遗传算法在无功优化应用中的改进

将遗传算法应用于电力系统无功优化的同时，针对无功优化的实际，文章提出了在不同优化阶段，对目标函数各项罚因子采用不同权重，并且构造出分阶段适应性函数，以及提出了选择式杂交方式等改进措施。通过典型算例和实际系统的测试，证明了这些改进方法对遗传算法应用于无功优化计算的寻优速度和收敛特性都有明显提高。

IMPROVEMENT OF GENETIC ALGORITHM FOR REACTIVE POWER OPTIMIZATION

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.