摘要
粒子群优化(PSO)算法可以解决在配电网状态估计中由分布式电源接入引起的非线性特征问题,但是将标准PSO算法应用于多模态函数系统会出现陷入局部收敛等问题。提出了带有变异算子的PSO算法,能够解决PSO算法在配电网状态估计时陷入局部收敛的问题。利用所提出算法对IEEE33节点系统进行状态估计,并与标准PSO算法进行比较,验证了所提算法的有效性。
Particle swarm optimization(PSO)algorithm can solve the problem with non-linear characteristics caused by the access of distributed generators in distribution network state estimation.However,the application of traditional PSO algorithm to multi-modal function system will lead to local convergence.This paper presents a PSO algorithm with mutation operator,which can solve the problem of local convergence of PSO algorithm in distribution network state estimation.The proposed algorithm is used to estimate the state of the IEEE33 bus system,and compared with the standard PSO algorithm.At the same time,the algorithm is used to realize the optimal allocation of distributed generators in the distribution network.
作者
张宝文
江道灼
王玉芬
梁一桥
ZHANG Bao-wen;JIANG Dao-zhuo;WANG Yu-fen;LIANG Yi-qiao(Colleae of Electricat Engineering Zhejiang University,Hangzhou 310027,China)
出处
《能源工程》
2020年第3期17-20,45,共5页
Energy Engineering
关键词
粒子群优化
变异算子
分布式电源配电网
状态估计
particle swarm optimization
variation operator
distributed power distribution network
state estimation
