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Energy Trading Strategies for Integrated Energy Systems Considering Uncertainty

Author

Listed:
  • Jin Gao

    (Key Laboratory of Energy Digitalization, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
    Department of Electrical Engineering, Yuan Ze University, Taoyuan 32003, Taiwan)

  • Zhenguo Shao

    (Key Laboratory of Energy Digitalization, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China)

  • Feixiong Chen

    (Key Laboratory of Energy Digitalization, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China)

  • Mohammadreza Lak

    (Department of Electrical Engineering, Yuan Ze University, Taoyuan 32003, Taiwan)

Abstract

To improve the stable operation and promote the energy sharing of the integrated energy system (IES), a comprehensive energy trading strategy considering uncertainty is proposed. Firstly, an IES model incorporating power-to-gas (P2G) and a carbon capture system (CCS) is established to reduce carbon emissions. Secondly, this model is integrated into a four-level robust optimization to address the fluctuation of renewable energy sources in IES operations. This not only considers probability distribution scenarios of renewable energy and the uncertainty of its output, but also effectively reduces the model’s conservatism by constructing a multi-interval uncertainty set. On this basis, a Nash–Harsanyi bargaining method is used to solve the issue of benefit allocation among multiple IESs. Finally, the energy trading model is solved using a distributed algorithm that ensures an equitable distribution of benefits while protecting the privacy of each IES. The simulation results validate the effectiveness of the proposed strategy.

Suggested Citation

  • Jin Gao & Zhenguo Shao & Feixiong Chen & Mohammadreza Lak, 2025. "Energy Trading Strategies for Integrated Energy Systems Considering Uncertainty," Energies, MDPI, vol. 18(4), pages 1-21, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:4:p:935-:d:1592006
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    References listed on IDEAS

    as
    1. Chen, Weidong & Wang, Junnan & Yu, Guanyi & Chen, Jiajia & Hu, Yumeng, 2022. "Research on day-ahead transactions between multi-microgrid based on cooperative game model," Applied Energy, Elsevier, vol. 316(C).
    2. Wu, Xiao & Yang, Lihua & Zheng, Bingle, 2024. "Joint capacity configuration and demand response optimization of integrated energy system considering economic and dynamic control performance," Energy, Elsevier, vol. 301(C).
    3. Singh, Kamini & Gadh, Rajit & Singh, Anoop & Lal Dewangan, Chaman, 2022. "Design of an optimal P2P energy trading market model using bilevel stochastic optimization," Applied Energy, Elsevier, vol. 328(C).
    4. Aras Ghafoor & Jamal Aldahmashi & Judith Apsley & Siniša Djurović & Xiandong Ma & Mohamed Benbouzid, 2024. "Intelligent Integration of Renewable Energy Resources Review: Generation and Grid Level Opportunities and Challenges," Energies, MDPI, vol. 17(17), pages 1-29, September.
    5. Liu, Sha & Shen, Jiong & Zhang, Junli, 2024. "A novel configuration optimization approach for IES considering exergy-degradation and non-energy costs of equipment," Energy, Elsevier, vol. 312(C).
    6. Khan, Saad Salman & Ahmad, Sadiq & Naeem, Muhammad, 2023. "On-grid joint energy management and trading in uncertain environment," Applied Energy, Elsevier, vol. 330(PB).
    7. Wang, Shouxiang & Wang, Shaomin & Zhao, Qianyu & Dong, Shuai & Li, Hao, 2023. "Optimal dispatch of integrated energy station considering carbon capture and hydrogen demand," Energy, Elsevier, vol. 269(C).
    Full references (including those not matched with items on IDEAS)

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