Environmental/economic power dispatch using a fuzzified multi-objective particle swarm optimization algorithm

被引:186
|
作者
Wang, Lingfeng [1 ]
Singh, Chanan [1 ]
机构
[1] Texas A&M Univ, Dept Elect & Comp Engn, College Stn, TX 77843 USA
关键词
multi-objective optimization; particle swarm optimization; environmental/economic power dispatch; local/global search; constraint satisfaction;
D O I
10.1016/j.epsr.2006.11.012
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The environmental issues that arise from the pollutant emissions produced by fossil-fueled electric power plants have become a matter of concern more recently. The conventional economic power dispatch cannot meet the environmental protection requirements, since it only considers minimizing the total fuel cost. The multi-objective generation dispatch in electric power systems treats economic and emission impact as competing objectives. which requires some reasonable tradeoff among objectives to reach an optimal solution. In this paper, a fuzzified multi-objective particle swarm optimization (FMOPSO) algorithm is proposed and implemented to dispatch the electric power considering both economic and environmental issues. The effectiveness of the proposed approach is demonstrated by comparing its performance with other approaches including weighted aggregation (WA) and evolutionary multi-objective optimization algorithms. All the simulations are conducted based on a typical test power system. (C) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:1654 / 1664
页数:11
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