Monte Carlo Method-Based Prediction Of Charging Load Of Large-Scaled Electric Vehicles

As a new energy vehicle,electric vehicles have the advantages that cannot be surpassed by traditional fuel vehicles in terms of improving the environmental pollution and energy shortage,and will certainly be developed and applied in large scale in the future.However,the regulation of the charging of large-scale electric vehicles cannot be controlled in an orderly manner,which will certainly cause some negative impact on the existing power grid.The prediction of the charging load of large-scale electric vehicles is to plan the future development of electric vehicles and ensure the safety of the power grid.Therefore,based on the Monte Carlo simulation method,this paper studies the charging load prediction of large-scale electric vehicles.The main contents include the following aspects:First of all,the development of large-scale electric vehicles will play an important role in environmental,energy and social development.It is pointed out that the electric vehicle charging load forecast is the premise and basis for the development of electric vehicles,and the research status of electric vehicle charging load forecasting and electric vehicle ownership at home and abroad is introduced.Summarizes the deficiency of current electric vehicle charging load forecasting model,and clarifies the importance and necessity of predicting the charging load of electric vehicles.Explained and excavated the various factors affecting the charging load of electric vehicles,from the type of electric vehicle,the type of power battery,the power supply mode,the charging characteristics,the charging start time,the average daily mileage,the power battery state of charge,charging power and other key research.Accurately grasp the status quo of the influencing factors of electric vehicle charging load,establish the function and parameters of the electric vehicle charging load forecasting model,and lay the foundation for the prediction of the charging load of large-scale electric vehicles.It is pointed out that the prediction of the charging load of electric vehicles depends fundamentally on the quantity of electric vehicles.Since the traditional inventory forecasting method cannot be applied to the prediction of electric vehicles,the Box-Cox Dogit model is used to calculate the maximum share of the electric vehicle market.Combining the Bass model based on time changes,a prediction model for electric vehicle ownership based on multiple factors was established.Through the analysis of traditional vehicle ownership data over the years,and using a multi-factor based prediction model for electric vehicle ownership,Beijing City predicts the amount of EVs for various uses in Beijing.Finally,combined with the Monte Carlo simulation method,the influencing factors of electric vehicle charging load,driving data and parameters,a large-scale electric vehicle charging load model based on Monte Carlo method is established.According to the predictive data of electric vehicle ownership for various uses in Beijing,the load forecast of electric vehicles for various purposes in Beijing was obtained and the load forecasting curve was obtained.Superimposed the prediction curve of the charging load of electric vehicles for each purpose,the total charging load forecast curve of Beijing can be obtained.The analysis shows that the charging load of Beijing’s electric vehicles after large-scale access to the power grid will peak at a certain moment,which may have a negative impact on certain local distribution networks.It is necessary to effectively control the chaiging load of electric vehicles.