Research On Optimization Design Of Energy Storage Electric Vehicle Charging Station And Optimization Of Charging Strategy

With the proposal of "30.60" dual carbon target in China,it is expected that a large number of electric vehicles will be connected to the power grid in the future.The fluctuation,randomness and uncertainty of charging and discharging of electric vehicles will have an impact on the safe and reliable operation of the power grid,and the development of energy storage technology brings a solution to this problem.Through the application of energy storage technology,the capacity of electric vehicle charging can be improved,which can reduce the operation cost of power supply system and low-carbon environmental protection construction.Based on the above background,according to the charging and discharging characteristics of electric vehicles and the large-scale centralized charging demand characteristics of electric vehicles,this thesis studies the coordinated planning and operation of charging station and distribution network;based on the energy storage system model,considering the large-scale access of electric vehicle charging load,power quality and economy,this thesis constructs the optimal planning scheme of electric vehicle charging station.The main contents of this thesis are as follows(1)Firstly,based on the urban distribution network architecture and traffic flow information,this thesis analyzes the impact of traffic flow on the distribution of charging stations,and considers the relationship between the network loss of distribution system and the number of charging stations and charging rate.Secondly,the economic cost of distribution system,electric vehicle owners and charging station operators is the lowest,The optimal planning scheme of charging pile is constructed,so as to select the location and capacity of the city’s charging station.(2)Construction of random charging prediction model of charging station: firstly,cluster analysis of historical charging load data is carried out to obtain the influencing factors of charging load;secondly,based on the finite two-dimensional life and death Markov chain theory,different charging states of electric vehicles are described;finally,the random charging prediction model of charging station is constructed to provide guidance for the operation and maintenance of charging station.(3)Construction of multi-objective electric vehicle charging scheduling optimization model: firstly,based on the time of use pricing mechanism,considering the demand response characteristics of electric vehicles,and taking the minimum charging cost of charging users and the minimum peak valley difference of power grid as the objective,an electric vehicle charging scheduling optimization mathematical model is established;secondly,an improved sparrow algorithm is proposed,which is based on Cauchy mutation and reverse learning,In order to solve the problem of large number of variables and high speed requirement,the improved algorithm is improved.Finally,the effectiveness of the improved algorithm is verified by simulation.This thesis contains 46 figures,8 tables and 54 references.