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A dynamic programming-based maintenance model of offshore wind turbine considering logistic delay and weather condition

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  • Zhu, Wenjin
  • Castanier, Bruno
  • Bettayeb, Belgacem

Abstract

There are several challenges toward maintaining offshore wind turbines such as ensuring the intrinsic performance of the wind turbine, maximizing short- and long-term profits, and optimizing maintenance grouping. These criteria should be optimized in respect to several practical constraints. Moreover, issues such as decision-making in uncertain environments where reliability-oriented field data are insufficient and information regarding the state of health state also be tackled.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:190:y:2019:i:c:3
    DOI: 10.1016/j.ress.2019.106512
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    References listed on IDEAS

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    3. 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).
    4. Li, He & Teixeira, Angelo P. & Guedes Soares, C., 2020. "A two-stage Failure Mode and Effect Analysis of offshore wind turbines," Renewable Energy, Elsevier, vol. 162(C), pages 1438-1461.
    5. Kan, Cihangir & Devrim, Yilser & Eryilmaz, Serkan, 2020. "On the theoretical distribution of the wind farm power when there is a correlation between wind speed and wind turbine availability," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    6. Zhang, Chen & Hu, Di & Yang, Tao, 2022. "Anomaly detection and diagnosis for wind turbines using long short-term memory-based stacked denoising autoencoders and XGBoost," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    7. Zhang, Nan & Cai, Kaiquan & Deng, Yingjun & Zhang, Jun, 2024. "Joint optimization of condition-based maintenance and condition-based production of a single equipment considering random yield and maintenance delay," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    8. Pliego Marugán, Alberto & García Márquez, Fausto Pedro & Pinar Pérez, Jesús María, 2022. "A techno-economic model for avoiding conflicts of interest between owners of offshore wind farms and maintenance suppliers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    9. 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).
    10. Pablo Viveros & Rodrigo Mena & Enrico Zio & Leonardo Miqueles & Fredy Kristjanpoller, 2023. "Integrated planning framework for preventive maintenance grouping: A case study for a conveyor system in the Chilean mining industry," Journal of Risk and Reliability, , vol. 237(5), pages 1011-1028, October.
    11. Wang, Jian & Gao, Shibin & Yu, Long & Zhang, Dongkai & Xie, Chenlin & Chen, Ke & Kou, Lei, 2023. "Data-driven lightning-related failure risk prediction of overhead contact lines based on Bayesian network with spatiotemporal fragility model," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    12. 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.
    13. 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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