Wind power is one of the most important sources of renewable energy available today. A large part of the cost of wind energy 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 circumstances that are less than ideal. 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 that 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 clearly show the benefit of PM planning compared to a pure CM strategy (about 30% lower maintenance cost).
In an agreement of a BOT project, concession period is one of the core terms that directly influence the benefits of all parties and the success of a project. Concession period has aroused the attention of both domestic and foreign scholars. This paper summarizes the main influencing factors of the concession period, simulating the NPV of the project income in Monte Carlo method with the probability distribution of the actual situation, selecting corresponding concession period according to a reasonable level of IRR. Based on the simulation results, the scheme of the highest comprehensive utility can be approached with the help of multi-objective fuzzy evaluation model for scheme optimization. And it also provides a possible solution for concession period strategy through the proof of a case.
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