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Distributed planning of electricity and natural gas networks and energy hubs

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  • Yang, Hangbo
  • You, Pengcheng
  • Shang, Ce

Abstract

Centralized planning of the electricity network, natural gas network and energy hubs (EHs) implicitly assumes a vertically integrated structure, which ignores the common independent ownership of different systems. A more practical approach should differentiate the electric system, gas system and each EH as separate stakeholders, and establish a distributed planning framework. Such a distributed planning framework based on the alternating direction method of multipliers (ADMM) is proposed in this paper, which uses the amount of electricity and natural gas required by EHs from each node as the decoupling information, and decomposes the joint planning problem into multiple planning sub-problems, respectively for the electric system, natural gas system and each EH. To reflect the operation more accurately in the planning stage, unit commitment is embedded in the planning model as its operation module. Finally, the proposed method is verified on an illustrative system composed of a modified IEEE RTS 24-bus electric system, Belgian 20-node natural gas system and four EHs. The case study demonstrates the impacts of unit commitment, gas price and penalty parameters on the planning scheme and the number of iterations.

Suggested Citation

  • Yang, Hangbo & You, Pengcheng & Shang, Ce, 2021. "Distributed planning of electricity and natural gas networks and energy hubs," Applied Energy, Elsevier, vol. 282(PA).
  • Handle: RePEc:eee:appene:v:282:y:2021:i:pa:s0306261920315142
    DOI: 10.1016/j.apenergy.2020.116090
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    2. Najafi, Arsalan & Pourakbari-Kasmaei, Mahdi & Jasinski, Michal & Lehtonen, Matti & Leonowicz, Zbigniew, 2022. "A medium-term hybrid IGDT-Robust optimization model for optimal self scheduling of multi-carrier energy systems," Energy, Elsevier, vol. 238(PA).
    3. Xu, Xiao & Hu, Weihao & Liu, Wen & Du, Yuefang & Huang, Rui & Huang, Qi & Chen, Zhe, 2021. "Look-ahead risk-constrained scheduling for an energy hub integrated with renewable energy," Applied Energy, Elsevier, vol. 297(C).
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    5. Najafi, Arsalan & Pourakbari-Kasmaei, Mahdi & Jasinski, Michal & Lehtonen, Matti & Leonowicz, Zbigniew, 2021. "A hybrid decentralized stochastic-robust model for optimal coordination of electric vehicle aggregator and energy hub entities," Applied Energy, Elsevier, vol. 304(C).
    6. Pengying Wang & Shuo Zhang & Limei Chen, 2023. "Research on the Integration of a Natural Gas-Distributed Energy System into the Oilfield Facility in China," Sustainability, MDPI, vol. 15(4), pages 1-15, February.

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