Analysis Of Charging Behavior Of Electric Vehicles And Research On Optimization Of Charging Facilities Planning

Electric vehicle(EV)has the advantages of energy saving,environmental protection and clean energy.The promotion of electric vehicles helps alleviate energy shortages and environmental pollution,and has gradually received attention from countries around the world.Vigorously developing electric vehicles is very important to achieve a comprehensive energy transformation in the transportation field.In order to reduce the impact of large-scale electric vehicle access on the power grid,analysis of electric vehicle charging behavior can improve the reliability and economics of power grid operation.As the most basic supporting facilities for electric vehicles,the reasonable planning of charging facilities can accelerate the formation of the electric vehicle ecosystem and improve the economic benefits of charging facilities.The research work in this paper is mainly focused on the following aspects:Firstly,in view of the problem of privacy leakage risk in the process of data clustering,in order to ensure the availability of clustering results and the security of data,an electric vehicle charging data clustering algorithm under differential privacy protection is proposed.The privacy of the algorithm is proved by theoretical analysis.Then,in order to solve the problem that the random charging behavior of electric vehicles affects the stability of the power grid,at the same time,in order to improve the charging service,based on the real electric vehicle charging data,a charging data clustering algorithm under differential privacy protection was used to design an electric vehicle charging behavior analysis model.The classification of electric vehicle users is achieved through experiment,and the characteristics of the charging mode corresponding to each user are analyzed.Finally,according to the planning needs of electric vehicle charging facilities and the social cost of charging facilities,a method for planning charging facilities based on an improved k-means algorithm is proposed.The minimum total cost of the whole society is taken as the objective function of the planning,and the optimal number of charging stations corresponding to the minimum social cost is taken as the optimization goal.Experiments are carried out using calculation examples to obtain the optimal location and number of charging stations with the lowest cost in a certain area,which proves the effectiveness of the proposed method.