A Study Of The Load Demand And Its Impact On Large-Scale Electric Vehicle Access To The Grid

In order to slow down greenhouse gas emissions and reduce dependence on fossil energy,electric vehicles with high efficiency and cleanliness have become one of the strategic emerging industries for the development of China in the new era and play an important role in promoting the energy revolution.With the further development of the electric vehicle industry,China will face the situation of large-scale and ultra-powerful application of electric vehicles in the future.Due to many factors such as the behaviour of EV users and the external environment,the large-scale EV charging load has strong randomness and uncertainty in space and time,which will inevitably bring certain challenges to the safe and stable operation and optimal scheduling of the power grid,not only increasing the peak-to-valley difference of the power grid,pulling down the node voltage and increasing the system network loss,but also causing problems such as transformer and line overload.Therefore,it is necessary to establish a more accurate and effective charging load prediction model to guide users to carry out reasonable charging,and to analyse the impact of charging load access on the power quality of the grid by combining theory with practice,so as to lay the foundation for subsequent research.This paper starts from the factors influencing the charging load of electric vehicles and the theoretical basis of charging load prediction,conducts research on charging load prediction methods,guides users to charge reasonably by setting adjustable charging service fees for public charging stations,analyses the impact of fast charging load guidance strategies on charging load distribution,grid voltage quality,users’ charging location,users’ charging efficiency and charging station power supply revenue,and analyses from theoretical and practical perspectives The impact of large-scale electric vehicle access on the distribution network.The main work carried out is as follows.(1)Analysis of the factors influencing the charging load of electric vehicles and the theoretical basis of load prediction.Firstly,a macro analysis of the current EV charging load influencing factors is conducted,mainly including four aspects of EV characteristics,electrical energy replenishment mode,user behaviour and vehicle power consumption.Then the travel chain theory is briefly introduced,leading to the electric vehicle travel chain on the basis of the definition and types of travel chains.Finally,the Monte Carlo method commonly used in the field of EV load prediction is introduced,laying a theoretical foundation for the subsequent charging load prediction and impact analysis.(2)Research on the spatio-temporal forecasting method of electric vehicle charging load.In view of the uncertainty in the spatial and temporal distribution of the charging load of electric private cars,a prediction model for the spatial and temporal distribution of the charging load of private cars,taking into account the influence of traffic conditions and temperature,is proposed.Firstly,a regional traffic road network model is established using graph theory;then,a spatio-temporal distribution model of vehicle travel is established using travel chain theory,the shortest path of each vehicle journey is planned using Dijkstra method,the real-time electricity consumption per unit mile of vehicle under the influence of traffic road conditions and temperature is obtained using a fuzzy algorithm,and the vehicle travel time and electricity consumption are calculated by combining the real-time traffic road conditions.The charging decision is made according to the user’s next trip,and the charging time and charging load are calculated;finally,the spatio-temporal distribution of charging demand for all electric private vehicles in the target area is simulated using the Monte Carlo method and travel chains.(3)Research on charging guidance strategy for fast charging loads based on adjustable charging service fees.To address the problem that the voltage quality of the distribution network deteriorates due to the access of large-scale EV fast charging loads,a charging guidance strategy based on adjustable and graded charging service fees is proposed to guide users to adopt the charging location decision with the lowest overall charging cost,thereby balancing the charging load distribution at each charging station and improving the voltage quality of the distribution network.Firstly,a fast charging load prediction model based on travel chain theory and Monte Carlo method is developed,taking into account the regional road network and distribution network constraints,and the change of users’ travel time and space trajectory and fast charging demand decision are depicted in detail.Then,a weighted decision model with the lowest comprehensive cost of charging service fee,travel time and power consumption is constructed.Finally,it is proved that the adjustable graded charging service fee at public charging stations can guide users to change their charging locations more effectively than the fixed charging service fee,change the spatial and temporal distribution of fast charging loads,improve the voltage quality of the distribution network,and reduce the charging cost of users to a certain extent.(4)Research on the impact of electric vehicle access on the power quality of the distribution network.Firstly,based on the charging load prediction results,the impact of EV access with different penetration rates on the power quality of the typical IEEE30 node distribution network is analysed theoretically.Subsequently,from a practical point of view,the charging load characteristics of typical grid plots in Fengxian area are analysed by means of data statistics and clustering methods.The impact of charging load access on the typical distribution network in the Top3 grid parcel is also analysed in terms of distribution network node voltage and transformer load factor based on the Matpower toolbox of Matlab software for tidal current calculation.Finally,station location and capacity predictions are made for future charging stations in typical Fengxian plots to provide suggestions for future planning of charging stations in the area.