Abstract: To accurately quantify the future electricity consumption planning of enterprises and producers, this paper focuses on the duration and degree of impact of expanding capacity changes on electricity sales, defines the impact life cycle of expansion, and establishes a contributing electricity prediction model through big data methods such as ARIMA, X-12 seasonal adjustment, user clustering and logistic regression. The model links the mapping chain from power business expansion to electric power consumption and predicts the change of electric power consumption through electricity installation. After tracking and training, the model's prediction accuracy has exceeded 90%, which better interprets the relationship between power business expansion and electricity sales and accurately predict the development trend of power business expansion capacity and map the industry prosperity.