Research On Electric Vehicle Charging Load Model And Coordinated Charging And Discharging Optimization Strategy

Under the background of China’s “30·60” Carbon-neutral Targe,the government has issued relevant policies to vigorously support the development of the electric vehicle（EV）industry,and the scale of EVs is increasing day by day.However,uncoordinated charging of large-scale EVs will have many impacts on the power grid,such as reducing voltage quality,affecting the economy and stability of power system operation.As a flexible energy storage resource,the orderly regulation of the charging and discharging behavior of electric vehicles through a reasonable and effective charging and discharging optimization strategy can give full play to the potential of flexible energy storage resources for large-scale electric vehicles,improve grid load distribution,reduce charging costs,meet grid peaking demand and improve vehicle charging economy.This paper considers the user’s travel rule and other factors,and focuses on the EV charging load model,the improvement of the particle swarm optimization algorithm,the coordinated charging（charging and discharging）optimization strategy and the charging and discharging optimization benefit evaluation method.This paper considers the user’s travel rule and other factors,focuses on the EV charging load model,the improvement of the particle swarm optimization（PSO）algorithm,the coordinated charging（charging and discharging）optimization strategy,and the charging and discharging optimization benefit evaluation method.Firstly,the trip chain theory is introduced to analyze the travel characteristics of EV users,and each characteristic quantity in the travel chain of the user is fitted to establish the travel rule model of the user based on the NHTS trip data.On this basis,considering factors such as weather,temperature,road network-grid topology,and traffic conditions,the EV charging load model is established,the spatiotemporal distribution of EV charging load is simulated by the Monte Carlo method,and the influence of uncoordinated charging on the distribution network load distribution and node voltage are analyzed.The simulation results show that the travel and uncoordinated charging behaviors of EV users have obvious spatiotemporal distribution characteristics,and the uncoordinated charging of EVs will increase the voltage offset of each node,especially the terminal node of the distribution network.Secondly,the traditional time-of-use electricity price and real-time electricity price charging demand response mechanism are prone to new load peaks during the load trough period.In addition,due to the long parking time of EVs in residential zones,the coordinated charging optimization process is prone to dimensional disaster and particles fall into local optimum.To solve the above problems,an adaptive improvement method of PSO algorithm and an optimization strategy based on dynamic time-of-use electricity price are proposed.By establishing a multi-objective function with the most charging amount and the least charging cost,the charging power of the EV in each period is dynamically optimized according to the power grid’s real-time electricity price.The simulation results show that the proposed improved PSO algorithm can effectively improve the convergence speed of particles and reduce the amount of calculation in the optimization process;the proposed coordinated charging optimization strategy can effectively reduce the charging cost of EVs and the peakto-valley difference of grid load.Finally,the optimization strategy of EVs charging and discharging is studied considering the time-space distribution of users’ travel rules.By taking into account the autonomy of users to participate in coordinated charging and discharging,a two-stage optimization strategy for coordinated charging and discharging is proposed,which reduces the user charging cost,grid load peak-to-valley difference,and distribution network node voltage offset,while reducing the optimization dimension and the amount of computation for the charge-discharge optimization process.In addition,a method for evaluating charge-discharge optimization benefit is proposed.The proposed method establishes a C-S coordinate system according to the rate of change of charging capacity and the rate of change of charging cost and evaluates the optimization benefit of charging-discharging by comparing the position of the user’s virtual participation in charging and discharging optimization and the position of the optimization benefit reference coefficient in the C-S coordinate system.The simulation results show that the proposed charging-discharging optimization benefit evaluation method can effectively evaluate the benefits of users’ virtual participation in the coordinated chargingdischarging process,which provides a reference for users to choose optimization schemes independently,ensuring the economy of users participating in coordinated charging and discharging.