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

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dc.contributor.authorXu, Yiming
dc.contributor.authorZhang, Lu
dc.contributor.authorOzkan, Nazmiye
dc.contributor.authorLong, Chao
dc.date.accessioned2024-06-12T14:46:28Z
dc.date.available2024-06-12T14:46:28Z
dc.date.issued2024-05-01
dc.description.abstractThe 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_UK
dc.description.sponsorshipThis work is partly supported by UK Department for Transport (DfT), ‘App for Peer to Peer energy trading with electric vehicles’, and Royal Society Sino-British Fellowship Trust International Exchanges Award (ref IES\R3\203114).en_UK
dc.identifier.citationXu 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. 84-88en_UK
dc.identifier.eisbn979-8-3503-0946-1
dc.identifier.eissn2836-3701
dc.identifier.isbn979-8-3503-0947-8
dc.identifier.issn2836-3698
dc.identifier.urihttps://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics60724.2023.00038
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/22494
dc.language.isoen_UKen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectV2V energy tradingen_UK
dc.subjectelectric vehicleen_UK
dc.subjectdouble auctionen_UK
dc.subjectk-factoren_UK
dc.titleAn anti-fraud double auction model in vehicle-to-vehicle energy trading with the k-factor approachen_UK
dc.typeConference paperen_UK
dcterms.dateAccepted2023-10-31

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