作　　者： ; ; ; ;

机构地区： 华南理工大学电力学院

出　　处： 《电网技术》 2010年第4期128-133,共6页

摘　　要： 提出了一种改进灾变遗传算法。该算法针对常规灾变算子局部搜索能力不足和收敛性差的缺点,提出了当前进化中最优个体灾变范围的概念,比常规灾变原理缩小了灾变范围,提高了灾变的针对性。此外,为提高遗传算法的收敛性能,设计了与进化代数相关的交叉概率和与个体适应度相关的变异概率。IEEE30节点系统算例表明,该算法具有良好的全局性能、收敛速度和收敛稳定性,适合求解电力系统的无功优化问题。 A new improved catastrophic genetic algorithm （ICGA） is proposed. According to the defects of insufficient local searching ability and unsatisfactory convergence of conventional catastrophic operator, a concept of optimal individual catastrophic region in current evolution is proposed, so the catastrophic region is decreased than that in conventional catastrophe principle and the pertinence to the catastrophe is improved. In addition, to improve the convergence of genetic algorithm, the computing formula of crossover probability related to evolutional generations and the computing formula of mutation probability related to individual fitness are designed. Calculation results of IEEE 30-bus system show that the proposed algorithm possesses satisfied global performance, high convergence speed and stable convergence performance, so it is suitable to solve the optimal reactive power panning.

关 键 词： 遗传算法 灾变 无功优化规划

领　　域： [自动化与计算机技术] [自动化与计算机技术] [电气工程]