Research On The Optimization And Capacity Setting Of Electric Vehicle Charging Station Layout In A Smart City

As part of the infrastructure construction of smart cities,electric vehicle charging stations are of great significance to the sustainable and high-quality development of cities.Reasonable planning of the construction location and scale of charging stations can not only avoid the waste of resources caused by excessive construction,but also improve the operation efficiency of charging stations and enhance the convenience of charging for electric vehicle users.However,at present,the layout planning of charging stations in many cities is not reasonable,resulting in the phenomenon of "having a car without a pile or a pile without a car".To address the problem of unreasonable layout planning of charging stations,this study takes Xi’an city as an example and conducts an in-depth study on the optimization and capacity of charging station layout from the current situation of electric vehicle development and the actual situation of charging infrastructure construction:(1)The problems faced by the construction of charging stations within the city are analyzed from the actual situation of charging station construction.The current research status of charging demand prediction,charging station layout optimization and charging station capacity setting models is sorted out,common model solving algorithms are summarized,the theories related to electric vehicles and charging station infrastructure construction are introduced,and the interests of all parties involved in charging station construction and the principles of charging station layout planning are analyzed.(2)A combined prediction model of car ownership based on the Shapley value method is constructed with two single prediction models,ARIMA and GM(1,1),as the base models.The above model was used to forecast the car ownership in Xi’an,and the results showed that the combined model based on the Shapley value method reduced the prediction error by 1.54%and 2.07%compared with the ARIMA and GM(1,1)models,respectively.A regional electric vehicle ownership prediction method that combines data on population density,area and electric vehicle share in the case planning region is further proposed.(3)A charging station layout optimization and capacity fixing model that considers the interests of both operators and users is established.On the basis of considering the cost of distance loss on the way to charging for users,the cost of time loss in waiting in line for charging,and the construction cost and operation cost of operators,a charging station layout optimization and capacity setting model that fits the actual situation of the case is constructed with the distance between users and charging stations,the number of charging stations,the number of charging piles,and the distance between charging stations as constraints.(4)An improved artificial ecosystem optimization algorithm(IAEO)is proposed.Charging station layout optimization is a multi-variable,multi-constrained,nonlinear mathematical problem,and a solution method for charging station layout optimization based on the IAEO algorithm is proposed for this problem,which improves the original AEO algorithm based on the AEO algorithm by using Tent chaos initialization,improved nonlinear weight coefficients and stochastic backward learning strategy,and the comparison experiments show that after the improved IAEO algorithm’s global search ability,merit-seeking speed and merit-seeking accuracy are significantly improved.(5)The performance of the proposed model and the IAEO algorithm is verified by using two typical regions of Xi’an city as examples.In Case 1,the optimal charging station planning solution solved by the IAEO algorithm saves RMB 747,900,RMB1,164,000,RMB 1,276,500,and RMB 128,500 compared with the solutions solved by the IPSO,ASO,WOA,and AEO algorithms,respectively.The best planning number of charging stations obtained is 7.The number of charging posts in each charging station ranges from 14 to 19.In Case 2,the optimal charging station planning solution solved by the IAEO algorithm saves RMB 260,700,RMB 720,400,RMB 826,800,and RMB114,100 compared to the IPSO,ASO,WOA,and AEO algorithm solutions,respectively.The best planning number of charging stations obtained is 4.The number of charging posts in each charging station ranges from 15 to 17.The above results verify the layout rationality and economic feasibility of the charging station planning scheme solved by the IAEO algorithm.