A Bayesian reliability analysis exploring the effect of scheduled maintenance on wind turbine time to failure
Anderson, Fraser and Dawid, Rafael and McMillan, David and García‐Cava, David (2023) A Bayesian reliability analysis exploring the effect of scheduled maintenance on wind turbine time to failure. Wind Energy, 26 (9). pp. 879-899. ISSN 1095-4244 (https://doi.org/10.1002/we.2846)
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Abstract
This article presents a Bayesian reliability modelling approach for wind turbines that incorporates the effect of time‐dependent variables. Namely, the technique is used to explore the effect of annual services on wind turbine failure intensity through time for turbines within a currently operational wind farm. In the operator's experience, turbines seemed to fail more frequently after scheduled maintenance was performed; however, this is an unexplored effect in the literature. Additionally, the effects of seasonality, year of operation and position in the array on failure intensity are explored. These features were included in a Cox‐like model formulation which allows for time‐dependent covariates. Inference was performed via Bayes rule. Results show a spike in failure intensity reaching 1.57 times the baseline in the six days directly proceeding annual servicing, after which failure intensity is reduced compared to baseline. Also observed is a significant year‐on‐year reduction of failure intensity since the introduction of the site's data management system in 2018, a clear preference for modelling time to failure via a Weibull distribution and a dependence on location in the array with respect to the prominent wind direction. Results also show the benefit of employing a Bayesian regime, which provides easily interpretable uncertainty quantification.
ORCID iDs
Anderson, Fraser, Dawid, Rafael ORCID: https://orcid.org/0000-0002-7574-6195, McMillan, David ORCID: https://orcid.org/0000-0003-3030-4702 and García‐Cava, David;-
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Item type: Article ID code: 86113 Dates: DateEventSeptember 2023Published6 July 2023Published Online4 June 2023Accepted15 September 2022SubmittedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering > Production of electric energy or power Department: Faculty of Engineering > Electronic and Electrical Engineering
Strategic Research Themes > EnergyDepositing user: Pure Administrator Date deposited: 11 Jul 2023 14:47 Last modified: 28 Nov 2024 01:26 URI: https://strathprints.strath.ac.uk/id/eprint/86113