Locating And Sizing Optimization Method For Fast Charging Stations Of Electric Vehicle Based On Analysis Of Users' Travel Characteristics

Environmental pollution and oil shortage forces the transportation industry towards the direction of green,energy saving,electric vehicle that has the characteristics of low energy consumption,zero emission,low noise and other characteristics has received extensive attention.Large-scale application of electric vehicles can effectively reduce automobile exhaust emissions and the dependence on oil resources,and perfect fast charging station service network is the important guarantee to the popularity of electric vehicles.Electric vehicle fast charging stations are a crucial supporting facility for the rapid power supply of electric vehicles,charging station planning is prerequisite to promote the construction of charging stations facilities,the popularity of electric vehicles and support a wide range operation of electric vehicles.Firstly,the paper presents a method of the electric vehicle fast charging demand calculation based on the analysis of the user's travel characteristics from the total amount of the user's travel,the travel time distribution,travel mode,travel distance and other characteristics the start.According to the total travel amount and travel time distribution of the users throughout the day(Residents travel amount in each period of time accounts for the proportion of the total travel amount throughout the day),obtains the total travel flow of road network in each time period.Analysis of the influence of whether charging station is constructed on the user's path selection by the cumulative prospect theory,and with the help of stochastic user equilibrium assignment model based on cumulative prospect theory,calculates the path flow for each time period.According to fuel vehicles and electric vehicles two types of travel tools,the travel amount that residents choose electric vehicles as travel tools accounts for the proportion of total travel amount is analyzed based on the discrete Logit model(electric vehicle travel share rate),and gets the number of electric vehicle on each path for each time period.By electric vehicles battery state of charge(SOC)of unit time travel distance,analyzes the probability of electric vehicles with low battery need to recharge during travel,determines the number of electric vehicles to enter the charging station in each period of time,and correspondingly obtain the charging power of charging stations in each time period.Secondly,on the basis of analyzing behavioral characteristics of electric vehicle into the charging stations,depicting the queuing behavior of electric vehicles based on mixed queuingmodel.In peak period the waiting time of user,queue loss rate of charging station and in valley period the utilization of the charger constraints,the paper puts forward the fast charging station capacity optimization configuration method based on M/M/s/K mixed-queuing theory,to determine the optimal number of chargers of fast charging stations.25 nodes traffic network is used as an example for the simulation calculation,comparative analysis of the number of charger optimization results under different candidate site,and discusses the user travel time distribution,the electric vehicle travel share rate on the influence of sizing optimization of fast charging station,study case results show that the number of chargers are a positive correlation with the product of users' travel amount and charging probability during peak period,and are proportional to the electric vehicle travel share rate.Finally,on the basis of electric vehicle fast charging demand calculation and sizing optimization on the charger,in order to meet the power balance constraint,line transmission power constraint,voltage constraint of the charging stations connected to the distribution network,capturing traffic and service radius of charging stations constraints,the minimum sum of charging station investment cost and electric vehicle users charging costs is taken as the goal,proposes the fast charging station location optimization model.The paper uses binary particle swarm optimization algorithm to solve the fast charging stations locating model,25 nodes traffic network and 33 node distribution network couple system is used to be numerical simulation.Comparative analysis of charging station location optimization results under different number of fast charging station,mainly discussed the impact of the user path route choice that considering charging stations construction decision before and after and travel time distribution,the electric vehicle travel share rate and other behavior characteristics on the locating of the fast charging station.The simulation results shows that the user path route choice behavior that considers the charging station construction decision has an influence on the locating of the fast charging station;The investment operation cost of the candidate charging station and the charging cost of the electric vehicle users are reduced with the advance of the travel time of the users during the peak period,and are increased with the increase of electric vehicle travel sharing rate.Under the coupling system of the 25 node traffic network and the 33 node distribution network,the location decision of the chargingstation is decided by the comprehensive cost of the charging station,and is not affected by the travel time distribution of the users and the sharing rate of the electric vehicle.