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基于混合智能算法的电力系统无功优化研究
引用本文:葛莲,理文祥.基于混合智能算法的电力系统无功优化研究[J].江西电力职工大学学报,2012(1):1-4.
作者姓名:葛莲  理文祥
作者单位:兰州交通大学,甘肃兰州730070
摘    要:研究了电力系统的无功优化功问题,给出了结合电力市场实行的无功优化目标函数。在分析了遗传算法和蚁群算法各自优缺点的基础上,将遗传算法与蚁群算法融合,利用遗传算法的交叉、变异操作产生蚁群算法新的搜索路径,以此提高混合智能算法的全局搜索能力和收敛速度,并将混合智能算法应用于实例进行仿真。仿真结果表明,该混合智能算法具有快速的收敛速度和优良的全局优化能力。

关 键 词:无功优化  遗传算法  蚁群算法  混合智能算法

Research on Reactive Power Optimization of Power System Based on Hybrid Intelligent Algorithm
GE Lian,LI Wen-xiang.Research on Reactive Power Optimization of Power System Based on Hybrid Intelligent Algorithm[J].Journal of Jiangxi Electrical University For Staff,2012(1):1-4.
Authors:GE Lian  LI Wen-xiang
Affiliation:(Lanzhou Jiaotong University,Lanzhou 730070,China)
Abstract:In this paper,the reactive power optimization of power system is researched and the objective function of reactive power optimization combined with electricity market is given.Based on the analysis of the advantages and disadvantages of genetic algorithm and ant colony algorithm respectively,an amalgamation of the two algorithms is given by using crossover and mutation operations of genetic algorithm to generate new searching path for ant colony algorithm,which can be used to improve the global search ability and convergence speed of hybrid intelligent algorithm.Then this hybrid intelligent algorithm applied in a instance is simulated.The simulation results show that the hybrid intelligent algorithm has fast convergence speed and fine global optimization ability.
Keywords:reactive power optimization  genetic algorithm  ant colony algorithm  hybrid intelligent algorithm
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