Research On Multi-Objective Reactive Power Optimization Based on Modified Particle Swarm Optimization Algorithm
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.
Multi-Objective Reactive Power Optimization TABU voltage stability active network loss PSO MPSO
Jianhua Wu Nan Li Lihong He Bin Yin Jianhua Guo Yaqiong Liu
School of Information Science and Engineering, Northeastern University, Shenyang, 110004
国际会议
The 22nd China Control and Decision Conference(2010年中国控制与决策会议)
徐州
英文
477-480
2010-05-26（万方平台首次上网日期，不代表论文的发表时间）