Intelligent Identification Method for Potential Users of Electric Energy Substitution Based on Data Mining

In order to solve the problem that the Gauss kernel density of power users is not clear, which leads to the low stability of the identification method, an intelligent identification method based on data mining is designed. The data mining technology is used to estimate the potential value of electric energy substitution, divide the types of electric energy consumption structure, calculate the minimum distance and maximum distance from the sample center respectively, and obtain the Gauss kernel density of power users. Combined with the development law of power load, the user membership matrix is constructed, and the intelligent recognition mode is set to realize the design of intelligent recognition method. Experimental results: under different attack strength conditions, the average stability of the proposed method is high, up to 83.278, which provides a guarantee for identifying potential users of electric energy substitution.