基于共享小生境伪并行遗传算法配网无功优化研究

针对传统遗传算法(SGA)在配电网无功优化中的缺陷和配电网的特点,把基于共享函数的小生境技术和伪并行遗传算法有机结合起来应用于无功优化,采用实数编码和自适应交叉、变异等策略.建立了以运行费用最小为目标的数学模型.实际网络计算结果表明,小生境伪并行遗传算法在提高运算速度、维持群体多样性和抑制早熟等方面显示出优越性,更加适用于配网无功优化.

Research on Reactive Power Optimization of Distribution Network Based on the Sharing Niche Pseudo-Parallel Genetic Algorithm

Regarding to the defects of traditional genetic algorithm applied to reactive power optimization of distribution network and the characteristics of distribution network, the sharing niche pseudo parallel genetic algorithm is put forward to enhance the ability of global optimization with the strategy of real valued coding and adaptive crossover mutation genetic algorithm.An objective function consider the run charge least. The network calculation shows that sharing niche pseudo parallel genetic algorithm is superiority for advance rate of convergence, maintain variety of colony and restrain prematurity. It is more fit for the reactive power optimization.