摘要
基于改进后的PSO算法,研究了如何利用网架扩展规划,来缓解风电并网发电后部分线路出现输电阻塞的现象。在PSO算法中,惯性权重和学习因子分别是控制PSO算法全局搜索和局部搜索的关键性可调整参数。为避免陷入局部解,同时加快收敛速度,提出了同时动态优化调整惯性权重和学习因子的改进PSO算法。基于IEEE39节点的仿真算例表明:在保证获得最优解的前提下,该算法的收敛速度显著加快。
In this paper, based on particle swarm optimization algorithm, the expansion planning of power network containing wind power for relieving transmission congestion is investigated. Inertia weights and acceleration coefficients are critical parameters in PSO algorithm. To avoid local optimal solution and to accelerate convergence speed, an improved PSO algorithm with self-adjusting inertia weights and acceleration coefficients is proposed. The simulations on the IEEE 39 power system show that the proposed algorithm significantly reduces computational time to obtain the global optimal solution.
出处
《江苏电机工程》
2014年第5期28-31,共4页
Jiangsu Electrical Engineering
关键词
网架扩展规划
PSO算法
惯性权重
学习因子
transmission network expansion planning
particle swarm optimization
inertia weights
acceleration coefficients
