Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains

Li, Y.; Coolen, F.P.A.

Abstract

Due to the high failure rates and the high cost of operation and maintenance of wind turbines, not only manufacturers but also service providers try many ways to improve the reliability of some critical components and subsystems. In reality, redundancy design is commonly used to improve the reliability of critical components and subsystems. The load dependencies and failure dependencies among redundancy components and subsystems are crucial to the reliability assessment of wind turbines. However, the redundancy components are treated as a parallel system, and the load correlations among them are ignored in much literature, which may lead to the wrong system’s reliability and much higher costs. For this reason, this article explores the influences of load-sharing on system reliability. The whole system’s reliability is quantitatively evaluated using fault tree analysis and the Markov-chain method. Following this, the optimisation of the redundancy allocation problem considering the load-sharing is conducted to maximise the system reliability and reduce the total cost of the system subjecting to the available system cost and space. The results produced by this methodology can show a realistic reliability assessment of the entire wind turbine from a quantitative point of view. The realistic reliability assessment can help to design a cost-effective and more reliable system and significantly reduce the cost of wind turbines.

Citation

Li, Y., & Coolen, F. (2019). Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 233(6), 1074-1085. https://doi.org/10.1177/1748006x19859690

• Journal Article Type: Article
• Acceptance Date: May 28, 2019
• Online Publication Date: Jul 3, 2019
• Publication Date: Dec 31, 2019
• Deposit Date: May 31, 2019
• Publicly Available Date: May 31, 2019
• Journal: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
• Print ISSN: 1748-006X
• Electronic ISSN: 1748-0078
• Publisher: SAGE Publications
• Peer Reviewed: Peer Reviewed
• Volume: 233
• Issue: 6
• Pages: 1074-1085
• DOI: https://doi.org/10.1177/1748006x19859690
• Public URL: https://durham-repository.worktribe.com/output/1329682