摘要
Evolutionary algorithms EAs have m any potential applications in power system s operation and control. However,when applying EAs to engineering optimization,there is still a preeminent problem,i. e. the prem ature convergence problem,which degrades the EAs’perform ance.As such,there has been extensive research from a theoretical point of view in this field to avoid the premature convergence problem and to im prove EAs’performance. This review attem pts to collect,organize and present in a unified way som e of the most representative works in this field.They are categorized into four parts:encoding,self- adaptation,constraints- handling techniques and multi- objective optim ization. An overview on the four technologies is presented herein and it is desired to provide some new ideas for developing successful EAs’applications. This projectis supported by National Natural Science Foundation of China No. 5 0 0 0 70 0 2 and Rencai Yinjin Foundation of HU ST No.AA131F47 .
Evolutionary algorithms EAs have m any potential applications in power system s operation and control. However,when applying EAs to engineering optimization,there is still a preeminent problem,i. e. the prem ature convergence problem,which degrades the EAs'perform ance.As such,there has been extensive research from a theoretical point of view in this field to avoid the premature convergence problem and to im prove EAs'performance. This review attem pts to collect,organize and present in a unified way som e of the most representative works in this field.They are categorized into four parts:encoding,self- adaptation,constraints- handling techniques and multi- objective optim ization. An overview on the four technologies is presented herein and it is desired to provide some new ideas for developing successful EAs'applications. This projectis supported by National Natural Science Foundation of China No. 5 0 0 0 70 0 2 and Rencai Yinjin Foundation of HU ST No.AA131F47 .
出处
《电力系统自动化》
EI
CSCD
北大核心
2001年第2期60-63,共4页
Automation of Electric Power Systems
基金
国家自然科学基金! (5 0 0 0 70 0 2 )
华中科技大学人才引进基金! (AA131F47)资助项目
关键词
电力系统
运行
进化算法
约束优化问题
罚函数法
evolutionary algorithms
encoding
self- adaptation
constraints- handling techniques
multi- objective optim izationT