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 .
提出了一种分析FACTS多个控制回路之间交互影响的新方法:改进相对增益矩阵(Relative gain array,RGA)方法,使其可对合成控制系统不同控制过程之间的交互影响进行分析,以利于设计人员通过考察各输入对输出变量的影响程度,选取控制变量与被控量之间的最佳搭配。为了验证所提出方法的有效性,将其用于指导FACTS阻尼控制器的设计。数字仿真结果表明,利用该方法进行UPFC阻尼控制器附加回路的选取,能取得较满意的效果。
