Analysis of User’s Power Consumption Behavior Based on K-means

With the continuous development of energy Internet and smart grid technologies, the potential value of power big data is constantly being mined. User behavior of power consumption is of great significance to power companies, consumers and power systems. In this paper, through the mining and analysis of the data on the power consumption side, the K- means clustering method is used to search the similarity of the samples, and the users are classified according to the characteristics of the power consumption behavior. Finally, four different types of users are obtained, and the family structure composition and economic status of related users are analyzed. Through this method, the user's power consumption behavior pattern is analyzed, which provides a decision-making basis for the grid management side, and improves the service quality of electricity sellers to users.