Application of catastrophic PSO based on neighborhood search of global optimal particle in reactive power optimization

作者：Zhu, Ying-Ping^*; Cai, Ze-Xiang; Zhang, Yong-Jun; Yang, Yin-Guo; Song, Yong-Chao

来源：Power System Protection and Control, 2011, 39(18): 110-115.

• Catastrophe
• Neighborhood search
• Particle swarm
• Power System
• Reactive power optimization
• Search speed
• Statistical datas
• Theory of action

In order to resolve the issues of easy prematurity and partial convergence of basic particle swarm optimization (BPSO) applied to reactive power optimization in power system, an improved BPSO is proposed. Neighborhood search of global optimal particle is added to PSO(NSGOP-PSO), which improves the search speed and precision of particle swarm. Moreover, catastrophic algorithm based on evolutionary algorithm is also added(NSGOP-CPSO) in the whole particles or parts regularly, which can solve issues of prematurity and non-convergence of BPSO. Detailed analysis and explanation of action principle of this algorithm, simulation diagram and statistical data of IEEE30 nodes system show the effectiveness of NSGOP-CPSO.

• 出版日期2011-9-16
• 单位华南理工大学