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Research on a Comprehensive Maintenance Optimization Strategy for an Offshore Wind Farm

Author

Listed:
  • Yang Lu

    (College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China)

  • Liping Sun

    (College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China)

  • Yanzhuo Xue

    (College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China)

Abstract

Offshore wind is considered a crucial part in the future energy supply. However, influenced by weather conditions, the maintenance of offshore wind turbine system (OWTs) equipment is challenged by poor accessibility and serious failure consequences. It is necessary to study the optimized strategy of comprehensive maintenance for offshore wind farms, with consideration of the influences of incomplete equipment maintenance, weather accessibility and economic relevance. In this paper, a Monte Carlo algorithm-improved factor is presented to simulate the imperfect preventive maintenance activity, and waiting windows were created to study the accessibility of weather conditions. Based on a rolling horizon approach, an opportunity group maintenance model of an offshore wind farm was proposed. The maintenance correlations between systems and between equipment as well as breakdown losses, maintenance uncertainty, and weather conditions were taken into account in the model, thus realizing coordination of maintenance activities of different systems and different equipment. The proposed model was applied to calculate the maintenance cost of the Dafengtian Offshore Wind Farm in China. Results proved that the proposed model could realize long-term dynamic optimization of offshore wind farm maintenance activities, increase the total availability of the wind power system and reduce total maintenance costs.

Suggested Citation

  • Yang Lu & Liping Sun & Yanzhuo Xue, 2021. "Research on a Comprehensive Maintenance Optimization Strategy for an Offshore Wind Farm," Energies, MDPI, vol. 14(4), pages 1-22, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:965-:d:498013
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    References listed on IDEAS

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    2. 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.
    3. Zhu, Wenjin & Castanier, Bruno & Bettayeb, Belgacem, 2019. "A dynamic programming-based maintenance model of offshore wind turbine considering logistic delay and weather condition," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    4. Shafiee, Mahmood, 2015. "Maintenance logistics organization for offshore wind energy: Current progress and future perspectives," Renewable Energy, Elsevier, vol. 77(C), pages 182-193.
    5. Laura, Castro-Santos & Vicente, Diaz-Casas, 2014. "Life-cycle cost analysis of floating offshore wind farms," Renewable Energy, Elsevier, vol. 66(C), pages 41-48.
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    Cited by:

    1. Liang Cui & Ye Xu & Ling Xu & Guohe Huang, 2021. "Wind Farm Location Special Optimization Based on Grid GIS and Choquet Fuzzy Integral Method in Dalian City, China," Energies, MDPI, vol. 14(9), pages 1-13, April.
    2. Finn Gunnar Nielsen, 2022. "Perspectives and Challenges Related Offshore Wind Turbines in Deep Water," Energies, MDPI, vol. 15(8), pages 1-6, April.

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