Research on Power Behavior Analysis Based on Clustering

Abstract

This research is based on data clustering to analyze power users’ electricity consumption behavior, and analyzes the load curve to obtain the users’ electricity consumption characteristics and classify users according to the characteristics of electricity consumption behavior. It is of far-reaching significance to the power industry and socio-economic development. This paper introduces the principle and flow of the main clustering algorithm K-means, fuzzy clustering and neural network clustering algorithm. The data preprocessing method is given. The clustering algorithm and the optimal clustering number are determined by defining the clustering volatility and clustering accuracy index. Then the power consumption behavior of the user is analyzed through the load curves and characteristic parameters obtained through clustering.