Research On Energy Storage Configuration Of Photovoltaic Charging Station Based On Orderly Charging Of Electric Vehicles

In recent years,the number of electric vehicle(EV)continues to grow,and a large number of disorderly charging of EVs have a significant impact on the power grid.At the same time,energy storage system(ESS)and photovoltaic(PV)technology are promoted because of the improvement of technical performance and the reduction of cost.The photovoltaic and energy-storage integrated charging station(PESICS)is a diversified application form that combines PV,ESS and EVs,which can effectively reduce the impact of electric vehicle charging behavior on the grid.However,the EV loads and PV powers are highly uncertain.How to realize the coordinated control optimization of "generation-storage-load" of the charging station is an urgent problem to be solved.This paper takes the PESICS as the research object,and systematically studies EV load forecasting,ESS configuration of PESICS and scheduling strategy of PESICS.The research of the paper is organized as follows:(1)The space-time distribution of EV load prediction is studied.Firstly,the types and charging modes of EVs are summarized,and the time-space transfer model of EVs is established based on the travel chain theory.Secondly,with the shortest distance from the destination as the goal,the Dijkastra algorithm is used to simulate the travel path of EVs.Then,according to the measured data,the traffic and temperature energy consumption models of EVs are obtained.Finally,taking an urban area as an example,the temporal and spatial distribution of EV load is obtained by Monte Carlo simulation,and the characteristics of EV load in different functional areas and the influence of traffic and environmental temperature on EV load are discussed.(2)The ESS economic configuration of PESICS is studied.Firstly,the investment cost of the charging station is analyzed in detail,and the ESS life model based on the charging and discharging depth and cycle life is established.Secondly,aiming at maximizing the annual comprehensive income of the charging station and considering the load optimization of the station,a bi-level programming model is established.Then,according to the peak valley electricity price,the corresponding ESS operation strategy is formulated.Finally,the particle swarm optimization algorithm is used to calculate the configuration scheme in the commercial district and the optimization effect of the station load under the configuration scheme,and the state of health of the ESS and various income changes within the investment period are analyzed.(3)The real-time scheduling strategy of PESICS is studied.Firstly,the optimization architecture and real-time scheduling strategy of PESICS are introduced.Secondly,an ordered charging strategy that considering users' the charging demand is introduced.Then,aiming at the fluctuation of EV load and PV power of charging station,in order to achieve the coordinated control optimization among PV,ESS and EVs,a joint optimal scheduling strategy of the charging station based on model predictive control is proposed.Finally,the optimal scheduling results are obtained through simulation analysis,and the key characteristics of the proposed strategy are analyzed.