Software-Defined Electric Vehicle (EV)-to-EV Charging Framework With Mobile Aggregator

Haneul Ko; Taeyun Kim; Daeyoung Jung; Sangheon Pack

doi:10.1109/JSYST.2023.3240509

Software-Defined Electric Vehicle (EV)-to-EV Charging Framework With Mobile Aggregator

Haneul Ko, Taeyun Kim, Daeyoung Jung, Sangheon Pack

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

Even though electric vehicle (EV)-to-EV charging has the potential to overcome the inconvenience due to a shortage of electric charging stations, its distributed and dynamic nature makes it difficult to match charging EV (C-EV) and discharging EV (D-EV). In this article, we propose a software-defined EV-to-EV charging framework (SD-E2EC) with mobile aggregators, in which, on the basis of the collected information in a global view, the charging controller determines the charging location, monetary cost for C-EV, and monetary reward for D-EV. To maximize the revenue of the operator of SD-E2EC, we formulate a joint optimization problem of determining the appropriate charging location, monetary cost, and reward. As a practical solution to the problem, we propose a highly acceptable pair decision (HAPD) algorithm. Extensive simulation results demonstrate that HAPD can achieve up to 129% revenue (compared to the conventional method using fixed aggregators) while maintaining the waiting time below a certain level.

Original language	English
Pages (from-to)	2815-2823
Number of pages	9
Journal	IEEE Systems Journal
Volume	17
Issue number	2
DOIs	https://doi.org/10.1109/JSYST.2023.3240509
Publication status	Published - 2023 Jun 1

Bibliographical note

Funding Information:
This work was supported in part by the National Research Foundation (NRF) of Korea funded by the Korean Government (MSIP) under Grant 2020R1A2C3006786 and in part by the MSIT (Ministry of Science and ICT), Korea, within the ITRC (Information Technology Research Center) support program under Grant IITP-2023-RS-2022-00156353 supervised by the IITP (Institute for Information & Communications Technology Planning & Evaluation).

Publisher Copyright:
© 2007-2012 IEEE.

Keywords

Aggregator
EV-to-EV charging
controller
electric vehicle (EV)
software-defined network (SDN)

ASJC Scopus subject areas

Information Systems
Electrical and Electronic Engineering
Control and Systems Engineering
Computer Networks and Communications
Computer Science Applications

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10.1109/JSYST.2023.3240509

Cite this

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abstract = "Even though electric vehicle (EV)-to-EV charging has the potential to overcome the inconvenience due to a shortage of electric charging stations, its distributed and dynamic nature makes it difficult to match charging EV (C-EV) and discharging EV (D-EV). In this article, we propose a software-defined EV-to-EV charging framework (SD-E2EC) with mobile aggregators, in which, on the basis of the collected information in a global view, the charging controller determines the charging location, monetary cost for C-EV, and monetary reward for D-EV. To maximize the revenue of the operator of SD-E2EC, we formulate a joint optimization problem of determining the appropriate charging location, monetary cost, and reward. As a practical solution to the problem, we propose a highly acceptable pair decision (HAPD) algorithm. Extensive simulation results demonstrate that HAPD can achieve up to 129% revenue (compared to the conventional method using fixed aggregators) while maintaining the waiting time below a certain level.",

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Software-Defined Electric Vehicle (EV)-to-EV Charging Framework With Mobile Aggregator

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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