Study On Location Of Electric Vehicle Charging Station Considering Of Charging Demand

China’s automobile market has experienced a period of rapid development for ten years,and the number of new energy vehicles continues to rise,but the level of new energy vehicle charging and replacement infrastructure is relatively insufficient.Therefore,the energy supplementary efficiency of electric vehicles has become a difficulty restricting the sustainable and efficient development of the industry.Based on traffic allocation theory and dynamic programming theory,this thesis considers users’ charging demand,takes pure electric vehicles as the research object,and conducts grid demand analysis from the perspective of space to discuss EV charging demand prediction and charging station location optimization.First of all,the advantages and development prospects of charging stations compared with changing stations are expounded by classifying and discussing the mechanism and information interaction mode of charging stations,as well as the operation characteristics of facilities and equipment and the advantages and disadvantages of various modes.The definition,characteristics and influencing factors of charging demand are given.Secondly,this thesis clarifies the basic theory of EV charging demand prediction,and clarifies the conversion relationship between the number of EV and charging demand by analyzing the influencing factors of urban vehicle ownership and the share rate of EV in urban vehicles.The final prediction result of EV charging demand is obtained by using the weighted combination of grey prediction model based on particle swarm optimization algorithm and BP neural network algorithm.In the process of studying the time cost of users’ charging behavior,this thesis takes into account the time variability of the driving speed of electric vehicles in the road section between the nodes of the traffic network,based on the traffic allocation and dynamic traffic flow theory,introduces the delay coefficient of the road section driving process,takes the POI intensity and delay level as the standard,reasonably calculates the range of the road section driving time,and conducts inductive analysis on it.By dividing the grid,the user needs are analyzed and described spatially.Finally,this thesis establishes a multi-objective planning model for charging station location.Under the premise of ensuring the minimum cost,this model fully considers the importance of user charging process time cost to the selection of charging station location scheme,takes the number of charging facilities and the selection scheme as two decision variables,and adds the influence of demand space division on the construction scale and selection of charging station in the constraint conditions.The objective function of the model is normalized by linear weighting method.Then,taking an urban planning area in Jinan city as an example,enumeration method and genetic algorithm improved by elite strategy were used to solve the target model.Based on the purpose of ensuring the stability of users’ charging needs,the investment cost and site selection scheme changes of charging stations with redundant charging facilities were proposed.Finally,reasonable suggestions for future site selection of charging stations were given.