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Smoothed Least-Laxity-First Algorithm for Electric Vehicle Charging: Online Decision and Performance Analysis with Resource Augmentation

Chen, Niangjun and Kurniawan, Christian and Nakahira, Yorie and Chen, Lijun and Low, Steven H. (2022) Smoothed Least-Laxity-First Algorithm for Electric Vehicle Charging: Online Decision and Performance Analysis with Resource Augmentation. IEEE Transactions on Smart Grid, 13 (3). pp. 2209-2217. ISSN 1949-3053. doi:10.1109/tsg.2021.3138615. https://resolver.caltech.edu/CaltechAUTHORS:20220127-230706500

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Abstract

Adaptive charging can charge electric vehicles (EVs) at scale cost effectively, despite of the uncertainty in EV arrivals. We formulate adaptive EV charging as a feasibility problem that meets all EVs’ energy demands before their deadlines while satisfying constraints in charging rate and total charging power. We propose an online algorithm, smoothed least-laxity-first (sLLF), that decides the current charging rates without the knowledge of future arrivals and demands. We characterize the performance of the sLLF algorithm analytically and numerically. Numerical experiments with real-world data show that it has a significantly higher rate of feasible EV charging than several other existing EV charging algorithms. Resource augmentation framework is employed to assess the feasibility condition of the algorithm. The assessment shows that the sLLF algorithm achieves perfect feasibility with only a 7% increase in the maximal power supply of the charging station.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/tsg.2021.3138615DOIArticle
ORCID:
AuthorORCID
Chen, Niangjun0000-0002-2289-9737
Kurniawan, Christian0000-0002-3178-4042
Nakahira, Yorie0000-0003-3324-4602
Chen, Lijun0000-0001-6694-4299
Low, Steven H.0000-0001-6476-3048
Additional Information:© 2021 IEEE. Manuscript received February 23, 2021; revised June 19, 2021 and December 17, 2021; accepted December 20, 2021. Date of publication December 27, 2021; date of current version April 22, 2022. Paper no. TSG-00305-2021. The materials presented here is based upon work supported by the Electrical, Communication and Cyber Systems (ECCS) Divison of the National Science Foundation (NSF) Cyber Physical Systems (CPS) award number 1932611.
Funders:
Funding AgencyGrant Number
NSFECCS-1932611
Subject Keywords:Power generation scheduling, scheduling, road vehicle power systems, resource management, battery chargers
Issue or Number:3
DOI:10.1109/tsg.2021.3138615
Record Number:CaltechAUTHORS:20220127-230706500
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220127-230706500
Official Citation:N. Chen, C. Kurniawan, Y. Nakahira, L. Chen and S. H. Low, "Smoothed Least-Laxity-First Algorithm for Electric Vehicle Charging: Online Decision and Performance Analysis With Resource Augmentation," in IEEE Transactions on Smart Grid, vol. 13, no. 3, pp. 2209-2217, May 2022, doi: 10.1109/TSG.2021.3138615
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:113136
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:28 Jan 2022 18:06
Last Modified:26 Apr 2022 17:39

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