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dc.contributor.author | Noorfatima, Nadya | - |
dc.contributor.author | Yoon, Donghyun | - |
dc.contributor.author | Jung, Jaesung | - |
dc.date.issued | 2024-01-01 | - |
dc.identifier.uri | https://aurora.ajou.ac.kr/handle/2018.oak/37140 | - |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85207457596&origin=inward | - |
dc.description.abstract | The actual market clearing price (MCP) of the uniform price-based peer-to-peer (UPP2P) energy trading may differ from its optimal value owing to imperfect competition. Meanwhile, in the UPP2P, MCP is essential to determining optimal social welfare and thus allocating trading capacity among participants. Therefore, this study proposes UPP2P energy trading with novel data-driven MCP estimation using the finite horizon Markov decision process (MDP). Using historical data, the non-technical aspects of the UPP2P operation, such as market power, incomplete information, and bidding strategy, can be integrated into the process of predicting optimal MCP. Furthermore, a modified Kirschen network cost allocation (KNCA) method, which can estimate the effect of UPP2P participants on the network reliability and is incorporated to elucidate the optimization of MCP. The proposed UPP2P with data-driven MCP estimation is applied on a noncooperative matrix game-based UPP2P algorithm, and simulation results are given to show the effectiveness of the method. | - |
dc.description.sponsorship | This study was supported by the International Energy Joint R&D Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP), granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea. (No. 20228530050030). | - |
dc.language.iso | eng | - |
dc.publisher | IEEE Computer Society | - |
dc.subject.mesh | Energy trading | - |
dc.subject.mesh | Kirschen network cost allocation | - |
dc.subject.mesh | Market clearing | - |
dc.subject.mesh | Markov Decision Processes | - |
dc.subject.mesh | Matrix game | - |
dc.subject.mesh | Network cost allocation | - |
dc.subject.mesh | Noncooperative matrix game | - |
dc.subject.mesh | Peer to peer | - |
dc.subject.mesh | Peer-to-peer energy trading | - |
dc.subject.mesh | Price-based | - |
dc.subject.mesh | Uniform price | - |
dc.subject.mesh | Uniform price-based market clearing | - |
dc.title | Uniform Price-based Peer-to-peer Energy Trading with Data-driven Market Clearing Price Estimation | - |
dc.type | Conference | - |
dc.citation.conferenceDate | 2024.7.21. ~ 2024.7.25. | - |
dc.citation.conferenceName | 2024 IEEE Power and Energy Society General Meeting, PESGM 2024 | - |
dc.citation.edition | 2024 IEEE Power and Energy Society General Meeting, PESGM 2024 | - |
dc.citation.title | IEEE Power and Energy Society General Meeting | - |
dc.identifier.bibliographicCitation | IEEE Power and Energy Society General Meeting | - |
dc.identifier.doi | 10.1109/pesgm51994.2024.10688432 | - |
dc.identifier.scopusid | 2-s2.0-85207457596 | - |
dc.identifier.url | http://ieeexplore.ieee.org/xpl/conferences.jsp | - |
dc.subject.keyword | Kirschen network cost allocation | - |
dc.subject.keyword | Markov decision process | - |
dc.subject.keyword | noncooperative matrix games | - |
dc.subject.keyword | peer-to-peer energy trading | - |
dc.subject.keyword | uniform price-based market clearing | - |
dc.type.other | Conference Paper | - |
dc.description.isoa | false | - |
dc.subject.subarea | Energy Engineering and Power Technology | - |
dc.subject.subarea | Nuclear Energy and Engineering | - |
dc.subject.subarea | Renewable Energy, Sustainability and the Environment | - |
dc.subject.subarea | Electrical and Electronic Engineering | - |
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