Xu, YimingZhang, LuOzkan, NazmiyeLong, Chao2024-06-122024-06-122024-05-01Xu 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. 84-88979-8-3503-0947-82836-3698https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics60724.2023.00038https://dspace.lib.cranfield.ac.uk/handle/1826/22494The 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.en-UKAttribution-NonCommercial 4.0 InternationalV2V energy tradingelectric vehicledouble auctionk-factorConference paper979-8-3503-0946-12836-3701