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Research On Location Of Charging Station For Urban Pure Electric Vehicles

Posted on:2019-03-15Degree:MasterType:Thesis
Country:ChinaCandidate:E Z PangFull Text:PDF
GTID:2382330548988564Subject:Engineering
Abstract/Summary:PDF Full Text Request
In recent years,with the worsening regional haze and fog in our country,the awareness of protecting the environment and conserving resources has been deeply rooted in the hearts of the people.It's clearly stated that "building an ecological civilization is the grand occasion for the sustainable development of the Chinese nation" in the report of the 19 th National Congress of the CPC.Nowadays,our country is facing more serious resource crisis and environmental crisis,therefore vigorously developing electric vehicles become an important measure to solve the double crisis.However,the development of electric vehicles in our country is very slow compared with other developed countries at present.The fundamental problem is that the quantity of electric vehicle charging infrastructure in China can not be matched with that of electric vehicles.Consequently,the government has promulgated the layout plan,subsidy awards,the building standards and other aspects of policies to speed up the development of charging facilities.As the electric car charging station prior period huge investment,it is particularly important to scientifically siting with the minimum overall cost to meet customer demand for charging.This paper gives full consideration to the economic construction of the charging station,user convenience,safe operation of location based on the factors that affect the improvement of the traditional multi-objective programming model,a multi-objective planning decision utility function of charging station location optimization model based on the proposed electric vehicle charging station location of city specific steps.The effectiveness and to verify the model and the location method through a specific case study,provides a reference for other similar city electric vehicle charging station location.The main contents of this paper are as follows:The factors affecting the location of city electric vehicle charging station are analyzed.The author mainly considered the impact of investment cost,operation and maintenance cost,surrounding traffic conditions,traffic flow,power grid security,reliability,geographical environment,social environment,infrastructure environment and other factors on charging station site selection.In the modeling part,corresponding constraints were formed according to each factor.This paper built a multi-objective optimization model of city electric vehicle charging station location.Based on the traditional multi-objective programming model,the model introduced the utility function of the decision maker to solve the drawbacks of the past function in dealing with the additive problem of deviating components of different dimensions.On the premise of completing each target set in the site,the planning were transformed into a linear programming to obtain more direct and scientific decision makers' satisfaction.The detailed city electric car charging station site selection steps were described,which was mainly divided into two parts: 1)Using the Delphi method of charging station address preliminary to determine the candidate station.2)Using the built site optimization model to select the best address from the candidate station by comparing the final objective function value.The proposed site selection method and location model were validated by examples.Taking the planning of a charging station in an urban area of Baoding as an example,6 candidate station addresses were selected from 20 candidate addresses to calculate the satisfaction of decision makers at each candidate station,and thus the specific location of 3 charging stations to be built.The example results showed the effectiveness of the site selection method and site selection model.
Keywords/Search Tags:The Electric vehicle, Charging station location, Utility function of decision maker, Multi-objective programming model
PDF Full Text Request
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