基于动态NW小世界量子粒子群算法的电力系统无功规划优化

摘要

为了解决电力系统无功规划优化问题,提出一种动态NW小世界量子粒子群算法( NWQPSO) ,改善了传统量子粒子群算法易陷入局部最优的缺点. 将NW小世界的动态拓扑结构应用到粒子进化公式中,增加了迭代过程中粒子多样性,使其多局部搜索和全局性搜索. 利用电压稳定裕度指标,寻找系统电压稳定性较薄弱节点,将其作为无功补偿安装点,以无功补偿装置投资和网损综合费用为目标函数,通过IEEE30节点系统的仿真,验证了该规划方法和算法的有效性.%The paper proposed a dynamic NW small-world quantum particle swarm algorithm ( NWQPSO) to solve problems in the optimization of power system reactive power planning. The NW small-world dynamic topological structure was applied to the particle formula of evolution, increasing the diversity of particles in the iterative process, which enabled local search and global search. The voltage stability margin index was used to search for the nodes of system with relatively weak voltage stability, where reactive power compensation would be installed. Tak-ing reactive power compensation device investment and the network loss comprehensive cost as objective function, the effectiveness of planning method and the algorithm is verified through IEEE30 nodes system optimization simula-tion.