Optimizing Combination of Units Commitment Based on Improved Genetic Algorithms

被引：0
|
作者：
LAI Yifei
机构：
来源：
Wuhan University Journal of Natural Sciences | 2007年 / 06期
关键词：
generating units; unit commitment; genetic algorithms;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
GAs are general purpose optimization techniques based on principles inspired from the biological evolution using metaphors of mechanisms, such as natural selection, genetic re-combination and survival of the fittest. By use of coding better-ment, the dynamic changes of the mutation rate and the crossover probability, the dynamic choice of subsistence, the reservation of the optimal fitness value, a modified genetic algorithm for opti-mizing combination of units in thermal power plants is proposed. And through taking examples, test result are analyzed and com-pared with results of some different algorithms. Numerical results show available value for the unit commitment problem with ex-amples.
引用
收藏
页码：1003 / 1007
页数：5
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