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Opportunistic condition-based maintenance optimization for electrical distribution systems

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  • Wang, Yifei
  • He, Rui
  • Tian, Zhigang

Abstract

The major goal of maintenance decision-making for electrical distribution systems (EDS) is to find maintenance policy with minimum costs, and this has been the top priority requirement for many power companies. To this aim, an opportunistic condition-based maintenance (CBM) policy is proposed for EDS in this work and incorporated into the Monte Carlo simulation (MCS) framework for maintenance decision-making. In contrast to reported works, three main contributions are summarized. First, it is the first time to design maintenance policies for EDSs according to their inspection states with the consideration of opportunistic maintenance. Second, invalid failure data in EDS, possibly caused by unanticipated events, are measured and mitigated by statistical matching based on the maximum mean discrepancy (MMD) before assessing the benefits of maintenance decisions. Third, the influence of the structural dependency is modeled in the CBM policy, which widely exists in EDSs but is rarely considered in previous works. A case study using the dataset collected from a real EDS is provided to demonstrate and validate the proposed maintenance optimization method.

Suggested Citation

  • Wang, Yifei & He, Rui & Tian, Zhigang, 2023. "Opportunistic condition-based maintenance optimization for electrical distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:reensy:v:236:y:2023:i:c:s095183202300176x
    DOI: 10.1016/j.ress.2023.109261
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    1. Dinh, Duc-Hanh & Do, Phuc & Iung, Benoit & Nguyen, Pham-The-Nhan, 2024. "Reliability modeling and opportunistic maintenance optimization for a multicomponent system with structural dependence," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Qi, Faqun & Huang, Meiqi, 2024. "Joint optimization of maintenance and spares inventory policy for a series-parallel system considering dependent failure processes," Reliability Engineering and System Safety, Elsevier, vol. 247(C).

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