Orderly Charging Strategy Of Electric Vehicle Based On Time-Sharing Price

With the increasingly severe global energy crisis and environmental pollution,various countries around the world have formulated relevant policies for the distribution of energy,and China has increased the promotion of electric vehicles for the deterioration of the traffic environment.In recent years,the state has implemented many policies on electric vehicles.For example,the Notice on Further Improving the Financial Subsidy Policy for the Promotion and Application of New Energy Vehicles has implemented new subsidy schemes in first-tier c ities such as Beisheng and Guangzhou,which further shows the determination of the state in the field of promoting electric vehicles,At the same time,with the mass production of electric vehicles,the distribution facilities of the old charging equipment residential areas are also facing the trend of renewal.The large-scale charging of electric vehicles will bring many proble,ms to the load of power system,such as the impact on the distribution network power,the impact on the reliability of power system and so on.Therefore,the charging problem of electric vehicles should be planned in an orderly way.This paper is divided into four parts to discuss the charging of electric vehicles1)Firstly,by introducing the backgrou nd of EV and the recent research situation at home and abroad,the article points out many problems about the disrderly charging of EV.2)Monte Carlo simulation is used to simulate the stochastic fitting function of the return time,departure time and mileage of the electr ic vehicle,and the disordered charging mo,del of the electric veh icle is established.3)Through the influence of disorderly charging of electric vehicles on power grid,the difference between real-time price and time-of-use price is briefly analyzed,and the division of peak and valley periods of real-time price is determined.Subsequently,an orderly charging mathematical model based on m ulti-objecti ve functions of peak-valley difference,load standard deviation and user price is established.Then the improved particle swarm optimization algorithm is introduced to solve the mathematical model.