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Research on the optimal planning of the battery switch station for electric vehicles
- Source :
- IET Intelligent Transport Systems. 10:635-641
- Publication Year :
- 2016
- Publisher :
- Institution of Engineering and Technology (IET), 2016.
-
Abstract
- With the rapid development of the global economy, the energy crisis and the deterioration of the ecosystem are becoming more serious. In this context, the development of electric vehicles has received the attention of all countries. Research on charging and changing facilities has a very important significance for the future comprehensive promotion of electric vehicles. In this study, the authors first analyse the advantages and disadvantages of different charging electric network modes. Then, they introduce distribution planning requirements of electric vehicles’ changing stations, and propose an optimisation model meeting various requirements when selecting station sites. This model aims to minimise overall construction and transportation costs, and meet the charging demand of drivers. Changing stations’ service types and operating characteristics of the substation act as constraint conditions. Finally, they solve the model based on the improved graph algorithms. It not only calculates the optimisation location of the changing stations, but also obtains the corresponding optimal substation access scheme. The research of this study can significantly guide planning and construction of electric vehicles’ charging and battery switch stations.
- Subjects :
- Battery (electricity)
Scheme (programming language)
Service (systems architecture)
Engineering
Operations research
business.industry
020209 energy
Mechanical Engineering
Optimal planning
Transportation
Context (language use)
Graph theory
02 engineering and technology
Transport engineering
0202 electrical engineering, electronic engineering, information engineering
business
Law
Constraint (mathematics)
computer
Energy (signal processing)
General Environmental Science
computer.programming_language
Subjects
Details
- ISSN :
- 17519578
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- IET Intelligent Transport Systems
- Accession number :
- edsair.doi...........095ab9e3d4dfb17637ee2d92eeed4baa
- Full Text :
- https://doi.org/10.1049/iet-its.2016.0074