Online Menu-Based Scheduling of Electric Vehicle Charging

This paper addresses the problem of efficiently scheduling of EV charging requests in a single Charging Station (CS), also taking into consideration the inability of EV users to express their preferences in closed-form utility functions. We consider a paradigm where a menu of possible charging intervals, each associated with an urgency price, is generated online. By letting the EV users pick their most preferable menu option, the proposed algorithm commits on each EV’s charging completion time upon its arrival, achieves a near optimal total weighted charging completion time, and prevents the users from strategically misreporting their preferences, while offering a practical and implementable solution to the problem of EVs - charging station interaction. Our experimental evaluation demonstrates that our algorithmic approach performs nearly optimal in a variety of practically relevant scenarios.

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Publication Details

Journal
IEEE Transactions on Smart Grid
Published
2025-02-07
DOI
https://doi.org/10.1109/tsg.2025.3539962
Citations
2
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
1.46

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article

Online Menu-Based Scheduling of Electric Vehicle Charging

Γεώργιος Τσαούσογλου, Dimitris Fotakis, Emmanouel Varvarigos, Angeliki Mathioudaki
2 citations
IEEE Transactions on Smart Grid
Electric Vehicles and Infrastructure
1.46
article

Online Menu-Based Scheduling of Electric Vehicle Charging

Γεώργιος Τσαούσογλου, Dimitris Fotakis, Emmanouel Varvarigos, Angeliki Mathioudaki
article en
2 citations

Abstract

This paper addresses the problem of efficiently scheduling of EV charging requests in a single Charging Station (CS), also taking into consideration the inability of EV users to express their preferences in closed-form utility functions. We consider a paradigm where a menu of possible charging intervals, each associated with an urgency price, is generated online. By letting the EV users pick their most preferable menu option, the proposed algorithm commits on each EV’s charging completion time upon its arrival, achieves a near optimal total weighted charging completion time, and prevents the users from strategically misreporting their preferences, while offering a practical and implementable solution to the problem of EVs - charging station interaction. Our experimental evaluation demonstrates that our algorithmic approach performs nearly optimal in a variety of practically relevant scenarios.

IEEE Transactions on Smart GridVol. 16(3)
National Technical University of Athens (GR), Technical University of Denmark (DK)
National Technical University of Athens
Openalex Percentile: Top 20%
Electric Vehicles and Infrastructure
1.46
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Online Menu-Based Scheduling of Electric Vehicle Charging — Γεώργιος Τσαούσογλου, Dimitris Fotakis, et al. · IEEE Transactions on Smart Grid (2025) | TGRS Research Map | TGRS