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A Nash bargaining model for energy sharing between micro-energy grids and energy storage

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  • Wang, Zaichuang
  • Chen, Laijun
  • Li, Xiaozhu
  • Mei, Shengwei

Abstract

Micro-energy grids (MEGs) play a crucial role in achieving diverse energy utilization and promoting low-carbon economies. However, the intermittent nature of distributed generation and the inter-coupling of multiple energy types pose challenges to efficient energy management in MEGs. In this paper, we propose a novel Nash bargaining game-based electricity-gas energy-sharing model for MEGs. Our model incorporates bus structure-based energy storage combined with power-to-gas technology, which enables MEGs to establish an integrated electricity-gas energy-sharing network. This network facilitates both direct sharing and buffered sharing of energy, addressing the limitations of intermittent generation and enhancing overall energy management. To address the issue of computational complexity, the proposed Nash bargaining game model is decomposed into two sub-problems: social energy cost minimization and benefits sharing. Through optimization, we obtain optimal energy-sharing profiles and energy-sharing payments. Moreover, we consider the investment payback period of energy storage and adjust the initial benefit-sharing results accordingly. Case studies demonstrate that our model significantly improves economic performance, increasing the self-sufficiency ratio of MEGs to 64% and energy storage efficiency to 63% compared to operating independently. Additionally, the multiplayer Nash bargaining game model facilitates Pareto optimal benefits for MEGs and energy storage by capturing their interactive dynamics.

Suggested Citation

  • Wang, Zaichuang & Chen, Laijun & Li, Xiaozhu & Mei, Shengwei, 2023. "A Nash bargaining model for energy sharing between micro-energy grids and energy storage," Energy, Elsevier, vol. 283(C).
  • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223024593
    DOI: 10.1016/j.energy.2023.129065
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    1. Götz, Manuel & Lefebvre, Jonathan & Mörs, Friedemann & McDaniel Koch, Amy & Graf, Frank & Bajohr, Siegfried & Reimert, Rainer & Kolb, Thomas, 2016. "Renewable Power-to-Gas: A technological and economic review," Renewable Energy, Elsevier, vol. 85(C), pages 1371-1390.
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    1. Hou, Langbo & Tong, Xi & Chen, Heng & Fan, Lanxin & Liu, Tao & Liu, Wenyi & Liu, Tong, 2024. "Optimized scheduling of smart community energy systems considering demand response and shared energy storage," Energy, Elsevier, vol. 295(C).

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