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

Bachelor thesis (2021)

Authors

A. Amouzandeh Electrical Engineering, Mathematics and Computer Science

Contributors

Valentin Robu Algorithmics - EEMCS (supervisor 1)
C. Lofi Web Information Systems - EEMCS (supervisor 2)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2021 Ashkan Amouzandeh
Electric Vehicles Charging Station Scheduling Algorithms
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Published Date

01-07-2021

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

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.

Files

Research_Paper.pdf
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