Abstract
The rising demand for electric vehicles (EVs), motivated by their environmental benefits, is generating an increased need for EV charging infrastructure. Also, it has been recognized that the adequacy of such infrastructure helps promote EV use. Therefore, to facilitate EV adoption, governments seek guidance on continued investments in EV charging infrastructure development. Such investment decisions, which include EV charging station locations and capacities, and the timing of such investments require robust estimates of future travel demand and EV battery range constraints. This paper develops and implements a framework to establish an optimal schedule and locations for new charging stations and decommissioning gasoline refueling stations over a long-term planning horizon, considering the uncertainty in future travel demand forecasts and the driving range heterogeneity of EVs. A robust mathematical model is proposed to solve the problem by minimizing not only the worst-case total system travel cost but also the total penalty for unused capacities of charging stations. This study uses an adaptation of the cutting-plane method to solve the proposed model. Based on two key decision criteria (travelers’ cost and charging supply sufficiency), the results indicate that the robust scheme outperforms its deterministic counterpart.
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Data Availability Statement
All data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by Purdue University’s Center for Connected and Automated Transportation (CCAT), a part of the larger CCAT consortium that is a USDOT Region 5 University Transportation Center funded by the US Department of Transportation, Award #69A3551747105. The paper is also a part of the Center for Innovation in Control, Optimization, and Networks (ICON), and the Autonomous and Connected Systems (ACS) initiatives at Purdue University’s College of Engineering. The contents of this paper reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented herein, and do not necessarily reflect the official views or policies of the sponsoring organization.
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Information
Published In
Journal of Infrastructure Systems
Volume 29 • Issue 2 • June 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Apr 29, 2022
Accepted: Jan 1, 2023
Published online: Mar 29, 2023
Published in print: Jun 1, 2023
Discussion open until: Aug 29, 2023
ASCE Technical Topics:
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- Continuum mechanics
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