基于改进粒子群算法的动态无功优化研究  

Research on Dynamic Reactive Power Optimization Based on Improved PSO

作　　者：徐朝阳[1] 王孝友[1] 徐德贵 徐中辉 

机构地区：[1]池州供电公司,安徽池州247100 [2]榆树大岭第二中学,吉林榆树130414

出　　处：《东北电力大学学报》2017年第3期33-38,共6页Journal of Northeast Electric Power University

摘　　要：根据电力系统中负荷不断变化的情况,提出了动态无功优化的数学模型,并依据负荷曲线的变化特点进行智能分段。对粒子群算法进行改进,使其具有更好的收敛性和精确度,有效的避免了陷入局部最优解的情况。IEEE6节点系统算例分析表明,改进后的粒子群算法相比改进前的粒子群算法有明显的改善,能够减小系统网损。According to the change of load in power system, the mathematical model of dynamic reactive power optimization is put forward, according to the characteristics of load curve get the intelligent segmentation. Improved particle swarm optimization algorithm, which has better convergence and accuracy, and effectively avoid the local optimal solution. The analysis of IEEE6-node system shows that the improved PSO has obvious improvement compared with the PSO,can reduce the system network loss.

关 键 词：动态无功优化 粒子群算法 负荷曲线分段 

分 类 号：TM714.3[电气工程—电力系统及自动化]