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Multi-objective opportunity maintenance optimization for wind farms considering multiple factors

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  • Li, Wangsen
  • Xiang, Dong
  • Liang, Fengwei

Abstract

Wind power, as an essential component of clean energy, has made improving wind farm operation and maintenance (O&M) management a critical concern, yet no study has successfully integrated the impacts of reliability, wind speed, maintenance team constraints, and spare parts management into the decision-making process. This paper develops a joint optimization model that incorporates these factors, aiming to minimize the annual production loss and total maintenance cost of wind farms. A novel opportunity maintenance strategy is proposed, leveraging the reliability and external maintenance opportunities provided by low wind speed. A heuristic algorithm is employed to solve the maintenance team scheduling problem, and an (s, S) inventory policy is used to manage spare parts inventory. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is applied to derive a solution set that balances the two maintenance objectives. A case study on the O&M of an onshore wind farm is conducted to validate the advantages of the proposed strategy and analyze the impact of various parameters on the experimental results. The findings demonstrate that the proposed opportunity maintenance strategy performs well in reducing both maintenance costs and annual production losses.

Suggested Citation

  • Li, Wangsen & Xiang, Dong & Liang, Fengwei, 2026. "Multi-objective opportunity maintenance optimization for wind farms considering multiple factors," Renewable Energy, Elsevier, vol. 256(PA).
    • Handle: RePEc:eee:renene:v:256:y:2026:i:pa:s0960148125015320
    DOI: 10.1016/j.renene.2025.123868
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    References listed on IDEAS

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