AI optimization for peer-to-peer energy sharing: Trends, methods, and future directions

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dc.contributor.authorFilipovich, Daniil
dc.date.accessioned2026-04-16T16:46:13Z
dc.date.available2026-04-16T16:46:13Z
dc.date.issued2026
dc.description.abstractAs clean energy technology advances, Peer-to-peer (P2P) energy sharing has transitioned from a theoretical concept to an emerging real-world solution. A meta-analysis of over 25 academic sources from 2020 to 2025 was performed to track the evolution of P2P modelling. Early models (circa 2020) relied on predefined, fixed variables (such as weather, energy use, and energy storage) within centralized decision-making frameworks. While providing control, these models lacked the flexibility required for volatile real-world conditions. Over the past 5 years, the literature has shifted toward decentralized environments, accounting for changing variables and outcome probabilities. This shift has been accelerated by the growing availability of empirical data from communities that began peer-to-peer adoption, in Europe, the USA, and Australia, among others. According to industry trends, the next phase in this evolution is using real-world data for AI-driven data optimization. By requesting and compiling such data and replacing existing synthetic inputs and heuristic assumptions with empirical data, future models may help bridge the gap between existing theoretical modelling and real-world deployment, enabling real-time optimization of pricing, energy load distribution, and storage management.
dc.description.reviewstatusReviewed
dc.description.scholarlevelUndergraduate
dc.description.sponsorshipJamie Cassels Undergraduate Research Awards (JCURA)
dc.identifier.urihttps://hdl.handle.net/1828/23585
dc.language.isoen
dc.publisherUniversity of Victoria
dc.subjectP2P energy sharing
dc.subjectdecentralized energy management
dc.subjectstochastic optimization
dc.subjectartificial intelligence
dc.subjectempirical data analysis
dc.subjectgrid flexibility
dc.subjectJamie Cassels Undergraduate Research Awards (JCURA)
dc.subject.departmentPeter B. Gustavson School of Business
dc.titleAI optimization for peer-to-peer energy sharing: Trends, methods, and future directions
dc.typePoster

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