Tran, CQ, Ngoduy, D, Keyvan-Ekbatani, M et al. (1 more author) (2020) Bi-level optimization for locating fast-charging stations in large-scale urban networks. In: 2020 Forum on Integrated and Sustainable Transportation Systems (FISTS). 2020 Forum on Integrated and Sustainable Transportation Systems (FISTS), 03-05 Nov 2020, Delft, Netherlands. IEEE , pp. 205-210. ISBN 978-1-7281-9503-2
Abstract
Although the electrification of transportation can bring long-term sustainability, increasing penetration of Electric Vehicles (EVs) may cause more congestion. Inappropriate deployment of charging stations not only hinders the EVs adoption but also increases the total system costs. This paper attempts to identify the optimal locations for fast-charging stations in the urban network considering heterogeneous vehicles with respect to the traffic congestion at different levels of EVs’ penetration. A bi-level optimization framework is proposed to solve this problem in which the upper level aims to locate charging stations by minimizing the total travel time and the infrastructure costs. On the other hand, the lower level captures re-routing behaviours of travellers with their driving ranges. Finally, numerical study is performed to demonstrate the fast convergence of the proposed framework.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Spatial Modelling and Dynamics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Jun 2022 11:28 |
Last Modified: | 30 Jun 2022 11:28 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/fists46898.2020.9264894 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:188288 |