Abstract: In order to solve the problem that it is difficult to establish a model to describe the user’s electricity consumption behavior under the background of big data application in distribution network, a method based on clustering and random matrix theory is proposed to describe the user’s electricity consumption behavior. Firstly, the K-means clustering method is used to analyze the power consumption characteristic data of massive users, and the users are divided into groups according to the clustering results under different power consumption modes. Then, the model of user electricity behavior analysis is established based on the random matrix theory, through the analysis of the economic data, climate data and electricity price data of each user group, the factors related to the power consumption of the user group are identified, and describes the power user’s electricity consumption behavior. Finally, the effectiveness and accuracy of the proposed method is verified by the actual power consumption data of Wuwei power grid in Gansu Province, which provides data support for accurate power marketing and power demand side response strategy formulation.

Key words: big data, K-means clustering method, random matrix theory, user’s electricity consumption behavior