基于模糊遗传算法的配电网无功补偿

The Compensation of Distribution Network Reactive Power Based on Fuzzy Genetic Algorithm

文中首先介绍了通过模糊理论改进的遗传算法,然后建立了多目标配电网无功优化模型。遗传算法[1]的改进具体在选择操作上考虑了个体在种群中的浓度,在变异操作上加入了防止陷入局部最优的检验操作,有效解决了遗传早熟等缺点。用改进遗传算法求得补偿点的最优配置[2],从而在多种负荷[3]下运行的综合满意度达到最大。并将改进后的算法运用在具体的10 kV某一支路上,取得了非常好的实际应用效果。

This paper first introduces an improved genetic algorithm by fuzzy theory, and then builds a multi- objective dis- tribution network reactive power optimization model. An improved genetic algorithm exactly considers the concentration of individu- al during the choose of the specific operation in the population and adds optimum inspection operation to prevent falling into local in the mutation, effectively soluves the shortcomings of genetic premature. In this paper, using the improved genetic algorithm to ob- tain the optimal allocation of the compensation point, which achieve maximum satisfaction during running in a variety of load. And using the improved algorithm in a branch of 10 kV, makes a very good application effect.