一种改进的PSO算法在系统无功优化中的应用研究

为了确定系统中无功的合理配置,针对传统粒子群算法的不足,提出一种改进的小生境粒子群优化算法:借助于问题的局部极值点信息,对原目标函数进行"拉伸"变换,达到优化计算、缩小目标函数极值范围和降低搜索难度的目的。IEEE-6节点标准系统仿真结果表明,所提算法不仅收敛速度更快,且具备更强的全局搜索能力。

Application Research of an Improved PSO Algorithm in System Reactive Power Optimization

The purpose of reactive power optimization is for a reasonable reactive power configuration.An improved niching particle swarm optimization algorithm has been proposed aiming at the shortcomings of traditional particle swarm algorithm.Based in the local extreme points,the original objective function has been strength transformed for optimized calculation,minimizing the extreme point scope of the function and lower the searching difficulty.IEEE-6 node standard system simulation results show that the proposed algorithm not only has faster converged speed,but also owns stronger global searching ability.