基于改进免疫遗传的配电网故障区段定位研究

Research on Fault Section Location of Distribution Network Based on Improved Immune Genetic Algorithm

针对目前智能算法在配电网故障定位中存在收敛速度慢、易陷入局部最优的问题,提出将基于免疫遗传算法(ImmuneGeneticAlgorithm,IGA)应用于配电网故障定位中,同时引入精英保留思想对传统免疫遗传算法进行改进。改进后的算法拥有遗传算法搜索特性的同时保留了免疫算法多机制寻求多目标函数最优解的自适应特性,很大程度上避免了算法“早熟”,有效提高了算法的准确度和收敛速度。仿真结果表明,当配电网发生单重故障、多重故障或信号畸变时,改进免疫遗传算法都能够准确快速地进行区段定位,具有较好的有效性、容错性和快速性。

In consideration of the problems of slow convergence speed and easiness to fall into local optimum in the fault location of distribution network using traditional intelligent algorithm,the immune genetic algorithm(IGA)has been proposed to be used in fault location in distribution network,and the idea of elite reservation has been introduced to improve the immune genetic algorithm.The improved algorithm not only has the search characteristics of genetic algorithm,but also retains the adaptive characteristics of multi-mechanism immune algorithm to seek the optimal solution of multi-objective function,largely avoiding the"premature"phenomenon,and effectively improving the accuracy and convergence of fault location speed.The simulation results indicate that the improved immune genetic algorithm can accurately and quickly locate the fault section when single/multiple faults or signal distortion occurs in the distribution network,showing well effectiveness,fault tolerance and rapidness.