Firstly

based on the combined prediction model of grey prediction model

linear regression model and BP neural network model

the traditional car ownership prediction curve is calculated

and three parameter values of traditional car ownership based on Bass model are fitted by nonlinear square method. Then

through the Delphi method based on AHP

the relationship between parameters of traditional vehicles and electric vehicles is constructed

and the Bass model that can predict the number of electric vehicles is obtained. On the basis of the prediction results of the inventory

the Monte Carlo algorithm is used to simulate the electric private cars

electric buses and electric vehicles in the city by combining the initial charging time

daily mileage

battery parameters

charging efficiency and other influencing factors of the user’s use of electric vehicles. The load prediction of electric vehicles are completed. The application of this method for electric vehicle load prediction has higher accuracy and better effect.