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Distributed operation optimization of active distribution network with P2P electricity trading in blockchain environment

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  • Ruan, Hebin
  • Gao, Hongjun
  • Qiu, Haifeng
  • Gooi, Hoay Beng
  • Liu, Junyong

Abstract

With the increasing integration of distributed generators and the rapid development of electricity markets, active distribution networks (ADNs) confront new challenges in operation optimization. Centralized optimization methods usually aggravate the computational burden when applied to large-scale distribution networks (DNs). A distributed operation optimization model incorporating peer-to-peer (P2P) electricity trading in a blockchain environment is proposed in this paper, where network usage fees considering electrical distance are specially addressed. Meanwhile, the private information security of prosumers is ensured by the Proof-of-Authority (PoA) consensus blockchain during P2P electricity trading. The trading information of adjustable prosumers should be sent to the proxy entity authorized by the DN using the blockchain platform. In addition, a network partitioning method via dynamic reconfiguration considering multi-level switching is offered to adapt to the required distributed manner. The operation network, as well as the corresponding market structure can be automatically updated according to the results of dynamic reconfiguration. Moreover, the unit price of network usage fees can be adjusted to derive a higher amount of P2P electricity trading with security constraints. Case studies on a practical 148-bus system and a 297-bus system verify that the proposed model maximizes the profits and reduces the computational time in the distributed operation optimization.

Suggested Citation

  • Ruan, Hebin & Gao, Hongjun & Qiu, Haifeng & Gooi, Hoay Beng & Liu, Junyong, 2023. "Distributed operation optimization of active distribution network with P2P electricity trading in blockchain environment," Applied Energy, Elsevier, vol. 331(C).
    • Handle: RePEc:eee:appene:v:331:y:2023:i:c:s0306261922016622
    DOI: 10.1016/j.apenergy.2022.120405
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    References listed on IDEAS

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    Cited by:

    1. Ioanna Andreoulaki & Aikaterini Papapostolou & Vangelis Marinakis, 2024. "Evaluating the Barriers to Blockchain Adoption in the Energy Sector: A Multicriteria Approach Using the Analytical Hierarchy Process for Group Decision Making," Energies, MDPI, vol. 17(6), pages 1-27, March.
    2. Xia, Yuanxing & Xu, Qingshan & Fang, Jicheng & Tang, Rongchuan & Du, Pengwei, 2024. "Bipartite graph-based community-to-community matching in local energy market considering socially networked prosumers," Applied Energy, Elsevier, vol. 353(PB).
    3. Carlos Oliveira & Micael Simões & Leonardo Bitencourt & Tiago Soares & Manuel A. Matos, 2023. "Distributed Network-Constrained P2P Community-Based Market for Distribution Networks," Energies, MDPI, vol. 16(3), pages 1-16, February.
    4. Zhang, Kaoshe & Gao, Congchong & Zhang, Gang & Xie, Tuo & Li, Hua, 2024. "Electricity and heat sharing strategy of regional comprehensive energy multi-microgrid based on double-layer game," Energy, Elsevier, vol. 293(C).

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