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Bi-level operation model for energy hub based on energy-carbon coordination optimization framework

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Listed:
  • Ma, Siyuan
  • Mi, Yang
  • Li, Sidan
  • Wang, Xiaohu
  • Li, Dongdong
  • Wang, Peng

Abstract

Energy hub modeling is crucial for the operation and management of integrated energy system. In order to optimize the operation of integrated energy system from both economic and low-carbon perspectives, this paper proposes a bi-level optimization model for energy hub. This model can coordinate energy-carbon flows and incorporate a low-carbon integrated demand response. First, a unified carbon emission flow coupling matrix model for energy hub is formulated, the accurate carbon information can be transmitted from superior energy networks to terminal user side. Second, a bi-level energy-carbon collaborative optimization model is established. The upper-level coordinates the goals of operating cost and carbon reduction, then releases carbon intensity signals to consumers. Simultaneously, an iterative algorithm is presented to determine storage states and minimize carbon emissions. The lower-level adjusts energy consumption strategies to maximize the consumer surplus based on the low-carbon psychological demand response mechanism. The two-level model is bridged through interactive variables and solved iteratively until equilibrium is reached. Finally, case studies illustrate the effectiveness and applicability of the proposed method. Specifically, this method achieves a 1.84 % cost savings, a 9.06 % carbon emission reduction, and a 9.39 % consumer surplus growth compared to other methods. It shows comprehensive advantages for achieving low-carbon and economy operation for energy hub and enhancing utility for users.

Suggested Citation

  • Ma, Siyuan & Mi, Yang & Li, Sidan & Wang, Xiaohu & Li, Dongdong & Wang, Peng, 2025. "Bi-level operation model for energy hub based on energy-carbon coordination optimization framework," Energy, Elsevier, vol. 333(C).
  • Handle: RePEc:eee:energy:v:333:y:2025:i:c:s0360544225030919
    DOI: 10.1016/j.energy.2025.137449
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    as
    1. Ye, Jin & Shuai, Qilin & Hua, Qingsong, 2025. "Dynamic programming-based low-carbon and economic scheduling of integrated energy system," Energy, Elsevier, vol. 322(C).
    2. Wei, F. & Jing, Z.X. & Wu, Peter Z. & Wu, Q.H., 2017. "A Stackelberg game approach for multiple energies trading in integrated energy systems," Applied Energy, Elsevier, vol. 200(C), pages 315-329.
    3. Zhou, Yuan & Wang, Jiangjiang & Yang, Mingxu & Xu, Hangwei, 2023. "Hybrid active and passive strategies for chance-constrained bilevel scheduling of community multi-energy system considering demand-side management and consumer psychology," Applied Energy, Elsevier, vol. 349(C).
    4. Gou, Tong & Xu, Yinliang & Sun, Hongbin, 2025. "Carbon-aware day-ahead optimal dispatch for integrated power grid thermal systems with aggregated distributed resources," Applied Energy, Elsevier, vol. 389(C).
    5. Yang, Shenbo & Tan, Zhongfu & Lin, Hongyu & Li, Peng & De, Gejirifu & Zhou, Feng’ao & Ju, Liwei, 2020. "A two-stage optimization model for Park Integrated Energy System operation and benefit allocation considering the effect of Time-Of-Use energy price," Energy, Elsevier, vol. 195(C).
    6. Li, Songrui & Zhang, Lihui & Nie, Lei & Wang, Jianing, 2022. "Trading strategy and benefit optimization of load aggregators in integrated energy systems considering integrated demand response: A hierarchical Stackelberg game," Energy, Elsevier, vol. 249(C).
    7. Lu, Xinhui & Li, Haobin & Zhou, Kaile & Yang, Shanlin, 2023. "Optimal load dispatch of energy hub considering uncertainties of renewable energy and demand response," Energy, Elsevier, vol. 262(PB).
    8. Wan, Tong & Tao, Yuechuan & Qiu, Jing & Lai, Shuying, 2023. "Internet data centers participating in electricity network transition considering carbon-oriented demand response," Applied Energy, Elsevier, vol. 329(C).
    9. Zhang, Suhan & Chen, Shibo & Gu, Wei & Lu, Shuai & Chung, Chi Yung, 2024. "Dynamic optimal energy flow of integrated electricity and gas systems in continuous space," Applied Energy, Elsevier, vol. 375(C).
    10. Ma, Siyu & Liu, Hui & Wang, Ni & Huang, Lidong & Su, Jinshuo & Zhao, Teyang, 2024. "Incentive-based integrated demand response with multi-energy time-varying carbon emission factors," Applied Energy, Elsevier, vol. 359(C).
    11. Frederiks, Elisha R. & Stenner, Karen & Hobman, Elizabeth V., 2015. "Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1385-1394.
    12. Fan, Songli & Xu, Guodong & Jiang, Baoping & Wu, Zhengtian & Xing, Haijun & Gao, Yang & Ai, Qian, 2025. "Low-carbon economic operation of commercial park-level integrated energy systems incorporating supply and demand flexibility," Energy, Elsevier, vol. 323(C).
    13. Ma, Siyuan & Mi, Yang & Shi, Shuai & Li, Dongdong & Xing, Haijun & Wang, Peng, 2024. "Low-carbon economic operation of energy hub integrated with linearization model and nodal energy-carbon price," Energy, Elsevier, vol. 294(C).
    14. Tao, Jiaxin & Duan, Jiandong & Tuo, Lihao & Gao, Qi & Tian, Qinxing & Lu, Wenchao, 2025. "Exergy efficiency based multi-objective configuration optimization of energy hubs in the multi-energy distribution system," Energy, Elsevier, vol. 329(C).
    15. Zhong, Junjie & Zhao, Yirui & Cao, Yijia, 2024. "Collaborative optimization for energy hub and load aggregator considering the carbon intensity-driven and uncertainty-aware," Energy, Elsevier, vol. 312(C).
    16. Liang, Tao & Chai, Lulu & Tan, Jianxin & Jing, Yanwei & Lv, Liangnian, 2024. "Dynamic optimization of an integrated energy system with carbon capture and power-to-gas interconnection: A deep reinforcement learning-based scheduling strategy," Applied Energy, Elsevier, vol. 367(C).
    17. Lu, Shuai & Li, Yuan & Gu, Wei & Xu, Yijun & Ding, Shixing, 2023. "Economy-carbon coordination in integrated energy systems: Optimal dispatch and sensitivity analysis," Applied Energy, Elsevier, vol. 351(C).
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