Research On Electric Vehicle Charging And Discharging Strategy Based On Stopping Mode

Problems such as air pollution and shortage of resources are imminent,and more environmentally friendly new-type vehicle electric vehicles are also needed.As a power unit,the charging behavior of the electric vehicle is random in time.When a large-scale electric vehicle is freely connected to the grid,it is bound to have a negative impact on the grid load;as an energy storage unit,a large-scale electric vehicle has a non-negligible electrical energy reserve,and reasonable application can bring auxiliary effects to the grid through the power supply.Therefore,under the premise of satisfying the electric vehicle user's charge and feed demand as much as possible,through charge and feed strategic dispatch,can reduce the adverse impact on the power grid caused by load changes during charging,and at the same time,it can also use the electric vehicle to feed power.It assists the peak adjustment of the power grid and gives the user an economic subsidy,which has a win-win effect on the grid and the user side.In order to better estimate the charging value of the electric vehicle,this paper establishes the charging model through the probability distribution of the starting time and the daily driving distance of the electric vehicle.Thus using the Monte Carlo method to simulate the charging curve of three brands of electric vehicles under different scales of application.From the simulated data,with the increasing in the scale of electric vehicles,the pressure on the grid due to the charging load has also increased.In order to reduce the unfavorable influence on the load of the grid which is brought by the unorderd charging mode of electric vehicles.And from the perspective of the user side to meet the needs for charging of more users as much as possible.This paper proposes an intelligent charging strategy based on variable power distribution.Through the power changes to develop a better charging scheme to ensure the fairness of the user charging and achieve a better filling effect.And through the simulation data can be found,through the variable power distribution algorithm scheduling,the completion of the charging needs of the vehicle is better than unordered charging even better than regular ordered scheduling.This paper proposes a ladder time-sharing charging price model and a power distribution charging scheduling model,and uses an improved genetic algorithm to solve the problem.The reasonable results are obtained through reasonable simulation data.Finally,this paper also studies the role of electric vehicles as an energy storage unit in providing auxiliary services for peaking the grid.In order to reflect the effectiveness of the power-feed scheduling strategy better,this paper elicited a ladder time-sharing price for charging and feeding,and considered the cost of the battery's loss by the times of charging.The goal of economic benefits was compared from the user's side before and after the satisfaction of the scheduling.From the grid side,and with the grid load curve as an indicator,the effect of the intelligent charge and feed scheduling model in peak load shedding is measured.The results of the example analysis show that not only the user-side satisfaction is improved,but also grid-side peak-cutting and valley-filling effects are significant,and the grid peak-to-valley difference is reduced,and the grid daily load curve becomes smoother.