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Smoothed Least-laxity-first Algorithm for EV Charging

Nakahira, Yorie and Chen, Niangjun and Chen, Lijun and Low, Steven H. (2017) Smoothed Least-laxity-first Algorithm for EV Charging. In: e-Energy '17 Proceedings of the Eighth International Conference on Future Energy Systems. ACM , New York, NY, pp. 242-251. ISBN 978-1-4503-5036-5.

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We formulate EV charging as a feasibility problem that meets all EVs' energy demands before departure under charging rate constraints and total power constraint. We propose an online algorithm, the smoothed least-laxity-first (sLLF) algorithm, that decides on the current charging rates based on only the information up to the current time. We characterize the performance of the sLLF algorithm analytically and numerically. Numerical experiments with real-world data show that it has significantly higher rate of generating feasible EV charging than several other common EV charging algorithms.

Item Type:Book Section
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URLURL TypeDescription ItemDiscussion Paper
Nakahira, Yorie0000-0003-3324-4602
Chen, Niangjun0000-0002-2289-9737
Low, Steven H.0000-0001-6476-3048
Additional Information:© 2017 ACM.
Subject Keywords:Online algorithm, online feasibility, resource augmentation, electric vehicle charging
Record Number:CaltechAUTHORS:20170515-140123828
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Official Citation:Yorie Nakahira, Niangjun Chen, Lijun Chen, and Steven H. Low. 2017. Smoothed Least-laxity-first Algorithm for EV Charging. In Proceedings of the Eighth International Conference on Future Energy Systems (e-Energy '17). ACM, New York, NY, USA, 242-251. DOI:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:77462
Deposited On:16 May 2017 22:07
Last Modified:15 Nov 2021 17:31

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