An Improved particle swarm optimization algorithm for reactive power optimization

被引:0
|
作者
Xie, Tuo [1 ]
Xie, Jiancang [2 ]
Zhang, Gang [3 ]
Liu, Yin [2 ]
机构
[1] Xian Univ Technol, Sch Civil Engn & Architecture, Xian 710048, Peoples R China
[2] Xian Univ Technol, Inst Water Resources & Hydroelect Engn, Xian 710048, Peoples R China
[3] Gansu Elect Power Res Inst, Lanzhou 730050, Peoples R China
关键词
particle swarm optimization; reactive power optimization; mutation operator; combined Forecast;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Reactive power optimization of power system is a complicated multi-objective, multi-constraint combination optimization problem, particle swarm optimization (PSO) algorithm is the most commonly used algorithm to solve this problem. Aiming at the disadvantages of PSO algorithm, this paper came up with an improved particle swarm optimization (IPSO) algorithm. Firstly, it improved the particle population and initial position, and introduced weight coefficient in iterative process of evolution, which made the particles search process more reasonable and avoided premature convergence, secondly, it introduced the mutation operation to prevent particle swarming into local optimum, and enhanced the global optimization ability of the algorithm. Through the simulation calculation of the IEEE 6 nodes system, the results showed that IPSO algorithm is more effective than PSO algorithm.
引用
收藏
页码:489 / 493
页数:5
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