.

Suggested Citation

  • Xue, Zhihang & Wang, Kai & Cao, Di & Zhou, Siyu & Liu, Yu, 2025. "Resilience-based importance measure for ultra-high voltage converter stations under mainshock-aftershock sequences," Reliability Engineering and System Safety, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:reensy:v:262:y:2025:i:c:s0951832025004466
    DOI: 10.1016/j.ress.2025.111245
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    1. Wen, Jiayi & Wang, Longquan & Li, Xiaoxuan & Zhang, Yantai & Wei, Yang, 2026. "Non-contact automated identification of earthquake-induced micro damage in substation equipment system based on local damping parameter screening with a surrogate model," Reliability Engineering and System Safety, Elsevier, vol. 266(PA).

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