In recent years

influenced by reforms of electric power system

economic transformation and upgrading

increased environmental protection efforts

frequent extreme weather events

and coronavirus pandemic

customers face problems such as declining output and difficult sales that increases the electric charge recycling risk. A regression model based on industry development trend is proposed to predict the electric charge recycling risk. Firstly

the seasonal adjustment algorithm is used to extract the trend item of the historical industry electricity sales

and then the affecting factors are comprehensively and quantitatively analyzed. On this basis

a prediction model is built to perceive the industry development trend. Using the perception result

combined with data such as user’s payment behavior and capacity change

an early-warning model for the electric charge recycling risk is built. The model objectively quantifies the risk probability of user’s electric charge recycling. Finally

the example verification result shows that the model has good predictive ability.