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Optimal dynamic imperfect preventive maintenance of wind turbines based on general renewal processes

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  • Jinhe Wang
  • Xiaohong Zhang
  • Jianchao Zeng
  • Yunzheng Zhang

Abstract

With the rapid growth in wind turbine technology worldwide, the high operational and maintenance costs of wind turbines have posed a major challenge to wind power operating companies. Considering the high replacement cost, imperfect maintenance measures are employed widely once downtime failures occur. However, as the metric to describe the effect of imperfect maintenance is a non-intuitive variable, the evaluation results obtained from existing research do not conform with actual wind turbine situations. To address this issue, the virtual age factor and failure intensity update factor are expressed by intuitive variables to illustrate the imperfect maintenance effect. Additionally, we propose a failure rate function update model considering the above factors. To minimise maintenance costs while ensuring the availability of the wind turbine, we investigate a periodic dynamic imperfect preventive maintenance decision model based on the proposed failure rate function update model. We also provide a brief illustration of the accuracy and feasibility of the proposed model through optimal solution and sensitivity analyses. The results obtained from the case analysis and strategies comparison, based on actual wind turbine maintenance data, demonstrate the economic advantages of our approach.

Suggested Citation

  • Jinhe Wang & Xiaohong Zhang & Jianchao Zeng & Yunzheng Zhang, 2020. "Optimal dynamic imperfect preventive maintenance of wind turbines based on general renewal processes," International Journal of Production Research, Taylor & Francis Journals, vol. 58(22), pages 6791-6810, November.
  • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:22:p:6791-6810
    DOI: 10.1080/00207543.2019.1685706
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    Cited by:

    1. Levitin, Gregory & Xing, Liudong & Dai, Yanshun, 2021. "Joint optimal mission aborting and replacement and maintenance scheduling in dual-unit standby systems," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    2. Wang, Weikai & Chen, Xian, 2023. "Piecewise deterministic Markov process for condition-based imperfect maintenance models," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    3. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2021. "Influence of storage on mission success probability of m-out-of-n standby systems with reusable elements," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    4. Levitin, Gregory & Xing, Liudong & Dai, Yanshun, 2022. "Minimum cost replacement and maintenance scheduling in dual-dissimilar-unit standby systems," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    5. Levitin, Gregory & Xing, Liudong & Xiang, Yanping, 2021. "Optimal multiple replacement and maintenance scheduling in two-unit systems," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    6. Hajej Zied & Rezg Nidhal & Kammoun Mohamed Ali & Bouzouba Maryem, 2024. "Improved maintenance strategy for the wind turbine system under operating and climatic conditions," Journal of Risk and Reliability, , vol. 238(2), pages 349-365, April.
    7. Nguyen, Thi-Anh-Tuyet & Chou, Shuo-Yan & Yu, Tiffany Hui-Kuang, 2022. "Developing an exhaustive optimal maintenance schedule for offshore wind turbines based on risk-assessment, technical factors and cost-effective evaluation," Energy, Elsevier, vol. 249(C).

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