基于典型窃电用户相似性检索的窃电行为检测方法

Detection Method of Electricity Theft Behavior Based on Retrieval of Similarity of Typical Users with Electricity Theft

从窃电用户数据的波动形态角度出发,提出一种基于典型窃电用户相似性检索的窃电行为检测方法。首先,利用动态时间弯曲对窃电用户的用电数据进行相似性量度,得到窃电相似度矩阵。其次,结合窃电相似度矩阵,利用近邻传播聚类方法对其进行聚类划分,实现窃电用户自动聚类,并利用簇中心作为典型窃电用户。最后,利用典型窃电用户在电力数据库中的相似性检索出与典型窃电用户的用电行为相似的用户,结合人工经验分析判别出嫌疑窃电用户。利用中国国家电网某省电力公司提供的数据进行算例分析,验证了所提方法的可行性与适用性。

From the perspective of fluctuation patterns of user data for electricity theft, a detection method of electricity theft behavior based on the retrieval of similarity of typical electricity theft behavior is proposed. Firstly, dynamic time warping is used to measure the similarity of consumption data for users with electricity theft behavior, and the similarity matrix of electricity theft is obtained. Secondly, combining with the similarity matrix of electricity theft, the affinity propagation clustering method is used to classify users with electricity theft behavior, so as to realize the automatic clustering of users with electricity theft behavior, and the cluster center is used as typical sample of users with electricity theft behavior. Finally, the similarity of typical users with electricity theft behavior in the electricity database is used to retrieve the users who have similar electricity consumption behaviors, and the suspected users with electricity theft behavior are identified based on manual experience analysis. The feasibility and applicability of the proposed method are verified by an example analysis of the data provided by a provincial electric power company of State Grid of China.