IMPROVEMENT OF GENETIC ALGORITHM FOR REACTIVE POWER OPTIMIZATION
Zhao Dengfu Zhou Wenhua Zhang Fusheng Xia Daozhi Xi'an Jiaotong University Xi'an,710049 China
Applying genetic algorithm to reactive power optimization, the improvement measures such as adopting different weights of penalty factors in the objective function, constructing different adaptive functions, and selective hybridization are proposed in this paper. The results of the typical example and practical systems indicate that these measures can improve remarkably the searching speed and convergence of the genetic algorithm for reactive power optimization.
【CateGory Index】： TM744