Please use this identifier to cite or link to this item: https://knowledgecommons.lakeheadu.ca/handle/2453/5169
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dc.contributor.advisorYassine, Abdulsalam-
dc.contributor.advisorBenlamri, Rachid-
dc.contributor.authorMoniruzzaman, Md.-
dc.date.accessioned2023-06-07T15:20:15Z-
dc.date.available2023-06-07T15:20:15Z-
dc.date.created2023-
dc.date.issued2023-
dc.identifier.urihttps://knowledgecommons.lakeheadu.ca/handle/2453/5169-
dc.description.abstractPeer-to-peer (P2P) energy trading allows smart grid-connected parties to trade renewable energy with each other. It is widely considered a scheme to mitigate the supplydemand imbalances during peak-hour. In a P2P energy trading system, users (e.g., prosumers, Electric Vehicles (EV)) increase their utility by trading energy securely with each other at a lower price than that of the main grid. However, three challenges hinder the development of secured P2P energy trading systems. First, there is a lack of implicit trust and transparency between trading participants because they do not know each other. Second, P2P energy trading systems cannot offer an intelligent trading strategy that could maximize users’ (agents’) utility. This is because the agents may lack previous trading experience data that enable them to select an optimal trading strategy. Third, the current energy trading platforms are mainly centralized, which makes them vulnerable to malicious attacks and Single point of failure (SPOF). This may interrupt the transaction validation mechanism when the system is compromised, and the central database is unavailable. [...]en_US
dc.language.isoen_USen_US
dc.subjectPeer-to-peer (P2P) energy tradingen_US
dc.subjectBlockchain technologyen_US
dc.subjectArtificial intelligence (AI) in energy tradingen_US
dc.subjectCoalition formation mechanismen_US
dc.titleBlockchain and artificial intelligence enabled peer-to-peer energy trading in smart gridsen_US
dc.typeThesisen_US
etd.degree.nameDoctor of Philosophyen_US
etd.degree.levelDoctoralen_US
etd.degree.disciplineEngineering : Electrical & Computeren_US
etd.degree.grantorLakehead Universityen_US
Appears in Collections:Electronic Theses and Dissertations from 2009

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