Research On Orderly Charging Strategy Of Electric Vehicles Under V2G Mod

Today,with frequent environmental problem,our government has put forward the goal of "carbon peak,carbon neutral",and the problem of "carbon emission" generated by fuel vehicles is getting more and more attention.Electric vehicles use electricity as the driving energy,which has great advantages in reducing exhaust pollution and alleviating the energy crisis.The charging behavior of electric vehicles varies greatly depending on the type of electric vehicles and the charging habits of users.As the scale of electric vehicles increases,the disorderly connection of their charging loads to the power grid will have a negative impact on the power grid,such as increasing line loss,reducing power quality,and increasing the difficulty of grid dispatch.Electric vehicles are more flexible as energy storage devices and have great potential to participate in grid dispatch.With the development of Vehicle-to-Grid(V2G)technology,EVs can be connected to the grid for charging as a load during low load hours and supplying power to the grid as a power source during peak load hours,relieving the operational pressure on the grid.The potential of EVs to participate in grid dispatching can be fully utilized through reasonable charging load prediction and formulation of effective charging and discharging optimization strategies.In this paper,the establishment of an EV charging load model and the optimization strategy for orderly charging and discharging are investigated,taking into account user demand and travel rules.Firstly,the factors affecting the charging load of EVs are analyzed,and the EVs are classified into different categories according to their usage.On this basis,the composition and principle of V2 G system are introduced,and the architecture of EV participation in orderly charging and discharging is further explained.And the peak load,load variance and peak-to-valley difference ratio are selected as the main evaluation indexes to evaluate the grid quality.Secondly,this paper investigates different types of EVs and analyzes their charging start time,daily driving mileage and battery charge state at the start of charging according to their different categories,and establishes a charging load prediction model based on the travel data of each type of EV.The simulation analysis is carried out by using Monte Carlo method to obtain the charging load curves of each type of EVs,and the charging load curves are superimposed with the base load curves.The simulation results show that there is great variability in the charging load of different categories of EVs,and the disorderly charging load of EVs will increase the peak-to-valley difference and load variance of the grid load,which will adversely affect the stable operation of the grid.Finally,the traditional time-of-use tariff optimization strategy tends to form new load peaks during low tariff hours.To address this problem,an orderly charging and discharging optimization strategy based on Particle Swarm Optimization(PSO)algorithm is proposed.By establishing a multi-objective function with minimum load fluctuation and minimum charging cost,the charging and discharging power of electric vehicles is optimized in real time according to the time-of-use tariff.The simulation results show that the proposed orderly charging and discharging optimization strategy can not only effectively reduce the impact of EV charging load on the grid,but also significantly reduce the charging cost of EVs.