Decentralized Peer-to-Peer Electricity Trading Simulation Dashboard
| dc.citation.epage | 6 | |
| dc.citation.spage | 1 | |
| dc.contributor.author | Asrani Lit | |
| dc.contributor.author | Nazreen Junaidi | |
| dc.contributor.author | Shirley Rufus | |
| dc.contributor.author | Yanuar Zulardiansyah Arief | |
| dc.contributor.author | Sharifah Masniah Wan Masra | |
| dc.contributor.author | Mohd Zamri Che Wanik | |
| dc.contributor.department | Faculty of Engineering | |
| dc.coverage.spatial | Boracay Island-Philippines | |
| dc.coverage.temporal | 2026-04 | |
| dc.date.accessioned | 2026-06-10T03:38:42Z | |
| dc.date.issued | 2026-07-05 | |
| dc.description.abstract | Peer-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.presentationtype | Paper | |
| dc.description.references | Uncontrolled Keywords: Peer-to-Peer Energy Trading, Microgrid, Distributed Energy Resources, Renewable Energy, Electric Vehicle. | |
| dc.description.sponsorship | IEEE | |
| dc.description.status | Published | |
| dc.identifier.citation | Asrani, 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.email | lasrani@unimas.my | |
| dc.identifier.email | jnazreen@unimas.my | |
| dc.identifier.email | rshirley@unimas.my | |
| dc.identifier.email | ayzulardiansyah@unimas.my | |
| dc.identifier.uri | DOI: 10.1109/ACDSA67686.2026.11467723 | |
| dc.identifier.uri | https://scholarhub.unimas.my/handle/123456789/828 | |
| dc.relation.conference | International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA) 2026 | |
| dc.title | Decentralized Peer-to-Peer Electricity Trading Simulation Dashboard | |
| dc.type.event | Conference | |
| dc.type.status | Yes |
