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Towards balanced three-phase charging: Phase optimization in adaptive charging networks

Ye, Zixin and Li, Tongxin and Low, Steven (2022) Towards balanced three-phase charging: Phase optimization in adaptive charging networks. Electric Power Systems Research, 212 . Art. No. 108322. ISSN 0378-7796. doi:10.1016/j.epsr.2022.108322.

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We study the problem of phase optimization for electric-vehicle (EV) charging. We formulate our problem as a non-convex mixed-integer programming problem whose objective is to minimize the charging loss. Despite the hardness of directly solving this non-convex problem, we solve a relaxation of the original problem by proposing the PXA algorithm where "P", "X", and "A" stand for three variable matrices in the formed phase optimization problems. We show that under certain conditions, the solution is given by the PXA precisely converges to the global optimum. In addition, using the idea of model predictive control (MPC), we design the PXA-MPC, which is an online implementation of the PXA. Compared to other empirical phase balancing strategies, the PXA algorithm significantly improves the charging performance by maximizing energy delivery, minimizing charging price, and assisting future energy planning. The efficacy of our algorithm is demonstrated using data collected from a real-world adaptive EV charging network (ACN).

Item Type:Article
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URLURL TypeDescription
Ye, Zixin0000-0002-4107-3842
Li, Tongxin0000-0002-9806-8964
Low, Steven0000-0001-6476-3048
Additional Information:The success of this research relies on the solid foundation built by the Netlab team of Caltech and PowerFlex Systems. In particular, a special appreciation should be sent to Zachary Lee, a Netlab researcher who developed the ACN software platform and EV changing data pipeline, without which the experiment stage of this paper could not proceed. At last, this research receives strong support from the NSF fundings, including NSF ECCS-1931662 and NSF CPS: ECCS-1932611.
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Record Number:CaltechAUTHORS:20221010-449776900.1
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:117288
Deposited By: Research Services Depository
Deposited On:14 Oct 2022 22:18
Last Modified:14 Oct 2022 22:18

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