[1]王 姝,张海龙,王恩荣.基于改进粒子群算法的配电网网架优化研究[J].南京师范大学学报(工程技术版),2020,(01):015-19.[doi:10.3969/j.issn.1672-1292.2020.01.003]
 Wang Shu,Zhang Hailong,Wang Enrong.Study on Distribution Network OptimizationBased on Modified PSO[J].Journal of Nanjing Normal University(Engineering and Technology),2020,(01):015-19.[doi:10.3969/j.issn.1672-1292.2020.01.003]
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基于改进粒子群算法的配电网网架优化研究
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南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年01期
页码:
015-19
栏目:
电气工程
出版日期:
2020-03-15

文章信息/Info

Title:
Study on Distribution Network OptimizationBased on Modified PSO
文章编号:
1672-1292(2020)01-0015-05
作者:
王 姝张海龙王恩荣
(南京师范大学南瑞电气与自动化学院,江苏 南京 210023)
Author(s):
Wang ShuZhang HailongWang Enrong
School of NARI Electrical and Automation,Nanjing Normal University,Nanjing 210023,China
关键词:
配电网网架优化聚类分层粒子群
Keywords:
distribution networkgrid optimizationcluster stratificationparticle swarm optimization
分类号:
TM726.3
DOI:
10.3969/j.issn.1672-1292.2020.01.003
文献标志码:
A
摘要:
配电网网架优化是一个多目标综合优化问题,粒子群算法因其易实现、收敛速度快等特点逐渐成为电力系统优化领域研究热点之一. 针对粒子群算法易陷于局部最优问题,提出一种基于聚类策略的改进粒子群算法,动态地将粒子聚类为三种级别的粒子并对应采用不同的学习模型更新速度,增强了粒子群体多样性和全局搜索能力. 通过算例仿真验证了算法在配电网网架优化问题上的可行性.
Abstract:
Distribution network optimization is a multi-objective comprehensive problem. Meanwhile,particle swarm optimization(PSO)has become a hotspot in the field of power system optimization due to its easy implementation and fast convergence. To avoid trapping in local optimality,a modified PSO particle swarm optimization algorithm based on clustering strategy is proposed in this paper. Wherein,particles are dynamically clustered into three levels. Correspondingly,different learning models are used to update speed,thus enhancing the particle diversity and global search capabilities. The superiority of the proposed algorithm in distribution network optimization is verified by numerical simulation.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2019-05-14.
基金项目:南京师范大学企业合作项目(KJZX17015).
通讯作者:张海龙,博士,副教授,研究方向:电工理论与新技术. E-mail:61204@njnu.edu.cn
更新日期/Last Update: 2020-03-15