Planning And Energy Efficiency Evaluation Of Electric Vehicle Charging Station Based On Gravity Model

In recent years,energy and environmental issues have become increasingly prominent.Electric vehicles powered by clean energy have emerged as the times require,and have developed rapidly under the impetus of local policies.The increase in the number of electric vehicles is of great significance for reducing carbon dioxide emissions,promoting environmentally sustainable development,and creating an environmentally friendly ecosystem.However,the rapid development of the electric vehicle industry has also put forward new requirements for electric vehicle charging infrastructure,and how to rationally plan electric vehicle charging stations has attracted more and more attention.This paper firstly studies the influence of the external environment on the charging load of electric vehicles,and revises the traditional travel chain taking into account the user’s willingness to travel.Based on the gravitational model,the attractiveness of electric vehicle charging stations to electric vehicle users is described,and the area is realized.The selection of internal charging stations and the calculation of the time and space distribution of electric vehicles in the area;then,with the lowest total cost of the whole society and the smallest distribution network loss as the optimization goal,a multi-objective planning model for electric vehicle charging stations was established to realize the charging station Finally,based on the planning results of the charging station,an energy efficiency evaluation system for electric vehicle charging stations was established.According to the combination of weights based on the non-cooperative game method,evaluated the energy efficiency of the charging stations.The main work of this paper is as follows:Considering the problem of insufficient subjective of electric vehicle users’ travel,a prediction model of temporal and spatial distribution of electric vehicle charging load based on an gravity model is proposed.First,the influence of ambient temperature on the battery performance of electric vehicles and the opening of the air conditioner is considered,and the corresponding relationship between energy consumption and ambient temperature is revealed.Then,the influence of the external environment on the user’s willingness to travel is studied,and a travel chain model modified based on the willingness to travel is obtained.Finally,in view of the characteristics that the selection of charging stations for electric vehicles in the road network is affected by many subjective factors,an electric vehicle charging station selection model based on the gravity model is proposed,which describes the law of electric vehicle users’ selection of charging stations in the road network,and The choice of charging station with and without the coupling of electric vehicles is studied respectively.After the location,number,and scale of charging stations are determined,a more accurate description of the temporal and spatial distribution of electric vehicles in the road network is obtained,and the temporal and spatial distribution of the charging load in the area is obtained,and the result is compared with the result that does not take into account the user’s willingness to travel.The influence of users’ willingness to travel on the temporal and spatial distribution of charging load is studied.Aiming at the problem of charging station planning that only considers users and the economic indicators of the charging station side,a multi-objective charging station location and capacity strategy that takes into account the cost of the whole society and the loss of the distribution network is proposed.Taking the lowest cost of the whole society as the economic indicator,and the minimum total network loss of the distribution network as the technical indicator,a multi-objective optimization model considering economy and distribution network loss is established.The electric vehicle charging station selection strategy based on the universal gravitation model adopts particles.The group algorithm calculates the Pareto optimal frontier of the charging station optimization results,and obtains the satisfaction of each Pareto optimal solution through fuzzy mathematics,and finally obtains the number of electric vehicles charging stations that take into account the total cost of the whole society and the distribution network loss Target optimization results.Compared with the single-objective optimization results that only take into account the economic cost and the single-objective optimization results that only take into account the distribution network loss,the effectiveness of the proposed strategy is verified.In view of the fact that there are more plans for the area to be built in the current research on charging facilities,and there are fewer energy efficiency evaluations for the charging stations to be built or the charging stations that have been built,energy efficiency evaluation is carried out based on the planning results of electric vehicle charging stations.By comparing and analyzing the currently commonly used evaluation methods,the uncertainty analytic hierarchy process based on subjective analysis and the entropy weight method and gray correlation analysis method based on objective analysis are selected,and the index weights are modified by the cooperative game method,and the electric vehicle charging station is established.The energy efficiency classification and evaluation index system comprehensively evaluate the energy efficiency of charging stations,which solves the problem that the current energy efficiency analysis of electric vehicle charging stations is usually subjectively evaluated and lacks quantitative indicators for objective evaluation.After the evaluation,the compromised optimal solution of the third part and the two optimal solutions on the Pareto front are selected for comparison,which verifies the effectiveness of the proposed evaluation system and can be used to guide the actual charging station planning of the project.