Citation Export
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Noorfatima, Nadya | - |
| dc.contributor.author | Nam, Jounghoon | - |
| dc.contributor.author | Jung, Jaesung | - |
| dc.date.issued | 2023-01-01 | - |
| dc.identifier.uri | https://aurora.ajou.ac.kr/handle/2018.oak/36974 | - |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85174702863&origin=inward | - |
| dc.description.abstract | Multiple aggregators can be incorporated to utilize a large number of distributed energy resources (DERs) in distribution systems through hybrid peer-to-peer (P2P) energy trading. However, the optimal trading mechanism with less computation cost for hybrid P2P energy trading with multi-aggregators has not been investigated. Hence, this paper proposes the development of hybrid P2P energy trading with multiple aggregators by improving the mechanisms of customer allocation towards aggregators and trading optimization. For this purpose, a customer allocation mechanism using density-based clustering is developed with forecasting analysis. In addition, a hybrid P2P energy trading mechanism for multi-aggregators with distributed optimization is proposed. The results show that the proposed method improves the trading results and computation time compared to the existing methods. | - |
| dc.description.sponsorship | This research was supported by Energy AI Convergence Research & Development Program through the National IT Industry Promotion Agency of Korea (NIPA) funded by the Ministry of Science and ICT (No. S1601-20-1005) REFERENCES [1] H. Javed et al., \u201cRecent Trends, Challenges, and Future Aspects of P2P Energy Trading Platforms in Electrical-Based Networks Considering Blockchain Technology: A Roadmap Toward Environmental Sustainability,\u201d Frontiers in Energy Research, vol. 10. Frontiers Media SA, Mar. 18, 2022. [2] S. Haghifam, H. Laaksonen, and M. Shafie-Khah, \u201cModeling a Local Electricity Market for Transactive Energy Trading of Multi-Aggregators,\u201d IEEE Access, vol. 10. Institute of Electrical and Electronics Engineers (IEEE), pp. 68792\u201368806, 2022. [3] W. Bao, J. Yue, and Y. Rao, \u201cA Deep Learning Framework for Financial Time Series Using Stacked Autoencoders and Long-Short Term Memory,\u201d PLoS One, vol. 12, no. 7. Public Library of Science (PLoS), p. e0180944, July 14, 2017. [4] D. H. Nguyen, \Optimal Solution Analysis and Decentralized Mechanisms for Peer-to-Peer Energy Markets,\ IEEE Transactions on Power Systems, vol. 36, (2), pp. 1470-1481, 2021. Available: https://ieeexplore.ieee.org/document/9186203. [5] J.-G. Kim and B. Lee, \u201cAutomatic P2P Energy Trading Model Based on Reinforcement Learning Using Long Short-Term Delayed Reward,\u201d Energies, vol. 13, no. 20. MDPI AG, p. 5359, Oct. 14, 2020. [6] M. P. Deisenroth, A. Faisal, and C. S. Ong, Mathematics for Machine Learning | Pattern Recognition and Machine Learning. 2020. [7] H. M. Khodr et al, \Maximum Savings Approach for Location and Sizing of Capacitors in Distribution Systems,\ Electric Power Systems Research, vol. 78, (7), pp. 1192-1203, 2008. [8] Korea Electricity Company (KEPCO), International Electricity Tariff (2022). Available at: http://cyber.kepco.co.kr (Accessed October 4, 2022). | - |
| dc.language.iso | eng | - |
| dc.publisher | IEEE Computer Society | - |
| dc.subject.mesh | ADMM | - |
| dc.subject.mesh | Clusterings | - |
| dc.subject.mesh | Energy trading | - |
| dc.subject.mesh | GMM clustering | - |
| dc.subject.mesh | Hybrid P2P | - |
| dc.subject.mesh | LSTM | - |
| dc.subject.mesh | Multi-aggregator | - |
| dc.subject.mesh | P2P energy trading | - |
| dc.subject.mesh | Stackelberg game theory | - |
| dc.subject.mesh | Stackelberg Games | - |
| dc.title | Development of Hybrid Peer-to-peer Energy Trading for Distribution System with Multi-Aggregators | - |
| dc.type | Conference | - |
| dc.citation.conferenceDate | 2023.7.16. ~ 2023.7.20. | - |
| dc.citation.conferenceName | 2023 IEEE Power and Energy Society General Meeting, PESGM 2023 | - |
| dc.citation.edition | 2023 IEEE Power and Energy Society General Meeting, PESGM 2023 | - |
| dc.citation.title | IEEE Power and Energy Society General Meeting | - |
| dc.citation.volume | 2023-July | - |
| dc.identifier.bibliographicCitation | IEEE Power and Energy Society General Meeting, Vol.2023-July | - |
| dc.identifier.doi | 10.1109/pesgm52003.2023.10252880 | - |
| dc.identifier.scopusid | 2-s2.0-85174702863 | - |
| dc.identifier.url | http://ieeexplore.ieee.org/xpl/conferences.jsp | - |
| dc.subject.keyword | ADMM | - |
| dc.subject.keyword | GMM clustering | - |
| dc.subject.keyword | LSTM | - |
| dc.subject.keyword | Multi-aggregators | - |
| dc.subject.keyword | P2P energy trading | - |
| dc.subject.keyword | Stackelberg game theory | - |
| 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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