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Towards the Design of P2P Energy Trading Scheme Based on Optimal Energy Scheduling for Prosumers

Author

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  • Koo-Hyung Chung

    (Smart Grid Research Division, Korea Electrotechnology Research Institute, 12 Bulmosan-ro 10beon-gil, Seongsan-gu, Changwon-si 51543, Korea)

  • Don Hur

    (Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 01897, Korea)

Abstract

The peer-to-peer (P2P) energy trading is anchored in more efficient usage of electric power by allowing excess electric power from energy prosumers to be harnessed by other end-users. To boost the P2P energy trading, it is of pivotal significance to call on energy prosumers and end-users to actively participate in the trading while sharing information with a greater degree of freedom. In this perspective, this paper purports to implement the P2P energy trading scheme with an optimization model to assist in energy prosumers’ decisions by reckoning on hourly electric power available in the trading via the optimal energy scheduling of the energy trading and sharing system (ETS). On a purely practical level, it is assumed that all trading participants neither join the separate bidding processes nor are forced to comply with the predetermined optimal schedules for a trading period. Furthermore, this paper will be logically elaborated with reference to not only the determination of transaction price for maximizing the benefits of consumers under the different electricity rates but the establishment of additional settlement standards for bridging an imperative gap between optimally planned and actually transacted quantities of the P2P energy trading.

Suggested Citation

  • Koo-Hyung Chung & Don Hur, 2020. "Towards the Design of P2P Energy Trading Scheme Based on Optimal Energy Scheduling for Prosumers," Energies, MDPI, vol. 13(19), pages 1-15, October.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5177-:d:423876
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    References listed on IDEAS

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    9. Min Fu & Zhiyu Xu & Ning Wang & Xiaoyu Lyu & Weisheng Xu, 2020. "“Peer-to-Peer Plus” Electricity Transaction within Community of Active Energy Agents Regarding Distribution Network Constraints," Energies, MDPI, vol. 13(9), pages 1-23, May.
    10. Christie Etukudor & Benoit Couraud & Valentin Robu & Wolf-Gerrit Früh & David Flynn & Chinonso Okereke, 2020. "Automated Negotiation for Peer-to-Peer Electricity Trading in Local Energy Markets," Energies, MDPI, vol. 13(4), pages 1-19, February.
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    Cited by:

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    2. Liaqat Ali & M. Imran Azim & Nabin B. Ojha & Jan Peters & Vivek Bhandari & Anand Menon & Vinod Tiwari & Jemma Green & S.M. Muyeen, 2023. "Balancing Usage Profiles and Benefitting End Users through Blockchain Based Local Energy Trading: A German Case Study," Energies, MDPI, vol. 16(17), pages 1-18, August.
    3. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K. & Yuen, Chau & Smith, David, 2022. "Peer-to-peer kilowatt and negawatt trading: A review of challenges and recent advances in distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    4. Adrian Kampa & Iwona Paprocka, 2021. "Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times," Energies, MDPI, vol. 14(21), pages 1-25, November.
    5. Seongwoo Lee & Joonho Seon & Chanuk Kyeong & Soohyun Kim & Youngghyu Sun & Jinyoung Kim, 2021. "Novel Energy Trading System Based on Deep-Reinforcement Learning in Microgrids," Energies, MDPI, vol. 14(17), pages 1-14, September.
    6. Rozmysław Mieński & Przemysław Urbanek & Irena Wasiak, 2021. "Using Energy Storage Inverters of Prosumer Installations for Voltage Control in Low-Voltage Distribution Networks," Energies, MDPI, vol. 14(4), pages 1-21, February.
    7. Meritxell Domènech Monfort & César De Jesús & Natapon Wanapinit & Niklas Hartmann, 2022. "A Review of Peer-to-Peer Energy Trading with Standard Terminology Proposal and a Techno-Economic Characterisation Matrix," Energies, MDPI, vol. 15(23), pages 1-29, November.
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