文章基本信息

标题：Reactive Power Optimization Based on Parallel Immune Particle Swarm Optimization
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作者：Yuan, Guili ; Zhu, Lei ; Yu, Tong 等
期刊名称：Journal of Computers
印刷版ISSN：1796-203X
出版年度：2014
卷号：9
期号：9
页码：2198-2205
DOI：10.4304/jcp.9.9.2198-2205
语种：English
出版社：Academy Publisher
摘要：Reactive power optimization is important to ensure power quality, improve system security, and reduce active power loss. So, this paper proposed parallel immune particle swarm optimization (PIPSO) algorithm. This algorithm makes basic particle swarm optimization (BPSO) and discrete particle swarm optimization (DPSO) to optimize in parallel, and improves the convergence capability of particle swarm optimization with convergence ability. It is effective to overcome the problem of local convergence by immune operator, at the same time, it is more reasonable to solve the complex coding problem which discrete variables and continuous variables mixed by parallel optimization. Finally, the simulation results of IEEE-14, IEEE-30, IEEE-118 nodes system show that compared to the genetic algorithm and basic particle swarm optimization, the parallel immune particle swarm optimization can achieve the convergence effect faster and more stable, and better to solve the large-scale power system reactive power optimization.
关键词：reactive power optimization;particle swarm optimization;immune algorithm;discrete algorithm;parallel optimization