1. Zhejiang University Hangzhou 310027 China 2. Patent Agency of Jiangxi Province Nanchang 330046 China 3. Zhejiang Electricity Power Corporation Hangzhou 310007 China
Abstract：Taking energy-saving, environmental protection and economic principles as objectives, an optimal multi-objective scheduling model and multi-objective particle swarm optimization algorithm (MOPSO) are presented. Traditionally, only coordination degree was considered as the final target for transforming the multi-objective optimization problem into a single-objective one. In this paper, model is improved by adding the satisfaction requirements with coordination degree, and removing the ideal value used in the definition of satisfaction and coordination. In such a way, the feasibility of decision-making is improved, and the decision burden of decision-makers is alleviated effectively. Results of the case study proves that the improved method proposed can be suitable to adopt in the multi-objective optimization dispatch.
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2010, Vol. 25 
