Prediction of urban electric vehicle charging load based on Monte Carlo method

In recent years, the number of electric vehicles in China has shown a high growth trend. In response to the impact of the uncertainty of electric vehicle charging load on the power grid, a method based on an improved Bass model is proposed to predict the number of electric vehicles. On this basis, a Monte Carlo method for predicting urban electric vehicle charging load is constructed. Firstly, by improving the nonlinear least squares method, the model parameters were estimated and preliminarily optimized. A combined prediction model was proposed to analyze the number of traditional cars, and the Delphi method based on the analytic hierarchy process was used to establish the connection between traditional cars and electric cars, in order to predict the number of electric cars; Secondly, based on the Monte Carlo method, simulate the travel habits of urban electric vehicle users, predict the disorderly charging behavior of electric vehicles, and form the daily load curve of electric vehicles; Finally, a simulation model was established based on actual data from Baiyin City, Gansu Province to verify the feasibility of the model.