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.
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