Research On Multi-Objective Reactive Power Optimization Based on Modified Particle Swarm Optimization Algorithm

被引：2
|
作者：
Wu, Jianhua [1 ]
Li, Nan [1 ]
He, Lihong [1 ]
Yin, Bin [1 ]
Guo, Jianhua [1 ]
Liu, Yaqiong [1 ]
机构：
[1] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110004, Peoples R China
来源：
2010 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-5 | 2010年
关键词：
Multi-Objective Reactive Power Optimization; TABU; voltage stability; active network loss; PSO; MPSO;
D O I：
10.1109/CCDC.2010.5499012
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes modified Multi-Objective Particle Swarm Optimization (MPSO) algorithm based on Pareto solution to overcome the conventional MPSO algorithm can easily fall into its local maximum value and improve the diversity of solution set. This algorithm is composition of a modified Tabu Search with Multi-Objective Particle Swarm Optimization (TSMPSO). With this algorithm Establishing the memory devices- taboo list of global optimal solution, Store the history of the particle that is selected to be the optimal global. And through this approach to strengthen performance of particle swarm optimization in global and local searching. TSMPSO is simple and easy to implement. Simulation results of IEEE 30-bus system show that this algorithm can enhance power system voltage stability, meanwhile economic operation of power system is also implemented, thus the effectiveness and superiority of TSMPSO algorithm are verified.
引用
收藏
页码：477 / 480
页数：4
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