INTELTRADE: Intelligent Peer-to-Peer Energy Trading System With Dynamic Pricing and Coalition Formation
The decentralization of energy generation and consumption has become increasingly vital, with peer-to-peer (P2P) energy trading promoting resilience, and sustainability. This paper introduces INTELTRADE, a system addressing the energy sustainability and pricing challenges in P2P trading. INTELTRADE...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10843710/ |
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| author | Nicholas Kemp Md Sadman Siraj Eirini Eleni Tsiropoulou Symeon Papavassiliou |
| author_facet | Nicholas Kemp Md Sadman Siraj Eirini Eleni Tsiropoulou Symeon Papavassiliou |
| author_sort | Nicholas Kemp |
| collection | DOAJ |
| description | The decentralization of energy generation and consumption has become increasingly vital, with peer-to-peer (P2P) energy trading promoting resilience, and sustainability. This paper introduces INTELTRADE, a system addressing the energy sustainability and pricing challenges in P2P trading. INTELTRADE integrates a sophisticated coalition formation mechanism and an optimal pricing policy. Initially, the Approximate INTELTRADE (AINTELTRADE) mechanism uses matching theory to quickly determine the initial buyer-seller matches by ignoring prosumers’ externalities. This output feeds the Accurate INTELTRADE (AccINTELTRADE) mechanism, which refines the coalition formation using game theory while considering the prosumers’ externalities. Additionally, a non-cooperative game among energy-selling prosumers is formulated, deriving a unique Nash Equilibrium to maximize the sellers’ profits. INTELTRADE’s efficacy and scalability are validated through simulations with real-world data. A detailed comparative evaluation demonstrates INTELTRADE’s superiority in meeting the buyers’ energy demands and optimizing the sellers’ profits. |
| format | Article |
| id | doaj-art-7aba9c00d92a44f593e53587895d2f67 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-7aba9c00d92a44f593e53587895d2f672025-01-25T00:02:37ZengIEEEIEEE Access2169-35362025-01-0113124581246710.1109/ACCESS.2025.353042810843710INTELTRADE: Intelligent Peer-to-Peer Energy Trading System With Dynamic Pricing and Coalition FormationNicholas Kemp0Md Sadman Siraj1https://orcid.org/0000-0002-1391-5774Eirini Eleni Tsiropoulou2https://orcid.org/0000-0003-1322-1876Symeon Papavassiliou3https://orcid.org/0000-0002-9459-318XDepartment of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USAPerformance and Resource Optimization in Networks-PROTON Laboratory, School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USAPerformance and Resource Optimization in Networks-PROTON Laboratory, School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA3School of Electrical and Computer Engineering, National Technical University of Athens, Athens, GreeceThe decentralization of energy generation and consumption has become increasingly vital, with peer-to-peer (P2P) energy trading promoting resilience, and sustainability. This paper introduces INTELTRADE, a system addressing the energy sustainability and pricing challenges in P2P trading. INTELTRADE integrates a sophisticated coalition formation mechanism and an optimal pricing policy. Initially, the Approximate INTELTRADE (AINTELTRADE) mechanism uses matching theory to quickly determine the initial buyer-seller matches by ignoring prosumers’ externalities. This output feeds the Accurate INTELTRADE (AccINTELTRADE) mechanism, which refines the coalition formation using game theory while considering the prosumers’ externalities. Additionally, a non-cooperative game among energy-selling prosumers is formulated, deriving a unique Nash Equilibrium to maximize the sellers’ profits. INTELTRADE’s efficacy and scalability are validated through simulations with real-world data. A detailed comparative evaluation demonstrates INTELTRADE’s superiority in meeting the buyers’ energy demands and optimizing the sellers’ profits.https://ieeexplore.ieee.org/document/10843710/Peer-to-peer energy trading systemmatching theorycoalition gamespricinggame theory |
| spellingShingle | Nicholas Kemp Md Sadman Siraj Eirini Eleni Tsiropoulou Symeon Papavassiliou INTELTRADE: Intelligent Peer-to-Peer Energy Trading System With Dynamic Pricing and Coalition Formation IEEE Access Peer-to-peer energy trading system matching theory coalition games pricing game theory |
| title | INTELTRADE: Intelligent Peer-to-Peer Energy Trading System With Dynamic Pricing and Coalition Formation |
| title_full | INTELTRADE: Intelligent Peer-to-Peer Energy Trading System With Dynamic Pricing and Coalition Formation |
| title_fullStr | INTELTRADE: Intelligent Peer-to-Peer Energy Trading System With Dynamic Pricing and Coalition Formation |
| title_full_unstemmed | INTELTRADE: Intelligent Peer-to-Peer Energy Trading System With Dynamic Pricing and Coalition Formation |
| title_short | INTELTRADE: Intelligent Peer-to-Peer Energy Trading System With Dynamic Pricing and Coalition Formation |
| title_sort | inteltrade intelligent peer to peer energy trading system with dynamic pricing and coalition formation |
| topic | Peer-to-peer energy trading system matching theory coalition games pricing game theory |
| url | https://ieeexplore.ieee.org/document/10843710/ |
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