Charging Station Location Problem of Battery Electric Vehicles
This thesis is primarily focused on solving charging station location problem, and it is mainly conducted using p-Median based models. The differences, advantages and disadvantages of variations of p-Median model is investigated, and suggestions are made for further research. The primary motivation...
| Main Author: | |
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2019
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| Online Access: | https://eprints.nottingham.ac.uk/58374/ |
| _version_ | 1848799540894760960 |
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| author | Yu, Yanchi |
| author_facet | Yu, Yanchi |
| author_sort | Yu, Yanchi |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This thesis is primarily focused on solving charging station location problem, and it is mainly conducted using p-Median based models. The differences, advantages and disadvantages of variations of p-Median model is investigated, and suggestions are made for further research. The primary motivation for this research is the increasing environmental concerns as well as the increasing adoption of electric vehicles. This paper starts with a literature review of the basics of EV charging stations and what have been done for solving charging station location problems. Then the p-Median model is developed and implemented using Python and Gurobi, and it is proved that meaningful results can be obtained, including charging station locations, network graphs, demand coverage, average distance to charging stations and solution time. The optimal location of charging stations is affected by several factors, such as the population of client nodes, the capacity of charging stations, and the location of candidate charging stations. Another finding is that in a predefined space, the number of charging stations can be saturated, and building more charging stations beyond the saturation point is not effective nor economical. The number and location of candidate charging stations also have an impact on the optimality of the result. The developed program can be easily adaptable to solve any conceptual p-Median based facility problems and real world application is possible with some tweaks. |
| first_indexed | 2025-11-14T20:37:18Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-58374 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:37:18Z |
| publishDate | 2019 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-583742022-12-07T13:11:27Z https://eprints.nottingham.ac.uk/58374/ Charging Station Location Problem of Battery Electric Vehicles Yu, Yanchi This thesis is primarily focused on solving charging station location problem, and it is mainly conducted using p-Median based models. The differences, advantages and disadvantages of variations of p-Median model is investigated, and suggestions are made for further research. The primary motivation for this research is the increasing environmental concerns as well as the increasing adoption of electric vehicles. This paper starts with a literature review of the basics of EV charging stations and what have been done for solving charging station location problems. Then the p-Median model is developed and implemented using Python and Gurobi, and it is proved that meaningful results can be obtained, including charging station locations, network graphs, demand coverage, average distance to charging stations and solution time. The optimal location of charging stations is affected by several factors, such as the population of client nodes, the capacity of charging stations, and the location of candidate charging stations. Another finding is that in a predefined space, the number of charging stations can be saturated, and building more charging stations beyond the saturation point is not effective nor economical. The number and location of candidate charging stations also have an impact on the optimality of the result. The developed program can be easily adaptable to solve any conceptual p-Median based facility problems and real world application is possible with some tweaks. 2019-09 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/58374/1/Yanchi_Yu_4335896_dissertation.pdf Yu, Yanchi (2019) Charging Station Location Problem of Battery Electric Vehicles. [Dissertation (University of Nottingham only)] |
| spellingShingle | Yu, Yanchi Charging Station Location Problem of Battery Electric Vehicles |
| title | Charging Station Location Problem of Battery Electric Vehicles |
| title_full | Charging Station Location Problem of Battery Electric Vehicles |
| title_fullStr | Charging Station Location Problem of Battery Electric Vehicles |
| title_full_unstemmed | Charging Station Location Problem of Battery Electric Vehicles |
| title_short | Charging Station Location Problem of Battery Electric Vehicles |
| title_sort | charging station location problem of battery electric vehicles |
| url | https://eprints.nottingham.ac.uk/58374/ |