Optimal Transactive Energy Trading of Electric Vehicle Charging Stations With On-Site PV Generation in Constrained Power Distribution Networks

Affolabi, Larissa; Shahidehpour, Mohammad; Gan, Wei; Yan, Mingyu; Chen, Bo; Pandey, Shikhar; Vukojevic, Aleksandar; Paaso, Esa Aleksi; Alabdulwahab, Ahmed; Abusorrah, Abdullah

doi:10.1109/tsg.2021.3131959

Title: Optimal Transactive Energy Trading of Electric Vehicle Charging Stations With On-Site PV Generation in Constrained Power Distribution Networks

Journal Article · Wed Dec 01 00:00:00 EST 2021 · IEEE Transactions on Smart Grid

DOI:https://doi.org/10.1109/tsg.2021.3131959· OSTI ID:1879205

^[1];

^[2];

^[3]; Yan, Mingyu ^[1];

^[4]; Pandey, Shikhar ^[5]; Vukojevic, Aleksandar ^[5]; Paaso, Esa Aleksi ^[5];

^[6];

^[6]

Illinois Institute of Technology, Chicago, IL (United States)
Illinois Institute of Technology, Chicago, IL (United States); King Abdulaziz Univ., Jeddah (Saudi Arabia)
Huazhong Univ. of Science and Technology, Wuhan (China)
Argonne National Lab. (ANL), Lemont, IL (United States)
Commonwealth Edison Company, Oakbrook Terrace, IL (United States)
King Abdulaziz Univ., Jeddah (Saudi Arabia)

This paper presents a two-level transactive energy market framework, that enables energy trading among electric vehicle charging stations (EVCSs). At the lower level, the discharging capability of EVs and on-site PV generation are leveraged by individual EVCS for participating in the transactive trading with their peers. Once the lower-level trading is completed, EVCSs trade energy at the upper level through the power grid network managed by the distribution system operator (DSO). The upper-level market is cleared while satisfying the power distribution network constraints. A cooperative game-based model is proposed to model the energy trading among EVCSs. To this end, the asymmetric Nash bargaining method is applied to allocate the grand coalition's payoff to each EVCS at the upper-level market, while a weighted proportional allocation method is used to allocate individual EVCS's payoff to its respective EVs at the lower-level market. In this work, the upper-level market formulation is further decomposed into two subproblems representing an energy scheduling and trading subproblem which maximizes EVCS payoffs, and a bargaining subproblem which allocates EVCS payoffs. The effectiveness of the proposed framework for incentivizing transactive trades among EVs and EVCSs is validated in case studies.

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Research Organization:: Argonne National Lab. (ANL), Argonne, IL (United States)

Sponsoring Organization:: King Abdulaziz University. Deanship of Scientific Research (DSR); USDOE

Grant/Contract Number:: AC02-06CH11357; RG-10-135-40

OSTI ID:: 1879205

Report Number(s):: TSG-00379-2021; 177016

Journal Information:: IEEE Transactions on Smart Grid, Vol. 13, Issue 2; ISSN 1949-3053

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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