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Network-aware P2P multi-energy trading in decentralized electric-heat systems

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  • Sun, Chao
  • Liu, Yun
  • Li, Yuanzheng
  • Lin, Shunjiang
  • Gooi, Hoay Beng
  • Zhu, Jizhong

Abstract

Facilitated by the emerging 4th generation low-temperature district heating network, the electric-heat system is evolving towards a decentralized architecture consisting of multiple interconnected energy hubs (EHs). Multi-energy sharing is an effective way to bring down the EH operating costs and improve system efficiency. To this end, the network-aware peer-to-peer multi-energy scheduling and trading (P2P-MEST) is investigated in this paper. Considering that the non-convex energy transfer loss is inevitable which makes the decision making complex, a decentralized dual-loop P2P-MEST scheme with dynamically updated loss factors is proposed. Specifically, in the inner-loop iteration, P2P-MEST among the EHs is performed by incorporating fixed transfer loss factors. In the outer loop, the transfer loss factors are updated based on the latest transactive results by distributively estimating the operational states of the electric-heat system. A market equilibrium can be iteratively reached where energy transfer loss can be accurately considered and physical operational constraints can be indirectly handled. Case studies on a 4-EH electric-heat system validate the necessity of considering the network constraints, especially the energy transfer loss in P2P-MEST. The numerical results indicate that the proposed scheme has a satisfactory convergence performance, effectively handles the various network constraints, and significantly reduces the operational cost of each EH.

Suggested Citation

  • Sun, Chao & Liu, Yun & Li, Yuanzheng & Lin, Shunjiang & Gooi, Hoay Beng & Zhu, Jizhong, 2023. "Network-aware P2P multi-energy trading in decentralized electric-heat systems," Applied Energy, Elsevier, vol. 345(C).
  • Handle: RePEc:eee:appene:v:345:y:2023:i:c:s0306261923006621
    DOI: 10.1016/j.apenergy.2023.121298
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    References listed on IDEAS

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    1. Qiu, Haifeng & Vinod, Ashwin & Lu, Shuai & Gooi, Hoay Beng & Pan, Guangsheng & Zhang, Suhan & Veerasamy, Veerapandiyan, 2023. "Decentralized mixed-integer optimization for robust integrated electricity and heat scheduling," Applied Energy, Elsevier, vol. 350(C).

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