Estimation Of Electric Vehicle Charging Load And Its Impact On Residential Power Supply

In recent years,with the advancement of science and technology and the continuous improvement of the living standards of residents,the number of electric vehicles has increased rapidly.When large-scale electric vehicles are connected to the distribution network,the total load of the residential distribution network is gradually increased,which may result in Some residential distribution networks are unable to supply power properly.At the same time,the disorderly charging of large-scale electric vehicles will bring risks to the safe and stable operation of the distribution network.In order to avoid overload operation of the transformer,the transformer capacity selection is too large,and the maximum load ratio of some residential transformers is even less than 10%,which increases the investment cost of the distribution transformer.When a large-scale electric vehicle is connected to the grid for charging,taking into account the residents' work habits,the charging load must increase rapidly after work.The charging load of electric vehicles will adversely affect the stable operation of the distribution network.Therefore,it is necessary to analyze the charging load,fully consider the influencing factors of the charging load,study the change of the charging demand of the electric vehicle,analyze the change of the residential load on this basis,and select a reasonable capacity of the distribution transformer of the community.Firstly,the factors affecting the charging load of electric vehicles are analyzed.According to the statistics of the Ministry of Communications,the charging load model is established on this basis,and then the charging load is calculated.The Monte Carlo method is used to generate the load curve of the electric vehicle,and the influence of the disorderly access of the electric vehicle on the grid load of the community is analyzed.The results show that the disordered charging of electric vehicles increases the peak load of the system,which makes the peak-to-valley difference of the distribution network intensified.Second,estimate the state of charge of the electric vehicle.The accuracy of the battery's State of Charge(SOC)estimation will affect the life of the electric car.At the same time,accurate estimation of the SOC of the electric vehicle can fully utilize the battery capacity and improve the safety performance of the battery.After analyzing several SOC estimation algorithms,based on the Kalman filter algorithm,the Kalman filter algorithm is improved.The Kalman filter algorithm based on particle swarm optimization is proposed to estimate the state of charge of electric vehicles.The algorithm not only improves the algorithm.The battery has an accurate estimation accuracy and has better anti-interference ability.Finally,the uncertain factors of charging habits of electric vehicles,including charging time,charging power,charging power,and the influence of uncertain factors on electric vehicle charging demand and cell load curve are analyzed.Taking the initial charging time and the charging power as the control variables,and taking the minimum load variance of the distribution network as the objective function,the optimal adjustment model of the charging load is established.The results show that by adjusting the charging time and charging power to meet the user's charging demand,the impact of the charging of the electric vehicle on the grid can be reduced,so that the charging load of the cell can be accurately predicted,and finally a reasonable cell transformer is selected accordingly.capacity.