Abstract
Bundled wind–thermal generation system (BWTGS) is an effective way to utilize remote large–scale wind power. The optimal generation maintenance schedule (GMS) for BWTGS is not only helpful to improve the system reliability level but also useful to enhance the system economic efficiency and extend the lifetime of components. This paper presents a model to optimize the GMS for BWTGS. The probabilistic production simulation technique is employed to calculate the system costs, and a sequential probabilistic method is utilized to capture the sequential and stochastic nature of wind power. A hybrid optimization algorithm (HOA) based on the simulated annealing (SA) and multipopulation parallel genetic algorithm (GA) is developed to solve the proposed model. Case studies demonstrate the effectiveness of this proposed model. Effects of the reliability deterioration of thermal generating units (TGUs) and the pattern of BWTGS transmission power are also investigated.
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