Decentralized Peer-to-Peer Electricity Trading Simulation Dashboard

dc.citation.epage6
dc.citation.spage1
dc.contributor.authorAsrani Lit
dc.contributor.authorNazreen Junaidi
dc.contributor.authorShirley Rufus
dc.contributor.authorYanuar Zulardiansyah Arief
dc.contributor.authorSharifah Masniah Wan Masra
dc.contributor.authorMohd Zamri Che Wanik
dc.contributor.departmentFaculty of Engineering
dc.coverage.spatialBoracay Island-Philippines
dc.coverage.temporal2026-04
dc.date.accessioned2026-06-10T03:38:42Z
dc.date.issued2026-07-05
dc.description.abstractPeer-to-Peer (P2P) electricity trading has emerged as a key enabler for decentralized energy systems, allowing prosumers with distributed energy resources such as solar photovoltaic (PV) systems and electric vehicles (EVs) to buy and sell electricity directly. This paper presents a lightweight, interactive simulation dashboard for P2P electricity trading, developed using the Streamlit framework. The system models energy generation, demand patterns, dynamic pricing, and matching algorithms to emulate a residential P2P microgrid. Prosumers and consumers are represented with distinct profiles including solar homes, EV homes, hybrid solar-EV homes, and traditional consumers allowing visualization of energy flows and market activity. The dashboard provides real-time charts, automated trading logs, and a simplified market-clearing mechanism, making it suitable for teaching, prototyping, and community microgrid feasibility studies. Results demonstrate the capability of the simulation to model heterogeneous household interactions and visualize trade behavior across daily cycles. This tool offers a foundation for further work incorporating battery storage, blockchain smart contracts, and real-world sensor data.
dc.description.presentationtypePaper
dc.description.referencesUncontrolled Keywords: Peer-to-Peer Energy Trading, Microgrid, Distributed Energy Resources, Renewable Energy, Electric Vehicle.
dc.description.sponsorshipIEEE
dc.description.statusPublished
dc.identifier.citationAsrani, L., Nazreen, J., Rufus, S., Zulardiansyah, A. Y., Wan Masra, S. M., & Che Wanik, M. Z. (2026). Decentralized peer-to-peer electricity trading simulation dashboard. In Proceedings of the International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA) 2026 (Boracay Island, Philippines, February 5–7, 2026). https://doi.org/10.1109/ACDSA67686.2026.11467723
dc.identifier.emaillasrani@unimas.my
dc.identifier.emailjnazreen@unimas.my
dc.identifier.emailrshirley@unimas.my
dc.identifier.emailayzulardiansyah@unimas.my
dc.identifier.uriDOI: 10.1109/ACDSA67686.2026.11467723
dc.identifier.urihttps://scholarhub.unimas.my/handle/123456789/828
dc.relation.conferenceInternational Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA) 2026
dc.titleDecentralized Peer-to-Peer Electricity Trading Simulation Dashboard
dc.type.eventConference
dc.type.statusYes

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