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基于随机约束粒子群算法的配电网重构
引用本文:朱勇,陶用伟,李泽群,王常沛,何静,石祖昌.基于随机约束粒子群算法的配电网重构[J].中州煤炭,2018,0(1):145-152.
作者姓名:朱勇  陶用伟  李泽群  王常沛  何静  石祖昌
作者单位:(贵州电网有限责任公司凯里供电局,贵州 凯里 556000)
摘    要:同一地区的风速、光照强度和负荷均受各种气象因素的随机性影响,其影响因素具有一定的相关性,因此,为得到准确的配电网重构方案,不能忽略不确定性和相关性导致的误差。基于等概率转换和Cholesky分解,提出了同时计及风速、光照强度和负荷相关性的随机潮流方法,并在此基础上,引入机会约束理论,以满足一定置信水平的有功网损悲观值为目标,建立了配电网的机会约束重构模型。以IEEE-33节点配电系统为例进行验证,计算结果表明,配电网的随机潮流和重构结果均受到风速、光照强度和负荷间相关程度强弱的影响。

关 键 词:配电网重构  随机机会约束  粒子群算法  相关性  不确定性

 Reconfiguration of distribution network based on stochastic constrained particle swarm optimization
Zhu Yong,Tao Yongwei,Li Zequn,Wang Changpei,He Jing,Shi Zuchang. Reconfiguration of distribution network based on stochastic constrained particle swarm optimization[J].Zhongzhou Coal,2018,0(1):145-152.
Authors:Zhu Yong  Tao Yongwei  Li Zequn  Wang Changpei  He Jing  Shi Zuchang
Affiliation:(Kaili Bureau of Guizhou Power Grid Co.,Ltd.,Kaili 556000,China)
Abstract:According to the wind speed,the same area of the light intensity and load are subject to random effects of various meteorological factors and its influencing factors has certain correlation.Therefore,in order to get the solution of distribution network reconfiguration accurate,error cannot be neglected lead to uncertainty and correlation.This paper was based on the probability conversion and Cholesky decomposition,which was proposed considering wind speed,light intensity and power flow method,random load correlation,and on this basis,the introduction of the theory of chance constrained power loss and pessimism to meet a certain confidence level value as the goal,to establish distribution network reconfiguration model of chance constrained.The IEEE-33 node power distribution system was taken as an example to verify the results.The results showed that the random power flow and reconfiguration results were influenced by wind speed,light intensity and the degree of correlation between loads.
Keywords:,distribution network reconfiguration, stochastic chance constrained, particle swarm optimization, correlation, uncertainty
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