基于电压差网络映射和后验概率校核的低压配电网故障定位方法

李青杉; 徐凤乾; 赖秀炎; 冯洋; 伊长春; 郭建峰

李青杉,徐凤乾,赖秀炎,冯洋,伊长春,郭建峰.基于电压差网络映射和后验概率校核的低压配电网故障定位方法[J].电测与仪表,2026,63(3):146-157.
LI Qingshan,XU Fengqian,LAI Xiuyan,FENG Yang,YI Changchun,GUO Jianfeng.Fault localization method for low-voltage distribution network based on voltage difference network mapping and posterior probability verification[J].Electrical Measurement & Instrumentation,2026,63(3):146-157.

基于电压差网络映射和后验概率校核的低压配电网故障定位方法

Fault localization method for low-voltage distribution network based on voltage difference network mapping and posterior probability verification

DOI：10.19753/j.issn1001-1390.2026.03.015

中文关键词: 低压配电网故障区段定位电压差网络映射 K 均值聚类算法马尔可夫链蒙特卡罗算法

英文关键词:low-voltage distribution network, fault segment localization, voltage difference network mapping, Kmean clustering algorithm, Markov chain Monte Carlo algorithm

基金项目:国网浙江省电力有限公司科技项目（5211QZ240006）

作者中文名	作者英文名	单位
李青杉	LI Qingshan	浙江省电力有限公司衢州供电公司
徐凤乾	XU Fengqian	浙江省电力有限公司衢州供电公司
赖秀炎	LAI Xiuyan	浙江省电力有限公司衢州供电公司
冯洋	FENG Yang	浙江省电力有限公司衢州供电公司
伊长春	YI Changchun	浙江省电力有限公司衢州供电公司
郭建峰	GUO Jianfeng	武汉大学电气与自动化学院

摘要点击次数: 442

中文摘要:

针对低压配电网拓扑复杂而导致故障区段定位精度不高的问题,提出了一种基于电压差网络映射和后验概率校核的故障区段定位方法。首先构造可达矩阵描述配电网拓扑结构,以准确反映网络各节点的连通性;根据故障前后节点电压的变化,计算节点故障电压差并利用K 均值聚类算法对故障电压差进行聚类,得到故障电压差矩阵;通过推导可达矩阵和故障电压差矩阵的关系计算线路区段状态矩阵,最后采用马尔可夫链蒙特卡罗(Markov chain Monte Carlo, MCMC)算法计算各区段故障的后验概率,对所得故障区段判定结果进行校核。多个配电网中算例结果表明,所提方法在不同配电网拓扑结构下的单一故障识别率达100%,在相同条件下相较于传统方法收敛速度提高了40%,显著提高了故障区段定位的准确性和可靠性。

英文摘要:

Aiming at the problem that the topology of low-voltage distribution network is complex and leads to low fault segment localization accuracy, a fault segment localization method based on voltage difference network mapping and a posterior probability checking is proposed. Firstly, a reachable matrix is constructed to describe the topology of the distribution network to accurately reflect the connectivity of each node of the network; according to the change of the node voltage before and after the fault, the node fault voltage difference is calculated and clustered using the K-mean clustering algorithm to obtain the fault voltage difference matrix; the line segment state matrix is calculated by deducing the relationship between the reachable matrix and the fault voltage difference matrix. Finally, the Markov chain Monte Carlo (MCMC) algorithm is used to calculate the a posterior probability of faults in each segment, and the results of fault segment determination are checked. The results of several examples in distribution network show that the proposed method achieves a single fault recognition rate of 100% under different distribution network topologies. Under the same conditions, compared with the traditional methods, the convergence speed is increased by 40%, significantly improving the accuracy and reliability of fault segment localization.

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