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Cooperative operation of multiple low-carbon microgrids: An optimization study addressing gaming fraud and multiple uncertainties

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  • Zhao, Bingxu
  • Cao, Xiaodong
  • Duan, Pengfei

Abstract

To achieve efficient utilization of renewable energy and facilitate the development of a more equitable and harmonious power market, an optimization study is conducted focusing on peer-to-peer (P2P) power sharing within multiple low-carbon microgrids (LCMGs). Firstly, the coordinated operation mechanism of a LCMG is proposed involving a step-type carbon trading scheme as well as flexible supply and demand. Then, an optimization model of multi-LCMG cooperative operation is formulated based on the Nash bargaining theory. The original Nash bargaining problem is equivalently transformed into a subproblem of maximizing alliance benefits and a subproblem of maximizing the benefits of power trading. In the first subproblem, a combination of opportunity constraints and robust optimization method is employed to address these multiple uncertainties from renewable generation and electricity prices. The second subproblem addresses the issue of gaming fraud among LCMGs with a third-party intermediary model applied to achieve a fraud equilibrium. Further, to solve these problems efficiently, an improved adaptive parametric alternating direction method of multipliers (AP-ADMM) algorithm is used to protect the privacy of each party. Finally, a case study was conducted to validate the efficacy of the proposed method in enhancing the stability and cost-effectiveness of cooperative optimization within multi-LCMG systems.

Suggested Citation

  • Zhao, Bingxu & Cao, Xiaodong & Duan, Pengfei, 2024. "Cooperative operation of multiple low-carbon microgrids: An optimization study addressing gaming fraud and multiple uncertainties," Energy, Elsevier, vol. 297(C).
    • Handle: RePEc:eee:energy:v:297:y:2024:i:c:s0360544224010302
    DOI: 10.1016/j.energy.2024.131257
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    Cited by:

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    3. Liu, Nian & Yan, Jinwei & Tan, Lu & Li, Xinhao & Chen, Youxin & Zhang, Kuan, 2025. "A low-carbon trading strategy of multi-microgrid system considering electricity-hydrogen-carbon coupling characteristics," Energy, Elsevier, vol. 327(C).
    4. Hu, Jinxue & Duan, Pengfei & Cao, Xiaodong & Xue, Qingwen & Zhao, Bingxu & Zhao, Xiaoyu & Yuan, Xiaoyang & Zhang, Chenyang, 2025. "A multi-energy load forecasting method based on the Mixture-of-Experts model and dynamic multilevel attention mechanism," Energy, Elsevier, vol. 324(C).
    5. Shuai Wang & Xiaojing Ma & Yaling Yan & Tusongjiang Kari & Wei Zhang, 2025. "Collaborative Game Theory Between Microgrid Operators and Distribution System Operator Considering Multi-Faceted Uncertainties," Energies, MDPI, vol. 18(7), pages 1-25, March.
    6. Nurcan Yarar & Yeliz Yoldas & Serkan Bahceci & Ahmet Onen & Jaesung Jung, 2024. "A Comprehensive Review Based on the Game Theory with Energy Management and Trading," Energies, MDPI, vol. 17(15), pages 1-29, July.

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