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This paper addresses a hybrid particle swarm optimization-based approach for solving a generating unit maintenance scheduling problem (GMS). We focus on the power system reliability such as reserve ratio better than cost function as the objective function of GMS problem. It is shown that particle swarm optimization-based method is more effective in obtaining feasible schedules such as GMS problem...
In this paper, a new probabilistic generation modeling method which can address the characteristics of changed electricity industry is proposed. The major contribution of this paper can be captured in the development of a probabilistic generation modeling considering generator maintenance outage and in the classification of market demand into multiple demand clusters for the applications to electricity...
A new approach to unit maintenance scheduling (UMS) problems in competitive electricity markets is presented in this paper. The objectives of this study are to develop a new framework for UMS in competitive markets, to analyze a strategic behavior of profit maximizing generating companies (Gencos) in an UMS game, and to discuss equilibriums of the game from the standpoint of whole generation market...
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