Closest Energy Matching: Improving peer‐to‐peer energy trading auctions for EV owners. Issue 4 (11th March 2021)

• Record Type: Journal Article
• Authors: Thomas, Huw; Sun, Hongjian; Kazemtabrizi, Behzad
• Is Part Of: IET smart grid. Volume 4:Issue 4(2021)
• Page Start: 445
• Page End: 460
• Publication Date: 2021-03-11
• Subjects: Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/stg2.12016
• Languages: English
• ISSNs: 2515-2947

Abstract

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.