Research On Electric Vehicle Charging Load Modeling And Charging Optimization Guidance Strategy

Electric vehicles(EV)have unique advantages over traditional fuel vehicles in terms of reducing air pollutant emissions,saving energy,and mitigating climate warming.Therefore,they have received widespread attention from the government and society.Uncertainty.With the continuous expansion of the number of EVs,accurate simulation of EV travel characteristics and charging needs is an issue that needs to be studied.At the same time,disorderly charging of EVs will adversely affect the safe and economic operation of the power grid.Research on charging optimization guidance strategy.To address the uncertainty of temporal and spatial transfer and charging behavior of electric vehicles,a trip chain based temporal and spatial distribution method is presented for simulating EV charging loads.First,employing the trip chain concept,the feature quantities and state quantities of the temporal and spatial distribution in the daily traveling of EVs are presented.Based on the household travel survey data,a charging area is divided into six categories,and the Markov process is used to simulate the space transfer characteristics of EVs.Secondly,considering the impacts of time-of-use electricity price on the distribution of charging loads,the EV energy consumption model is established considering EV weights and ambient temperature.Finally,the well-established Monte Carlo(MC)simulation method is used to examine various scenarios,including different types of EVs with different vehicle weights and under various temperatures,and the charging loads in each charging area can be attained.Simulation results show that the presented model can accurately simulate charging demands of EVs under various temporal and spatial distributions.The disordered charging of EVs will pose a threat to the safe operation of the power grid.Inspiring EV users to respond and participate in charging optimization guidance strategies is of great significance to improve system safety.In order to fully stimulate the responsiveness of EV users,based on the time-of-use electricity price,the user’s reward mechanism for reducing grid load fluctuations is introduced.Based on the charging optimization management scheduling structure,an EV charging optimization guidance strategy considering the reward mechanism is proposed.The choice of charging location has uncertain EV users and users with relatively fixed charging locations consider the travel needs of users and take the overall user satisfaction as the goal;finally,consider the user’s responsiveness to the scheduling strategy to solve the proposed optimal scheduling model.The results show that the optimized scheduling model can effectively improve the problem of local load peaks,meanwhile,it can reduce grid load fluctuations and user charging costs,and it has certain reference for EV charging optimization guidance.This paper analyzes the travel characteristics and charging requirements of EVs in detail,establishes a charging load model that considers the EV space-time distribution,analyzes the impact of EV charging loads on the power grid,and studies the EV charging optimization guidance strategy that considers the reward mechanism to model the EV charging load And the study of charging optimization guidance strategy provides reference.