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Classification of electric vehicle charging time series with selective clustering

Sun, Chenxi and Li, Tongxin and Low, Steven H. and Li, Victor O. K. (2020) Classification of electric vehicle charging time series with selective clustering. Electric Power Systems Research, 189 . Art. No. 106695. ISSN 0378-7796. doi:10.1016/j.epsr.2020.106695.

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We develop a novel iterative clustering method for classifying time series of EV charging rates based on their “tail features”. Our method first extracts tails from a diversity of charging time series that have different lengths, contain missing data, and are distorted by scheduling algorithms and measurement noise. The charging tails are then clustered into a small number of types whose representatives are then used to improve tail extraction. This process iterates until it converges. We apply our method to ACN-Data, a fine-grained EV charging dataset recently made publicly available, to illustrate its effectiveness and potential applications.

Item Type:Article
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Li, Tongxin0000-0002-9806-8964
Low, Steven H.0000-0001-6476-3048
Additional Information:© 2020 Elsevier. Received 5 October 2019, Revised 24 February 2020, Accepted 1 August 2020, Available online 8 August 2020. Submitted to the 21st Power Systems Computation Conference (PSCC 2020). The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Subject Keywords:Time series clustering; EV charging curves
Record Number:CaltechAUTHORS:20210112-144610886
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Official Citation:Chenxi Sun, Tongxin Li, Steven H. Low, Victor O.K. Li, Classification of electric vehicle charging time series with selective clustering, Electric Power Systems Research, Volume 189, 2020, 106695, ISSN 0378-7796,
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107442
Deposited By: George Porter
Deposited On:13 Jan 2021 15:22
Last Modified:16 Nov 2021 19:03

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