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Low-carbon economic operation of energy hub integrated with linearization model and nodal energy-carbon price

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  • Ma, Siyuan
  • Mi, Yang
  • Shi, Shuai
  • Li, Dongdong
  • Xing, Haijun
  • Wang, Peng

Abstract

Energy hub has positive significance in absorbing renewable energy, improving energy utilization efficiency and reducing carbon emissions. Considering both linearization energy hub model and nodal integrated energy-carbon price, a low-carbon economic operation model of energy hub is constructed by taking advantage of the bi-level optimization structure. First, in order to simplify the modeling procedures and improve the solving efficiency, reversibility judgment criteria and linearization processes in energy hub modeling are improved. Then, a nodal integrated energy-carbon pricing strategy is proposed and calculated according to flow tracing method and carbon emission flow method. Additionally, the bi-level optimization model and solution procedure are presented to obtain the optimal operating states of energy hubs. At last, for the simulation results, the characteristics and the influence of nodal price on energy consumption behaviors of energy hubs are analyzed, the proposed model is effective to reduce the carbon emissions and operating costs.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:294:y:2024:i:c:s0360544224005267
    DOI: 10.1016/j.energy.2024.130754
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    1. Zhu, Xu & Sun, Yuanzhang & Yang, Jun & Dou, Zhenlan & Li, Gaojunjie & Xu, Chengying & Wen, Yuxin, 2022. "Day-ahead energy pricing and management method for regional integrated energy systems considering multi-energy demand responses," Energy, Elsevier, vol. 251(C).
    2. Gu, Haifei & Li, Yang & Yu, Jie & Wu, Chen & Song, Tianli & Xu, Jinzhou, 2020. "Bi-level optimal low-carbon economic dispatch for an industrial park with consideration of multi-energy price incentives," Applied Energy, Elsevier, vol. 262(C).
    3. Wang, Yi & Cheng, Jiangnan & Zhang, Ning & Kang, Chongqing, 2018. "Automatic and linearized modeling of energy hub and its flexibility analysis," Applied Energy, Elsevier, vol. 211(C), pages 705-714.
    4. 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).
    5. Shao, Changzheng & Ding, Yi & Wang, Jianhui, 2019. "A low-carbon economic dispatch model incorporated with consumption-side emission penalty scheme," Applied Energy, Elsevier, vol. 238(C), pages 1084-1092.
    6. Ma, Yiming & Wang, Haixin & Hong, Feng & Yang, Junyou & Chen, Zhe & Cui, Haoqian & Feng, Jiawei, 2021. "Modeling and optimization of combined heat and power with power-to-gas and carbon capture system in integrated energy system," Energy, Elsevier, vol. 236(C).
    7. Yining Zhang & Yubin He & Mingyu Yan & Chuangxin Guo & Yi Ding, 2018. "Linearized Stochastic Scheduling of Interconnected Energy Hubs Considering Integrated Demand Response and Wind Uncertainty," Energies, MDPI, vol. 11(9), pages 1-23, September.
    8. DE WOLF, Daniel & SMEERS, Yves, 2000. "The gas transmission problem solved by an extension of the simplex algorithm," LIDAM Reprints CORE 1489, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Pan, Guangsheng & Gu, Wei & Wu, Zhi & Lu, Yuping & Lu, Shuai, 2019. "Optimal design and operation of multi-energy system with load aggregator considering nodal energy prices," Applied Energy, Elsevier, vol. 239(C), pages 280-295.
    10. Rakipour, Davood & Barati, Hassan, 2019. "Probabilistic optimization in operation of energy hub with participation of renewable energy resources and demand response," Energy, Elsevier, vol. 173(C), pages 384-399.
    11. Huang, Yujing & Wang, Yudong & Liu, Nian, 2022. "A two-stage energy management for heat-electricity integrated energy system considering dynamic pricing of Stackelberg game and operation strategy optimization," Energy, Elsevier, vol. 244(PA).
    12. Li, Yang & Wang, Bin & Yang, Zhen & Li, Jiazheng & Chen, Chen, 2022. "Hierarchical stochastic scheduling of multi-community integrated energy systems in uncertain environments via Stackelberg game," Applied Energy, Elsevier, vol. 308(C).
    13. Daniel De Wolf & Yves Smeers, 2000. "The Gas Transmission Problem Solved by an Extension of the Simplex Algorithm," Management Science, INFORMS, vol. 46(11), pages 1454-1465, November.
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    2. Huang, Yu & Jin, Mingyue & Xie, Jiale & Peng, Yanjian & Zhong, Junjie, 2024. "Dynamic Bayesian game optimization method for multi-energy hub systems with incomplete load information," Energy, Elsevier, vol. 301(C).

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