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Price-Guided Peer-To-Peer Trading Scheme and Its Effects on Transaction Costs and Network Losses

Author

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  • SungJoong Kim

    (Electric Power Network and Economics Laboratory, Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea)

  • YongTae Yoon

    (Electric Power Network and Economics Laboratory, Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea)

  • YoungGyu Jin

    (Power System Economics Laboratory, Department of Electrical Engineering, Jeju National University, 102 Jejudaehak-ro, Jeju 62343, Korea)

Abstract

Distributed energy resources (DERs), such as small-scale renewable energy generators, storage systems, and controllable loads, have been attracting great attention. Accordingly, interest in peer-to-peer (P2P) energy trading between prosumers with DERs is growing. The prosumers may perform the P2P electricity trading within the loss-guided framework, where network losses are primarily considered during the peer matching process. However, the loss-guided framework has limitations in that prosumer welfare is neglected in favor of prioritizing the network losses caused by the P2P transactions. Thus, in this study, a price-based framework for P2P electricity trading is suggested, where the prosumer welfare is considered by including not only network loss costs but also energy costs in the matching procedure. The effects of the suggested price-based framework on network efficiency, prosumer welfare, and social welfare are examined by comparing simulation results with the loss-guided framework and the random transactions. Further, how those three properties are affected by the change in loss price is analyzed and a guideline for the suitable choice of the loss price is suggested.

Suggested Citation

  • SungJoong Kim & YongTae Yoon & YoungGyu Jin, 2022. "Price-Guided Peer-To-Peer Trading Scheme and Its Effects on Transaction Costs and Network Losses," Energies, MDPI, vol. 15(21), pages 1-19, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:21:p:8274-:d:964173
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    References listed on IDEAS

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    1. Jiayi, Huang & Chuanwen, Jiang & Rong, Xu, 2008. "A review on distributed energy resources and MicroGrid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(9), pages 2472-2483, December.
    2. Yael Parag & Benjamin K. Sovacool, 2016. "Electricity market design for the prosumer era," Nature Energy, Nature, vol. 1(4), pages 1-6, April.
    3. Alarcon-Rodriguez, Arturo & Ault, Graham & Galloway, Stuart, 2010. "Multi-objective planning of distributed energy resources: A review of the state-of-the-art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1353-1366, June.
    4. SungJoong Kim & YeonOuk Chu & HyunJoong Kim & HyungTae Kim & HeeSeung Moon & JinHo Sung & YongTae Yoon & YoungGyu Jin, 2022. "Analyzing Various Aspects of Network Losses in Peer-to-Peer Electricity Trading," Energies, MDPI, vol. 15(3), pages 1-23, January.
    5. Akorede, Mudathir Funsho & Hizam, Hashim & Pouresmaeil, Edris, 2010. "Distributed energy resources and benefits to the environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 724-734, February.
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