Wang, Y, Zhao, Y, Gan, S et al. (3 more authors) (2023) Optimization of Charging Stations Integrated with Dynamic Transportation Systems in Metropolises. Transportation Research Part D: Transport and Environment, 119. 103726. ISSN 1361-9209
Abstract
The development of electric vehicles (EVs) is expected to play an important role in achieving the emission reduction targets in the transportation sector by many countries and regions, including China’s dual carbon goals. A bottleneck to the mass roll-out of EVs is the limited charging facilities. This paper considers the planning of charging facilities for a new developing area in a metropolis, and an optimization model for charging station planning based on the dynamic transportation system is proposed. The proposed model is developed using an objective framework that considers the spatio-temporal characteristics of EV charging demand in order to minimize the overall cost while the constraints from suppliers and drivers are met. The Voronoi diagram is used to determine the final service boundary of each charging station, and the effect is verified in the planning of charge stations for the Yizhuang new town in Beijing. The case study confirms that the proposed method can optimize the charging facilities that fit well with the traffic network conditions. Furthermore, it is shown that the charging demand varies in accordance with the population density and regional functionality in different areas.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 Elsevier Ltd. This is an author produced version of an article, conference paper published in Transportation Research Part D: Transport and Environment. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Charging station; Optimization; Dynamic traffic system; Metropolis |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Apr 2023 14:01 |
Last Modified: | 25 Apr 2024 00:13 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.trd.2023.103726 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:198461 |