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Reliability assessment of the hydraulic system of wind turbines based on load-sharing using survival signature

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  • Li, Yao
  • Coolen, Frank P.A.
  • Zhu, Caichao
  • Tan, Jianjun

Abstract

The hydraulic system is one of the most critical subsystems of wind turbines. It is used to reset the aerodynamic brakes. Because of this, the reliability of the hydraulic system is important to the functioning of the entire wind turbine. To realistically assess the reliability of the hydraulic system, we propose in this article the load-sharing based reliability model using survival signature to conduct system reliability assessment. In addition, due to the uncertainty of the failure rates, it is difficult to conduct accurate reliability analysis. The Markov-based fuzzy dynamic fault tree analysis method is developed to solve this issue for reliability modeling considering dynamic failure characteristics. Following this, we explore the reliability importance and the reliability sensitivity of redundant components. The relative importance of the components with respect to the system reliability is evaluated and ranked. Then the reliability sensitivity with respect to the distribution parameters of redundant components is studied. The results of the reliability sensitivity analysis investigate the effects of the distribution parameters on the entire system’s reliability. The effectiveness and feasibility of the proposed methodology are demonstrated by the successful application on the hydraulic system of wind turbines.

Suggested Citation

  • Li, Yao & Coolen, Frank P.A. & Zhu, Caichao & Tan, Jianjun, 2020. "Reliability assessment of the hydraulic system of wind turbines based on load-sharing using survival signature," Renewable Energy, Elsevier, vol. 153(C), pages 766-776.
    • Handle: RePEc:eee:renene:v:153:y:2020:i:c:p:766-776
    DOI: 10.1016/j.renene.2020.02.017
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    References listed on IDEAS

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    1. Eryilmaz, Serkan & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2018. "Marginal and joint reliability importance based on survival signature," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 118-128.
    2. Pinar Pérez, Jesús María & García Márquez, Fausto Pedro & Tobias, Andrew & Papaelias, Mayorkinos, 2013. "Wind turbine reliability analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 463-472.
    3. Feng, Geng & Patelli, Edoardo & Beer, Michael & Coolen, Frank P.A., 2016. "Imprecise system reliability and component importance based on survival signature," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 116-125.
    4. Bin Liu & Min Xie & Way Kuo, 2016. "Reliability modeling and preventive maintenance of load-sharing systemswith degrading components," IISE Transactions, Taylor & Francis Journals, vol. 48(8), pages 699-709, August.
    5. Borgonovo, Emanuele & Aliee, Hananeh & Glaß, Michael & Teich, Jürgen, 2016. "A new time-independent reliability importance measure," European Journal of Operational Research, Elsevier, vol. 254(2), pages 427-442.
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    Cited by:

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    6. Qin, Shuidan & Wang, Bing Xing & Tsai, Tzong-Ru & Wang, Xiaofei, 2023. "The prediction of remaining useful lifetime for the Weibull k-out-of-n load-sharing system," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    7. Man-Ho Ling, 2022. "Optimal Constant-Stress Accelerated Life Test Plans for One-Shot Devices with Components Having Exponential Lifetimes under Gamma Frailty Models," Mathematics, MDPI, vol. 10(5), pages 1-13, March.
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    9. Khaled Guerraiche & Latifa Dekhici & Eric Chatelet & Abdelkader Zeblah, 2021. "Multi-Objective Electrical Power System Design Optimization Using a Modified Bat Algorithm," Energies, MDPI, vol. 14(13), pages 1-19, July.
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    11. Salomon, Julian & Winnewisser, Niklas & Wei, Pengfei & Broggi, Matteo & Beer, Michael, 2021. "Efficient reliability analysis of complex systems in consideration of imprecision," Reliability Engineering and System Safety, Elsevier, vol. 216(C).

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