摘要
文章针对无功优化问题的特点,在传统粒子群算法(PSO)的基础之上,提出一系列的改进措施,形成了一种新型分阶段粒子群优化算法(MPSO)。该算法通过调整惯性权重和加速系数使粒子自组织地跟踪个体极值和全局极值来扩大粒子的搜索空间和提高粒子的收敛精度,同时根据粒子处于不同的阶段实施相应的变异策略来增加种群的多样性,有效地抑制了PSO算法的"早熟"现象,进一步加快了算法的收敛速度。以IEEE-30节点系统为例对该改进算法的性能进行了测试,结果表明了该算法的有效性和可行性。
Power system voltage and reactive power control is an effective measure to keep power system safety and economic, and an important method to improve voltage equality. According to the reactive power optimization characteristics, this paper proposes a series of improvements based on the existing particle swarm optimization, and forms a new kind of novel multistage particle swarm optimiza- tion, which is applied to solve the problems of reactive power optimization. The particles are organized to track the domain of attraction of local optimum for enlarging search space and the domain of attraction of global optimum for improving convergence porformance by a- daptively adjusting the acceleration coefficients and the inertia weight. Meanwhile the corresponding strategies with mutation are adopted in different stages of the new algorithm to further enhance diversity of population. The introduction of multistage and mutation concept has effectively suppressed the degenerated phenomenon which appears in the evolution process, further speed up the algorithm convergence rate. IEEE 30 - bus system is used to test the performance of the multistage algorithm, and the results show its validity and feasibility.
出处
《天津电力技术》
2010年第2期9-13,共5页
Tianjin Electric Power Technology
