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Peer-to-peer energy sharing with dynamic network structures

Author

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  • Chen, Liudong
  • Liu, Nian
  • Li, Chenchen
  • Zhang, Silu
  • Yan, Xiaohe

Abstract

The integration of distributed energy resources facilitates peer-to-peer (P2P) energy sharing as an effective way to coordinate the energy scheduling. Previous research has focused on economic P2P energy sharing of user side without considering the possible response strategies of network sides. This paper proposes a P2P energy sharing framework that takes into consideration the dynamic network structure. A P2P energy sharing model aimed at increasing the energy local consumption and reducing each prosumers’ power losses arisen from P2P energy sharing is built for the P2P energy schedule. In the physical network, a dynamic network structure model is designed to incorporate the network operator into the energy sharing process, and obtain the better network structure while reducing the power losses of whole network. These two proposed models are jointly optimized by the upper and lower layer to get the optimal P2P energy sharing schedule, network operations conditions and comprehensive energy utilization. The solution algorithm for the joint optimization is composed of a designed matching mechanism and branch-exchange method and realized by the iteration process. Finally, numerical analysis reveals the effectiveness of the proposed framework in terms of prosumers’ strategies, network structures, comprehensive energy utilization, and practical feasibility.

Suggested Citation

  • Chen, Liudong & Liu, Nian & Li, Chenchen & Zhang, Silu & Yan, Xiaohe, 2021. "Peer-to-peer energy sharing with dynamic network structures," Applied Energy, Elsevier, vol. 291(C).
  • Handle: RePEc:eee:appene:v:291:y:2021:i:c:s0306261921003305
    DOI: 10.1016/j.apenergy.2021.116831
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    References listed on IDEAS

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    Cited by:

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    2. Zhou, Yuekuan & Lund, Peter D., 2023. "Peer-to-peer energy sharing and trading of renewable energy in smart communities ─ trading pricing models, decision-making and agent-based collaboration," Renewable Energy, Elsevier, vol. 207(C), pages 177-193.
    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. Illia Diahovchenko & Lubov Petrichenko, 2022. "Comparative Analysis of Power Distribution Systems with Individual Prosumers Owing Photovoltaic Installations and Solar Energy Communities in Terms of Profitability and Hosting Capacity," Energies, MDPI, vol. 15(23), pages 1-20, November.
    5. Botelho, D.F. & de Oliveira, L.W. & Dias, B.H. & Soares, T.A. & Moraes, C.A., 2022. "Integrated prosumers–DSO approach applied in peer-to-peer energy and reserve tradings considering network constraints," Applied Energy, Elsevier, vol. 317(C).
    6. Li, Junkai & Ge, Shaoyun & Xu, Zhengyang & Liu, Hong & Li, Jifeng & Wang, Chengshan & Cheng, Xueying, 2023. "A network-secure peer-to-peer trading framework for electricity-carbon integrated market among local prosumers," Applied Energy, Elsevier, vol. 335(C).

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