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Scheduling of EV Battery Swapping, I: Centralized Solution

You, Pengcheng and Low, Steven H. and Tushar, Wayes and Geng, Guangchao and Yuen, Chau and Yang, Zaiyue and Sun, Youxian (2018) Scheduling of EV Battery Swapping, I: Centralized Solution. IEEE Transactions on Control of Network Systems, 5 (4). pp. 1887-1897. ISSN 2325-5870. https://resolver.caltech.edu/CaltechAUTHORS:20171221-154244882

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Abstract

We formulate an optimal scheduling problem for battery swapping that assigns to each electric vehicle (EV) a best battery station to swap its depleted battery based on its current location and state of charge. The schedule aims to minimize a weighted sum of EVs’ travel distance and electricity generation cost over both station assignments and power flow variables, subject to EV range constraints, grid operational constraints, and ac power flow equations. To deal with the nonconvexity of power flow equations and the binary nature of station assignments, we propose a solution based on second-order cone programming (SOCP) relaxation of optimal power flow and generalized Benders decomposition. When the SOCP relaxation is exact, this approach computes a global optimum. We evaluate the performance of the proposed algorithm through simulations. The algorithm requires global information and is suitable for cases where the distribution grid, battery stations, and EVs are managed centrally by the same operator. In Part II of this paper, we develop distributed solutions for cases where they are operated by different organizations that do not share private information.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/TCNS.2017.2773025DOIArticle
https://arxiv.org/abs/1611.07943arXivDiscussion Paper
ORCID:
AuthorORCID
You, Pengcheng0000-0003-1532-8773
Low, Steven H.0000-0001-6476-3048
Tushar, Wayes0000-0003-1055-7200
Geng, Guangchao0000-0002-3626-0766
Yuen, Chau0000-0002-9307-2120
Yang, Zaiyue0000-0002-8288-3833
Additional Information:© 2017 IEEE. Manuscript received June 25, 2017; revised September 21, 2017; accepted October 26, 2017. Date of publication November 13, 2017; date of current version December 14, 2018. This work was supported in part by the Zhejiang Provincial Natural Science Foundation of China under Grant LR16F030002; in part by NSF under Grant CCF 1637598, Grant ECCS 1619352, and Grant CNS 1545096; in part by the ARPA-E under Grant DE-AR0000699 and the GRID DATA program; in part by the DTRA under Grant HDTRA 1-15-1-0003; in part by the Advance Queensland Research Fellowship AQRF11016-17RD2, which is jointly sponsored by the State of Queensland through the Department of Science, Information Technology and Innovation, the University of Queensland and Redback Technologies; in part by the NSFC under Grant 61750110529; and in part by the SUTD-MIT International Design Center.
Funders:
Funding AgencyGrant Number
Zhejiang Provincial Natural Science Foundation of ChinaLR16F030002
NSFCCF-1637598
NSFECCS-1619352
NSFCNS-1545096
Advanced Research Projects Agency-Energy (ARPA-E)DE-AR0000699
Defense Threat Reduction Agency (DTRA)HDTRA 1-15-1-0003
Advance Queensland Research FellowshipAQRF11016-17RD2
State of QueenslandUNSPECIFIED
University of QueenslandUNSPECIFIED
Redback TechnologiesUNSPECIFIED
National Science Foundation of China61750110529
SUTD-MIT International Design CentreUNSPECIFIED
Subject Keywords:Battery swapping, convex relaxation, Dist-Flow equations, electric vehicle (EV), generalized Benders decomposition
Issue or Number:4
Record Number:CaltechAUTHORS:20171221-154244882
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20171221-154244882
Official Citation:P. You et al., "Scheduling of EV Battery Swapping—Part I: Centralized Solution," in IEEE Transactions on Control of Network Systems, vol. 5, no. 4, pp. 1887-1897, Dec. 2018. doi: 10.1109/TCNS.2017.2773025
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:84009
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:21 Dec 2017 23:51
Last Modified:03 Oct 2019 19:13

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