An anti-fraud double auction model in vehicle-to-vehicle energy trading with the k-factor approach

Date

2024-05-01

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

IEEE

Department

Type

Conference paper

ISSN

2836-3698

Format

Citation

Xu Y, Zhang L, Ozkan N, Long C. (2023) An anti-fraud double auction model in vehicle-to-vehicle energy trading with the k-factor approach. In: 2023 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics), 17-21 December 2023, Danzhou, China, pp. 84-88

Abstract

The rise in electric vehicle adoption has reduced greenhouse gas emissions in transportation but overloads the power grid due to charging demands. This paper introduces a Double Auction (DA) model in Vehicle-to-Vehicle (V2V) energy trading with the K-factor approach. The novel approach defines unique market clearing prices for each successfully matched V2V transaction pairs, robustly counteracts potential economic fraud. It overcomes shortcoming of some other models of sacrificing participants who could have conducted V2V transactions in order to prevent economic fraud. Meanwhile, the model ensures transactional economic benefits, transparency and fairness. This work facilitates EV adoption across the UK and globally, by increasing confidence and convenience in energy trading mechanisms.

Description

Software Description

Software Language

Github

Keywords

V2V energy trading, electric vehicle, double auction, k-factor

DOI

Rights

Attribution-NonCommercial 4.0 International

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