基于自适应遗传算法的配电网无功优化

针对传统的遗传算法在求解配电网无功优化问题时容易陷入局部最优,并且收敛速度慢的缺点,将自适应遗传算法引入配电网无功优化中,采用自适应的交叉率和变异率使之符合遗传算法动态性和适应性搜索过程,并在编码方式、适应度函数设计、遗传操作以及终止判据等方面进行改进,对IEEE 33测试系统进行仿真分析,算例表明了算法的实用性和有效性。

Reactive Power Optimization of Distribution Network Based on Adaptive Genetic Algorithm

As for the shortcoming of traditional genetic algorithm which can easily fall into partial optimum and have slow rate of convergence when used in solving the reactive power optimization problems of distribution network,in this paper,adaptive genetic algorithm is introduced into reactive power optimization of distribution network,adaptive cross rate and variation rate is used so to make them conform to the dynamic and adaptive genetic algorithm search process.Some improvements in such areas as encoding,fitness function design,genetic operations and termination criterion are made.IEEE 33 test system is used for simulation analysis and the usefulness and effectiveness of the algorithm is shown in the numerical example.