Customer Identification of Potential Energy Substitution Based on Big Data Method

摘要

The usage of clean energy such as electric energy will help promote energy conservation and emission reduction, optimize energy use structure and improve energy efficiency. The realization of the "electric energy substitution" strategy can realize the replacement of loose coal and direct fuel in the terminal energy consumption, and finally realize the fundamental transformation of the energy development mode. This paper analyzed the customer characteristics of electric energy substitution potential from multiple dimensions, built a multi-dimensional linear electric energy substitution evaluation prediction model based on logistic regression algorithm, and quantified the output customer comprehensive score based on the obtained model results to identify high potential customers. At the same time, from the perspectives of government, power grid and enterprise, we utilized big data mining technology to analyze characteristics of high-potential customers, tapped customer demand characteristics, and achieved precise services.