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

Thomas, Huw; Sun, Hongjian; Kazemtabrizi, Behzad

doi:10.1049/stg2.12016

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

Thomas, Huw; Sun, Hongjian; Kazemtabrizi, Behzad

Authors

Huw Thomas huw.thomas@durham.ac.uk
PGR Student Doctor of Philosophy

Professor Hongjian Sun hongjian.sun@durham.ac.uk
Professor

Dr Behzad Kazemtabrizi behzad.kazemtabrizi@durham.ac.uk
Associate Professor

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

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© 2021 The Authors. IET Smart Grid published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

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