基于改进小生境伪并行遗传算法的电力系统无功优化研究

将小生境伪并行遗传算法进行改进,用于对电力系统无功功率进行优化。这种遗传算法是对小生境遗传算法和并行遗传算法的一个有效改进,该方法兼顾了对局部最优解和全局最优解的搜索,既维持了群体的多样性,避免了早期收敛现象的发生,又增强了自然群体进化的并行性,加快了搜索进程。实验结果表明该方法是有效可行的,通过合理选取选择、交叉、变异及小生境算子,能得到电力系统无功功率优化的最优解。

Research on the Reactive Power Optimization of Power System Based on Niche Pseudo-parallel Genetic Algorithms

Niche pseudo-parallel genetic algorithms are improved to optimize the reactive power of power system.The algorithms take both local optimal solution and global optimal solution to account,maintain the diversity of the groups to avoid the occurrence of the early convergence,and enhance the parallel of natural groups evolution to speed up the search process.Experimental results show that the method is effective and feasible,and the optimal solution of power system reactive power optimization is achieved through the rational selection of selection,crossover,mutation and niche operators.