基于数据挖掘的户变关系辨识技术  

Identification technology of household transformer relationship based on data mining

作　　者：郝雁翔 闫明 井泉 黄建华 刘兵 HAO Yanxiang;YAN Ming;JING Quan;HUANG Jianhua;LIU Bing(Xuchang Power Supply Company,State Grid Henan Electric Power Company,Xuchang 461000,Henan,China;STEN Smart Energy Technology Company,Nanjing 211800,China)

机构地区：[1]国网河南省电力公司许昌供电公司,河南许昌461000 [2]南京斯泰恩智慧能源技术有限公司,南京211800

出　　处：《电测与仪表》2024年第9期209-215,共7页Electrical Measurement & Instrumentation

基　　金：国网河南省电力公司科技项目(521750210003)。

摘　　要：低压台区长期面临拓扑结构缺失、户变关系不明确的问题,而近年来对配电网的精细化管理及控制需求明确的户变关系。针对此提出了一种基于数据挖掘技术的户变关系辨识方案。所提方法首先基于台区内节点的电压波动相似特点,以电压序列相似性为距离标准,利用DBSCAN算法聚类出疑似的不属于目标台区的离群节点;其次基于上下游设备的电度数据相似性确认疑似节点是否属于目标台区,采用Apriori算法生成符合约束条件的台区从属节点集,再使用余弦相似度判别得到最可能的户变从属结果。最后,以某市供电公司一实际台区数据通过结果对比验证了文中算法的有效性。The low-voltage substation area has long faced the problems of lack of topology and unclear household transformer relationship.In recent years,the refined management and control of distribution network require clear household transformer relationship.In this paper,a household transformer relationship identification scheme based on data mining technology is proposed.Firstly,based on the similar characteristics of voltage fluctuation of nodes in the neighborhood area,the suspected nodes that do not belong to the target station area are clustered by DBSCAN algorithm.Secondly,based on the power similarity of upstream and downstream equipment,it is confirmed that whether the suspected node belongs to the target station area.The Apriori algorithm is used to generate the neighborhood area dependent node set that meets the constraints,and then,the cosine similarity discrimination is used to obtain the most possible household transformer dependent result.Finally,the effectiveness of the proposed algorithm is verified by comparing the results of an actual neighborhood area network.

关 键 词：数据挖掘 户变关系 余弦相关性 密度聚类 

分 类 号：TM93[电气工程—电力电子与电力传动]