Research On Ordered Charging Strategy Of Electric Vehicle Based On Demand Response

With the economic development and the deterioration of the environment,more and more electric vehicles have entered every household.The advantages of electric vehicles are high energy efficiency and low pollution,which are valued by all countries.However,as the number of electric vehicles connected to the electric network increases,A large number of chaotic charging of electric vehicles will bring pressure on the safe and economic operation of the grid.How to charge EVs orderly and utilize them will be the focus of this paper.In this paper,firstly,the battery life loss of electric vehicles is studied.The factors that affect the battery life are analyzed by taking lithium-ion battery as an example.The models of the influence of charge-discharge depth and temperature on the life are established respectively.The model has been refined to make it more accurate when calculating life loss in V2 G.Secondly,it analyzes the factors that affect the load of electric vehicles and analyzes the first travel time,the daily driving distance and the end of the last travel time according to the National Transportation Survey(NHTS)by the U.S.Department of Transportation Probability density distribution.Established a model of electric vehicle charging load,and through this Monte Carlo simulation to get 300 electric vehicles in a distribution network within the disorderly charge of the load curve can be obtained through the analysis of the disorderly charging of electric vehicles caused peak load difference Increase,threatening the safe operation of the grid.Finally,based on the battery temperature loss coefficient and the charge-discharge depth influence coefficient obtained in Chapter 2,the EV evaluation system is established to evaluate the participation of EV users to screen EVs that are suitable for V2 G.On the user side,based on the improved model and time-of-use price of battery depth and loss in Chapter 2,the first phase optimization of minimizing user cost as the objective function is established.Then,On the distribution network side,the second phase optimization with objective function of minimizing the variance of distribution network load with grid excitation is established,and the optimization results of the first phase are used as constraints to protect the interests of users.