学术文献库

Wind power is one of the most important sources of renewable energy. A large part of the wind energy cost is due to the cost of maintaining the wind power equipment. To further reduce the maintenance cost, one can improve the design of the wind turbine components. One can also reduce the maintenance costs by optimal scheduling of the component replacements. The latter task is the main motivation for this paper. When a wind turbine component fails to function, it might need to be replaced under less than ideal circumstances. This is known as corrective maintenance. To minimize the 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 optimization model is developed 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 8.5% lower maintenance cost). When we compare it with another state-of-art optimization model, it shows similar scheduling with a much faster CPU time. The comparison demonstrated that our model is both fast and accurate.