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Distributed energy trading on networked energy hubs under network constraints

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  • Wu, Yuxin
  • Yan, Haoyuan
  • Liu, Min
  • Zhao, Tianyang
  • Qiu, Jiayu
  • Liu, Shengwei

Abstract

A distributed energy trading scheme with non-discriminatory pricing for a cluster of networked energy hubs (NEHs) is proposed. First, each energy hub (EH) is treated as a self-interested agent. The hybrid AC/DC microgrid (MG)-embedded EH model is proposed to optimize the operating costs under corresponding local energy balance constraints. The supply limits of the input energy systems, e.g., electrical feeders and natural gas pipelines, are represented as the global coupling constraints among NEHs. Then, to obtain the optimal operation and trading strategies, the distributed energy trading is formulated as a generalized Nash game (GNG). To ensure the solubility of the GNG problem, the existence and uniqueness of the generalized Nash equilibrium (GNE) are proved. Furthermore, to transform the complexity of the solution, the multivariable GNG problem is reformulated as a N+1 Nash game (NG) without coupling constraints, the equivalence between NG and the solution set of variational inequality (VI) problem is established. Then, an efficient distributed projection-based algorithm is proposed to compute a Nash equilibrium (NE) for the NG problem. Finally, a potential game-based centralized solution method is also implemented as a baseline, and the comparison of simulation results demonstrates the effectiveness of our proposed algorithm.

Suggested Citation

  • Wu, Yuxin & Yan, Haoyuan & Liu, Min & Zhao, Tianyang & Qiu, Jiayu & Liu, Shengwei, 2023. "Distributed energy trading on networked energy hubs under network constraints," Renewable Energy, Elsevier, vol. 209(C), pages 491-504.
  • Handle: RePEc:eee:renene:v:209:y:2023:i:c:p:491-504
    DOI: 10.1016/j.renene.2023.03.109
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    References listed on IDEAS

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    1. Lu, Xinhui & Liu, Zhaoxi & Ma, Li & Wang, Lingfeng & Zhou, Kaile & Yang, Shanlin, 2020. "A robust optimization approach for coordinated operation of multiple energy hubs," Energy, Elsevier, vol. 197(C).
    2. Gan, Wei & Yan, Mingyu & Yao, Wei & Wen, Jinyu, 2021. "Peer to peer transactive energy for multiple energy hub with the penetration of high-level renewable energy," Applied Energy, Elsevier, vol. 295(C).
    3. Francisco Facchinei & Christian Kanzow, 2010. "Generalized Nash Equilibrium Problems," Annals of Operations Research, Springer, vol. 175(1), pages 177-211, March.
    4. Najafi, Arsalan & Falaghi, Hamid & Contreras, Javier & Ramezani, Maryam, 2016. "Medium-term energy hub management subject to electricity price and wind uncertainty," Applied Energy, Elsevier, vol. 168(C), pages 418-433.
    5. Heidari, A. & Mortazavi, S.S. & Bansal, R.C., 2020. "Stochastic effects of ice storage on improvement of an energy hub optimal operation including demand response and renewable energies," Applied Energy, Elsevier, vol. 261(C).
    6. Harker, Patrick T., 1991. "Generalized Nash games and quasi-variational inequalities," European Journal of Operational Research, Elsevier, vol. 54(1), pages 81-94, September.
    7. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    8. Nikmehr, Nima, 2020. "Distributed robust operational optimization of networked microgrids embedded interconnected energy hubs," Energy, Elsevier, vol. 199(C).
    9. Junichi Haraguchi & Toshihiro Matsumura, 2016. "Cournot–Bertrand comparison in a mixed oligopoly," Journal of Economics, Springer, vol. 117(2), pages 117-136, March.
    10. Han, Deren & Zhang, Hongchao & Qian, Gang & Xu, Lingling, 2012. "An improved two-step method for solving generalized Nash equilibrium problems," European Journal of Operational Research, Elsevier, vol. 216(3), pages 613-623.
    11. Bostan, Alireza & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs," Energy, Elsevier, vol. 190(C).
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    1. Wu, Qian & Song, Qiankun & He, Xing & Chen, Guo & Huang, Tingwen, 2024. "Distributed peer-to-peer energy trading framework with manufacturing assembly process and uncertain renewable energy plants in multi-industrial micro-grids," Energy, Elsevier, vol. 302(C).

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