Research On Electric Vehicle Charge And Discharge Scheduling Strategy In V2G Application Scenarios

In recent years,people around the world have gradually become more concerned about the environment and resources,and the issue of energy transition reform has received extensive attention.Electric vehicles use clean and efficient electric energy instead of traditional fossil energy sources as their power source.They have the advantages of environmental protection,energy saving,and low noise.The large-scale development of electric vehicles is an effective measure to accelerate the energy transition.However,the charging load of electric vehicle group is centralized,which will bring adverse effects such as load fluctuation and power loss to the power grid.Therefore,it is necessary to study the charging strategy of electric vehicles.In the V2 G application scenario,electric vehicles can reduce the negative impact of their own charging load on the grid through charge and discharge scheduling,and have a positive effect in peak shaving and valley filling,and improving the economic efficiency of vehicle owners.Therefore,the research on electric vehicle charging and discharging scheduling in V2 G application scenarios has important practical significance.First,this paper establishes an electric vehicle charging load model that considers factors such as daily mileage,initial charging time,and charging duration,and uses Monte Carlo method to solve it.Through simulation,the load change of a certain area after the electric private car is connected is obtained,and the influence of the charging load on the total load distribution in the area is studied.Taking the 33-bus system as an example,the influence of electric vehicle charging on the network loss and voltage offset of the system is studied.Secondly,considering the user autonomy,based on the master-slave game theory and smart grid electric vehicle intelligent charging and swapping technology,this paper proposes an intelligent charging scheme with time-of-use price as the guiding means;combined with the basic load of each period of the grid,the time-of-use price is determined by using fuzzy membership function;a one-way mode multi-objective scheduling model of electric vehicle charging is established,The particle swarm optimization algorithm is used to solve the Pareto optimal solution of the model.The results show that the proposed charging strategy can reduce the charging cost of users,reduce the peak valley difference of power grid load,and achieve the expected goal.Finally,this article studies the charging and discharging scheduling strategy of electric vehicles in V2 G mode.In order to study whether the battery of an electric vehicle has enough power to support its participation in V2 G mode scheduling after driving and consuming power,the charging and discharging capacity of the electric vehicle is modeled and analyzed.This paper establishes the electric vehicle charging and discharging model,which includes charge and discharge SOC,charge and discharge time,charge and discharge load,and discuss related calculation methods.In order to reduce grid load fluctuations,this paper proposes a dispatch strategy for electric vehicles to participate in grid peak shaving.Through simulation,it is found that electric vehicles have good peak-shaving capabilities,which can significantly reduce the peak load of the grid and increase the valley load of the grid.In this paper,a multi-objective dispatching strategy model for electric vehicles under V2 G mode is established and simulated with the goal of the minimum change of power grid load and the minimum charge and discharge cost of vehicle owners.The results show that the proposed V2 G mode scheduling strategy has a great effect in reducing load fluctuations in this area,and at the same time can bring economic benefits to vehicle owners.By analyzing the effects of different scheduling strategies in reducing load fluctuations,reducing load peak-valley differences,and improving the economy of vehicle owners,it is found that the electric vehicle scheduling strategy under the V2 G mode is more superior than the one-way scheduling strategy.This article has 46 figures,13 tables,and 81 references.