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Optimal Maintenance Schedule for a Wind Power Turbine with Aging Components
Version 1
: Received: 21 June 2023 / Approved: 21 June 2023 / Online: 21 June 2023 (07:15:49 CEST)
A peer-reviewed article of this Preprint also exists.
Yu, Q.; Carlson, O.; Sagitov, S. Optimal Maintenance Schedule for a Wind Power Turbine with Aging Components. Algorithms 2023, 16, 334. Yu, Q.; Carlson, O.; Sagitov, S. Optimal Maintenance Schedule for a Wind Power Turbine with Aging Components. Algorithms 2023, 16, 334.
Abstract
Wind power is one of the most important sources of renewable energy available today. A large part of the wind energy cost is due to the cost of maintaining wind power equipment. When a wind turbine component fails to function, it might need to be replaced under the less than ideal circumstances. This is known as corrective maintenance. To minimize unnecessary costs, a more active maintenance policy based on the life expectancy of the key components is preferred. Optimal scheduling of preventive maintenance activities requires advanced mathematical modeling. In this paper, an optimal preventive maintenance algorithm is designed using the renewal-reward theorem. In the multi-component setting, our approach involves a new idea of virtual maintenance which allows us to treat each replacement event as a renewal event even if some components are not replaced by new ones. The proposed optimization algorithm is applied to a four-component model of a wind turbine and the optimal maintenance plans are computed for various initial conditions. The modeling results showed clearly the benefit of PM planning compared to pure CM strategy (about 30% lower maintenance cost).
Keywords
Algorithm design; Combinatorial optimization; Preventive maintenance; Virtual maintenance; Linear programming; Wind turbine; Weibull distribution; Renewal-reward theorem
Subject
Computer Science and Mathematics, Applied Mathematics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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