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Research On Charging Facility Planning Of Urban Electric Vehicle

Posted on:2020-11-22Degree:MasterType:Thesis
Country:ChinaCandidate:P SuFull Text:PDF
GTID:2392330602956738Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
Electric vehicle is an important part of realizing low-carbon economy,environmental protection and building a strong smart grid in China in the 21st century.In order to adapt to the rapid development of electric vehicle industry,it is urgent to build an electric vehicle charging station as a supplementary energy facility for electric vehicle.The research on the optimal planning of electric vehicle charging station has become a domestic and international issue.Hotspots of concern.With the large number of distributed generations connected,the optimization of charging stations for electric vehicles is not only a single index such as user cost,power company cost and network loss,but also a space index such as distributed generation absorption and layout of roads and distribution networks.Therefore,the planning of electric vehicle charging station is gradually becoming the focus of attention and research by scholars at home and abroad.In order to meet the requirements of the overall planning of urban electric vehicle development and power grid planning,many factors should be taken into account in the construction planning of charging stations for electric vehicles.The charging allocation and demand characteristics of users should be taken into account in order to meet all the needs of users and realize the convenience of user services;and the structure and later operation of charging stations should be considered.This will enable the construction,operation and charging users of charging stations to do so.From the perspective of urban charging station planning,the constraints of urban traffic network layout should also be fully considered.In view of the various factors that need to be considered in the charging station of the electric vehicle,this paper introduces in detail the development status of the charging pile of the electric vehicle at home and abroad,and mainly expounds the development trend and policy situation of the charging pile of the electric vehicle in China.In addition,according to the characteristics of different types of charging stations,the influencing factors of different types of charging stations planning optimization are summarized,which provides a good idea for the planning and location of electric vehicle charging stations.Based on BASS model,the demand forecasting of various products has good effect,starting from the essence of electric vehicle charging,this paper establishes BASS model to forecast the total amount of electric vehicle in the next few years,and calculates the scale of charging station.In addition,the queuing model is used to optimize the location of the charging station,and the exhaustion method with minimum cost as the objective function is used to solve this problem.At the same time,it can optimize the distribution of charging stations and make them more balanced.Therefore,the model is helpful for the government to plan the future development of electric vehicles.In addition,considering that distributed generation and electric vehicles are often connected to the distribution network at the same time,a multi-objective optimization problem is proposed.Under the conditions of road and grid,the fuel cell and distributed generation system are realized under the constraints of the number of electric vehicles and the number of possible electric vehicles in all regions.Distributed Generations(DG)are configured and scaled simultaneously.This problem is defined as Mixed Integer Non-Linear Problems(MINLP)to optimize the user loss,network power consumption,future development costs and improve the voltage distribution of distribution system.Non-dominated Sorting Genetic Algorithms-II(NSGA-II)is used to solve MINLP.Finally,Laiwu electric vehicle charging station planning is used as an example to verify the accuracy of the proposed method.
Keywords/Search Tags:Electric Vehicle, Charging Station Planning, Distributed Generation, Non-dominated Sorting Genetic Algorithms
PDF Full Text Request
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