Scheduling of EV Battery Swapping, I: Centralized Solution

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.

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.

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