PSO-based multi-criteria optimum design of A grid-connected hybrid power system with multiple renewable sources of energy

被引:57
作者
Wang, Lingfeng [1 ]
Singh, Chanan [1 ]
机构
[1] Texas A&M Univ, Dept Elect & Comp Engn, College Stn, TX 77843 USA
来源
2007 IEEE SWARM INTELLIGENCE SYMPOSIUM | 2007年
基金
美国国家科学基金会;
关键词
D O I
10.1109/SIS.2007.367945
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the stricter environmental regulation and diminishing fossil-fuel reserve, various renewable sources of energy are being exploited recently. These alternative sources of energy are usually environmentally friendly and emit no pollutants. However, the capital investments for those renewable sources of energy are normally high and there are also maintenance cost differences to be considered. Furthermore, due to the variability of these power sources, reliability issues should be addressed when integrating different power sources. In this paper, a grid-connected hybrid generating system comprising wind turbine generators, photovoltaic panels, and storage batteries is designed. In this multi-source generation system design, three design objectives are considered, that is, costs, relliabitity, and pollutant emmissions. Considering the complexity of this problem, we have developed a multi-objective particle swarm optimization (MOPSO) algorithm to derive a set of non-dominated solutions, each of which represents a candidate system design. A numerical example is discussed to illustrate the design procedure and the simulation results are analyzed.
引用
收藏
页码:250 / +
页数:2
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