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Optimization of Cooperative Operation of Multiple Microgrids Considering Green Certificates and Carbon Trading

Author

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  • Xiaobin Xu

    (State Grid Hebei Economic Research Institute, Shijiazhuang 050023, China)

  • Jing Xia

    (State Grid Hebei Economic Research Institute, Shijiazhuang 050023, China)

  • Chong Hong

    (State Grid Hebei Economic Research Institute, Shijiazhuang 050023, China)

  • Pengfei Sun

    (State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050023, China)

  • Peng Xi

    (State Grid Hebei Economic Research Institute, Shijiazhuang 050023, China)

  • Jinchao Li

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

Abstract

In the context of achieving low-carbon goals, building low-carbon energy systems is a crucial development direction and implementation pathway. Renewable energy is favored because of its clean characteristics, but the access may have an impact on the power grid. Microgrid technology provides an effective solution to this problem. Uncertainty exists in single microgrids, so multiple microgrids are introduced to improve system stability and robustness. Electric carbon trading and profit redistribution among multiple microgrids have been challenges. To promote energy commensurability among microgrids, expand the types of energy interactions, and improve the utilization rate of renewable energy, this paper proposes a cooperative operation optimization model of multi-microgrids based on the green certificate and carbon trading mechanism to promote local energy consumption and a low carbon economy. First, this paper introduces a carbon capture system (CCS) and power-to-gas (P2G) device in the microgrid and constructs a cogeneration operation model coupled with a power-to-gas carbon capture system. On this basis, a low-carbon operation model for multi-energy microgrids is proposed by combining the local carbon trading market, the stepped carbon trading mechanism, and the green certificate trading mechanism. Secondly, this paper establishes a cooperative game model for multiple microgrid electricity carbon trading based on the Nash negotiation theory after constructing the single microgrid model. Finally, the ADMM method and the asymmetric energy mapping contribution function are used for the solution. The case study uses a typical 24 h period as an example for the calculation. Case study analysis shows that, compared with the independent operation mode of microgrids, the total benefits of the entire system increased by 38,296.1 yuan and carbon emissions were reduced by 30,535 kg through the coordinated operation of electricity–carbon coupling. The arithmetic example verifies that the method proposed in this paper can effectively improve the economic benefits of each microgrid and reduce carbon emissions.

Suggested Citation

  • Xiaobin Xu & Jing Xia & Chong Hong & Pengfei Sun & Peng Xi & Jinchao Li, 2025. "Optimization of Cooperative Operation of Multiple Microgrids Considering Green Certificates and Carbon Trading," Energies, MDPI, vol. 18(15), pages 1-31, August.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:15:p:4083-:d:1715888
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    References listed on IDEAS

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    1. Xiaoqing Wang & Wenxin Jin & Baochang Xu & Kaihua Wang, 2025. "Volatility in Carbon Futures Amid Uncertainties: Considering Geopolitical and Economic Policy Factors," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(4), pages 308-325, April.
    2. Ma, Tengfei & Pei, Wei & Deng, Wei & Xiao, Hao & Yang, Yanhong & Tang, Chenghong, 2022. "A Nash bargaining-based cooperative planning and operation method for wind-hydrogen-heat multi-agent energy system," Energy, Elsevier, vol. 239(PE).
    3. Wang, Zhuo & Hou, Hui & Zhao, Bo & Zhang, Leiqi & Shi, Ying & Xie, Changjun, 2024. "Risk-averse stochastic capacity planning and P2P trading collaborative optimization for multi-energy microgrids considering carbon emission limitations: An asymmetric Nash bargaining approach," Applied Energy, Elsevier, vol. 357(C).
    4. Pan, Yushu & Ju, Liwei & Yang, Shenbo & Guo, Xinyu & Tan, Zhongfu, 2024. "A multi-objective robust optimal dispatch and cost allocation model for microgrids-shared hybrid energy storage system considering flexible ramping capacity," Applied Energy, Elsevier, vol. 369(C).
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