Evaluation and Comparison of Scheduling Strategies for the Scheduling of Electric Vehicles at Capacity-Constrained Charging Stations

Bachelor Thesis (2021)
Author(s)

A. Amouzandeh (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

V. Robu – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)

C. Lofi – Graduation committee member (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2021
Language
English
Graduation Date
01-07-2021
Awarding Institution
Delft University of Technology
Project
CSE3000 Research Project
Programme
Computer Science and Engineering
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

As the popularity of electric vehicles (EVs) increases, congestion at charging becomes a more imminent problem. Congestion at a charging station can lead to long waiting queues and failure of EV owners to charge their vehicles fully before their departure from the station. To combat this issue, this paper explores several candidate scheduling strategies that can be applied for the charging prioritization of EVs at a single station. Through extensive simulations, the efficacy of these strategies is studied under three performance metrics. From the set of strategies studied, we find that earliest deadline first (EDF) and shortest job first (SJF) are the best options in the case that adherence to deadline or a shorter waiting time is most valued, respectively.

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