Modelling wind turbine degradation and maintenance

Le, Bryant and Andrews, John (2016) Modelling wind turbine degradation and maintenance. Wind Energy, 19 (4). pp. 571-591. ISSN 1099-1824

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Abstract

degradation, inspection and maintenance processes. The model was developed based on the Petri net method that effectively captures the stochastic nature of the dynamic processes through the use of appropriate statistical distributions. The versatility of the method allows the details of the degradation and maintenance operations to be incorporated in the model. In particular, there are dependent deterioration processes between wind turbine subsystems, complex maintenance rules and the incorporation of condition monitoring systems for early failure indication to enable replacement prior to failure. The purposes of the model are to predict the future condition of wind turbine components and to investigate the effect of a specified maintenance strategy. The model outputs are statistics indicating the performance of the wind turbine components; these include the probability of being in different condition states, the expected number of maintenance actions and the average number and duration of system downtime under any maintenance strategy.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/977420
Additional Information: This is the peer reviewed version of the following article: Le, B., and Andrews, J. (2016) Modelling wind turbine degradation and maintenance. Wind Energ., 19: 571–591, which has been published in final form at http://dx.doi.org/10.1002/we.1851. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Keywords: wind turbine; Petri net; degradation; maintenance modelling
Schools/Departments: University of Nottingham, UK > Faculty of Engineering
Identification Number: 10.1002/we.1851
Depositing User: Eprints, Support
Date Deposited: 25 Sep 2017 14:55
Last Modified: 04 May 2020 20:03
URI: https://eprints.nottingham.ac.uk/id/eprint/46719

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