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Maintenance Optimization of Offshore Wind Turbines Based on an Opportunistic Maintenance Strategy

Author

Listed:
  • Lubing Xie

    (School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China)

  • Xiaoming Rui

    (School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China)

  • Shuai Li

    (School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China)

  • Xin Hu

    (School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China)

Abstract

Owing to the late development of offshore wind power in China, operational data and maintenance experience are relatively scarce. Due to the harsh environmental conditions, a reliability analysis based on limited sample fault data has been regarded as an effective way to investigate maintenance optimization for offshore wind farms. The chief aim of the present work is to develop an effective strategy to reduce the maintenance costs of offshore wind turbines in consideration of their accessibility. The three-parameter Weibull distribution method was applied to failure rate estimation based on limited data. Moreover, considering the impacts of weather conditions on the marine maintenance activities, the Markov method and dynamic time window were used to depict the weather conditions. The opportunistic maintenance strategy was introduced to cut down on the maintenance costs through optimization of the preventive maintenance age and opportunistic maintenance age. The simulation analysis we have performed showed that the maintenance costs of the opportunistic maintenance strategy were 10% lower than those of the preventive maintenance strategy, verifying the effectiveness of the proposed maintenance strategy.

Suggested Citation

  • Lubing Xie & Xiaoming Rui & Shuai Li & Xin Hu, 2019. "Maintenance Optimization of Offshore Wind Turbines Based on an Opportunistic Maintenance Strategy," Energies, MDPI, vol. 12(14), pages 1-26, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2650-:d:247273
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    References listed on IDEAS

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    1. Sinha, Y. & Steel, J.A., 2015. "A progressive study into offshore wind farm maintenance optimisation using risk based failure analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 735-742.
    2. Ding, Fangfang & Tian, Zhigang, 2012. "Opportunistic maintenance for wind farms considering multi-level imperfect maintenance thresholds," Renewable Energy, Elsevier, vol. 45(C), pages 175-182.
    3. Zhang, Chen & Gao, Wei & Guo, Sheng & Li, Youliang & Yang, Tao, 2017. "Opportunistic maintenance for wind turbines considering imperfect, reliability-based maintenance," Renewable Energy, Elsevier, vol. 103(C), pages 606-612.
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    1. Ren, Zhengru & Verma, Amrit Shankar & Li, Ye & Teuwen, Julie J.E. & Jiang, Zhiyu, 2021. "Offshore wind turbine operations and maintenance: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    2. Cheng Yang & Jun Jia & Ke He & Liang Xue & Chao Jiang & Shuangyu Liu & Bochao Zhao & Ming Wu & Haoyang Cui, 2023. "Comprehensive Analysis and Evaluation of the Operation and Maintenance of Offshore Wind Power Systems: A Survey," Energies, MDPI, vol. 16(14), pages 1-39, July.
    3. Jichuan Kang & Zihao Wang & C. Guedes Soares, 2020. "Condition-Based Maintenance for Offshore Wind Turbines Based on Support Vector Machine," Energies, MDPI, vol. 13(14), pages 1-17, July.

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