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Research paper | Open Access

Battery electric buses charging schedule optimization considering time-of-use electricity price

Jia He1Na Yan1Jian Zhang1( )Yang Yu2Tao Wang3
Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing, China
Transport for New South Wales, Sydney, Australia
School of Vehicle and Mobility, Tsinghua University, Beijing, China
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Abstract

Purpose

This paper aims to optimize the charging schedule for battery electric buses (BEBs) to minimize the charging cost considering the time-of-use electricity price.

Design/methodology/approach

The BEBs charging schedule optimization problem is formulated as a mixed-integer linear programming model. The objective is to minimize the total charging cost of the BEB fleet. The charge decision of each BEB at the end of each trip is to be determined. Two types of constraints are adopted to ensure that the charging schedule meets the operational requirements of the BEB fleet and that the number of charging piles can meet the demand of the charging schedule.

Findings

This paper conducts numerical cases to validate the effect of the proposed model based on the actual timetable and charging data of a bus line. The results show that the total charge cost with the optimized charging schedule is 15.56% lower than the actual total charge cost under given conditions. The results also suggest that increasing the number of charging piles can reduce the charging cost to some extent, which can provide a reference for planning the number of charging piles.

Originality/value

Considering time-of-use electricity price in the BEBs charging schedule will not only reduce the operation cost of electric transit but also make the best use of electricity resources.

References

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Journal of Intelligent and Connected Vehicles
Pages 138-145

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Cite this article:
He J, Yan N, Zhang J, et al. Battery electric buses charging schedule optimization considering time-of-use electricity price. Journal of Intelligent and Connected Vehicles, 2022, 5(2): 138-145. https://doi.org/10.1108/JICV-03-2022-0006

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Received: 30 March 2022
Revised: 11 April 2022
Accepted: 14 April 2022
Published: 05 May 2022
© 2022 Jia He, Na Yan, Jian Zhang, Yang Yu and Tao Wang. Published in Journal of Intelligent and Connected Vehicles. Published by Emerald Publishing Limited.

This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode