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基于分块关联矩阵的中压配电网可靠性评估分块算法
引用本文:唐建宇,洪灿,姚钪,陈曦.基于分块关联矩阵的中压配电网可靠性评估分块算法[J].广东电力,2013(12):48-52.
作者姓名:唐建宇  洪灿  姚钪  陈曦
作者单位:深圳供电局有限公司,广东深圳518020
摘    要:结合中压配电网结构特点,提出基于分块关联矩阵的中压配电网可靠性评估分块算法。首先形成配电网分块,然后提出了分块关联矩阵的构造方法。基于此,在以块为单位进行故障解析模拟时,通过递归故障块的前后向块来确定故障影响范围,可大量节省故障枚举时间和重复的开关元件搜索时间。同时在分块关联矩阵形成后可不再考虑网络结构,方便求得带子馈线及备用电源的配电网可靠性指标。应用该算法对可靠性测试系统进行了可靠性评估,算例表明该算法计算准确,计算过程简单且便于分析系统中的薄弱点。

关 键 词:电力系统  配电网  可靠性评估  分块算法  分块关联矩阵

Block Algorithm for Reliability Evaluation of Medium Distribution Network Based on Block Incidence Matrix
TANG Jianyu,HONG Can,YAO Kang,CHEN Xi.Block Algorithm for Reliability Evaluation of Medium Distribution Network Based on Block Incidence Matrix[J].Guangdong Electric Power,2013(12):48-52.
Authors:TANG Jianyu  HONG Can  YAO Kang  CHEN Xi
Affiliation:(Shenzhen Power Supply Bureau Co. , Ltd. , Shenzhen, Guangdong 518020, China)
Abstract:Combining structural characteristics of medium distribution network, this paper proposes block algorithm for relia- bility evaluation of medium distribution network based on block incidence matrix which firstly forms distribution network block and then proposes a construction method for block incidence matrix. Based on the above principle, it proposes to deter- mine the fault impact scope by front and rear block of the fault block when carrying through fault analysis simulation by tak- ing block as unit which is able to greatly save fault enumeration time and repeated switching element searching time. Meanwhile, it considers that after forming the block incidence matrix, there is no need to think about network struc- ture which is more convenient to acquire reliability index of the distribution network provided with subfeeders and backup power source. It conducts reliability evaluation on reliability testing system by applying this algorithm and the example indi- cates veracity of the algorithm which is provided with simple calculation process for easy to analyze weak spot in the system.
Keywords:power system  distribution network  reliability evaluation  block algorithm  block incidence matrix
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