基于k-means聚类算法的低压台区线损异常辨别方法  

Abnormal Line Loss Identification Method for Low-Voltage Substation Area Based on k-Means Clustering Algorithm

作　　者：陈洪涛 蔡慧 李熊[2] 王颖 郑恩辉 CHEN Hongtao;CAI Hui;LI Xiong;WANG Ying;ZHEN Enhui(College of Mechanical and Electrical Engineering of China Jiliang University,Hangzhou 310018,China;Zhejiang Electric Power Corporation,Hangzhou 310008,China)

机构地区：[1]中国计量大学机电工程学院,杭州310018 [2]国网浙江省电力公司,杭州310008

出　　处：《南方电网技术》2019年第2期2-6,共5页Southern Power System Technology

基　　金：浙江省自然科学基金青年科学基金项目(LQ17E070003)~~

摘　　要：目前电力公司对于台区线损异常的判断是当线损率超过一定阈值时为线损异常,这样的判断具有片面性和局限性。针对如何有效辨别线损异常的问题,在研究聚类算法和线损率数据特性的基础上,提出了一种基于k-means聚类算法的线损异常辨别方法。首先将低压台区线损率进行一次k-means聚类分成3类,然后根据各类数据的数量状况判断是否进行二次分类,最终根据平均线损率的大小、聚类中心的距离等因素,判断该低压台区是否存在线损异常,对聚类结果中线损率高的那一类数据的时间离散度进行分析,得到低压台区线损异常的程度。实验结果证明,该方法具有一定的实际应用效果,可以提高线损异常判断的准确性。At present,electric power companys'judgment on abnomal line loss is that the line loss is abnormal when the line loss rate exceeds a certain threshold.Yet the judgement is one-sidedness and limited.To effectively identify the problem of line loss,based on the study of clustering algorithm and the characteristics of the line loss rate data,an improved k-means clustering algorithm for anomal line loss discrimination is proposed.The method firstly carries out a k-means clustering on the line loss rate of the low voltage substation area to be classified into three classes,then judges whether to carry out secondary classification according to the quantity of various data,and finally judges whether a line loss abnormality exists in the low voltage substation area according to factors such as the size of average line loss rate,and the distance of the clustering center.By analyzing the time dispersion of the class of data with high line loss rate of the clustering results.the degree of abnormality of the line loss can be obtained.Experimental results show that this method has a certain practical application effect and can improve the accuracy of abnormal line loss judgement.

关 键 词：线损率 线损异常 数据挖掘 聚类算法 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]