Closest Energy Matching: Improving peer‐to‐peer energy trading auctions for EV owners

Thomas, Huw; Sun, Hongjian; Kazemtabrizi, Behzad

Abstract

Herein, a novel approach to conduct peer-to-peer energy auctions for electric vehicles (EVs) to benefit both buyers and sellers is presented. It considers a scenario where households can sell their surplus solar energy to visiting EVs that make use of the households' vacant charge points during the day. The aim of the energy trading is to maximise the amount of charge EVs receive from the solar energy, and increase the revenue for sellers. The novel Closest Energy Matching (CEM) double auction mechanism is proposed and it is compared with four other mechanisms. CEM allows the auction to take into account current energy requests as well as the potential future demand without requiring additional information. A novel algorithm, MARMES (MAtrix Ranking for Maximising Element Selection), is also presented to solve the optimisation problem that forms the basis of the CEM mechanism. The CEM mechanism on average results in 21.5% more solar energy used, lower cost to the consumer, a 24.9% increase in profits for sellers and a 71.4% reduction in required grid energy compared with the traditional double auction mechanism.

Citation

Thomas, H., Sun, H., & Kazemtabrizi, B. (2021). Closest Energy Matching: Improving peer‐to‐peer energy trading auctions for EV owners. IET Smart Grid, 4(4), 445-460. https://doi.org/10.1049/stg2.12016

• Journal Article Type: Article
• Acceptance Date: Dec 11, 2020
• Online Publication Date: Mar 11, 2021
• Publication Date: 2021-08
• Deposit Date: Mar 11, 2021
• Publicly Available Date: Dec 20, 2021
• Journal: IET Smart Grid
• Print ISSN: 2515-2947
• Electronic ISSN: 2515-2947
• Publisher: Institution of Engineering and Technology (IET)
• Peer Reviewed: Peer Reviewed
• Volume: 4
• Issue: 4
• Pages: 445-460
• DOI: https://doi.org/10.1049/stg2.12016
• Public URL: https://durham-repository.worktribe.com/output/1245608