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Fleet-level opportunistic maintenance for large-scale wind farms integrating real-time prognostic updating

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  • Xia, Tangbin
  • Dong, Yifan
  • Pan, Ershun
  • Zheng, Meimei
  • Wang, Hao
  • Xi, Lifeng

Abstract

Operation and maintenance (O&M) of wind farms has become progressively more important for renewable energy. The key challenge is that each modern large-scale wind farm normally consists of many wind turbines in parallel, while each complex turbine also contains diverse series of components. Traditional maintenance policies cannot handle such a complex system, let alone that each individual component undergoes different degradations. To reduce the scheduling complexity and maintenance cost, a fleet maintenance cost saving (FMCS) policy is developed to optimize condition-based opportunistic maintenance. Real-time condition data for each component is utilized to update its failure prognostic for avoiding the individual variation in the degradation process. On this basis, the whole wind farm is constructed as a fleet structure with series-parallel components. Power production loss within the same turbine and repeated personnel dispatch among other parallel turbines are analyzed to reduce the total maintenance cost efficiently. Through the case study, the framework with real-time prognostic updating and FMCS scheduling policy in component/fleet levels has been proven its economic advantages for future large-scale wind farms.

Suggested Citation

  • Xia, Tangbin & Dong, Yifan & Pan, Ershun & Zheng, Meimei & Wang, Hao & Xi, Lifeng, 2021. "Fleet-level opportunistic maintenance for large-scale wind farms integrating real-time prognostic updating," Renewable Energy, Elsevier, vol. 163(C), pages 1444-1454.
    • Handle: RePEc:eee:renene:v:163:y:2021:i:c:p:1444-1454
    DOI: 10.1016/j.renene.2020.08.072
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    References listed on IDEAS

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    Cited by:

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    2. Li, Yao & He, Yihai & Liao, Ruoyu & Zheng, Xin & Dai, Wei, 2022. "Integrated predictive maintenance approach for multistate manufacturing system considering geometric and non-geometric defects of products," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    3. McMorland, J. & Collu, M. & McMillan, D. & Carroll, J. & Coraddu, A., 2023. "Opportunistic maintenance for offshore wind: A review and proposal of future framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    4. Zhu, Ying & Xia, Tangbin & Hong, Ge & Chen, Zhen & Pan, Ershun & Xi, Lifeng, 2022. "Collaborative maintenance service and component sales under coopetition patterns for OEMs challenged by booming used-component sales," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    5. Liu, Gehui & Chen, Shaokuan & Ho, Tinkin & Ran, Xinchen & Mao, Baohua & Lan, Zhen, 2022. "Optimum opportunistic maintenance schedule over variable horizons considering multi-stage degradation and dynamic strategy," Reliability Engineering and System Safety, Elsevier, vol. 225(C).

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