IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i8p1902-d1376930.html
   My bibliography  Save this article

Optimal Scheduling of Integrated Energy System Considering Hydrogen Blending Gas and Demand Response

Author

Listed:
  • Zijie Zheng

    (Faculty of Electrical Engineering, Xinjiang University, Urumqi 830000, China)

  • Abuduwayiti Xiwang

    (Faculty of Electrical Engineering, Xinjiang University, Urumqi 830000, China)

  • Yufeng Sun

    (Faculty of Electrical Engineering, Xinjiang University, Urumqi 830000, China)

Abstract

In the context of carbon neutrality and carbon peaking, in order to achieve low carbon emissions and promote the efficient utilization of wind energy, hydrogen energy as an important energy carrier is proposed to mix hydrogen and natural gas to form hydrogen-enriched compressed natural gas (HCNG). It is also injected into the natural gas pipeline network to achieve the transmission and utilization of hydrogen energy. At the same time, the participation of demand response is considered, the load’s peak and trough periods are adjusted, and the large-scale consumption of renewable energy and the reduction in carbon emissions are achieved. First of all, a fine model of hydrogen production and hydrogen use equipment is established to analyze the impact of adding hydrogen mixing on the economy and the low-carbon property of the system. With green certificates and demand response, the utilization rate of hydrogen energy is improved to further explore the energy utilization rate and emission reduction capacity of the system. Secondly, on the basis of modeling, the optimal scheduling strategy is proposed with the sum of energy purchase cost, equipment operation cost, carbon emission cost, wind curtailment cost, and green certificate income as the lowest objective function. Considering the constraints such as hydrogen blending ratio and flexible load ratio of the pipeline network, a low-carbon economic scheduling model of hydrogen mixed natural gas was established. The model was linearized and solved by using MATLAB 2021a and CPLEX solver. By comparing different scenarios, the superiority of the model and the effectiveness of the strategy are verified.

Suggested Citation

  • Zijie Zheng & Abuduwayiti Xiwang & Yufeng Sun, 2024. "Optimal Scheduling of Integrated Energy System Considering Hydrogen Blending Gas and Demand Response," Energies, MDPI, vol. 17(8), pages 1-17, April.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:8:p:1902-:d:1376930
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/8/1902/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/8/1902/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Jianhui & Mao, Jiangwei & Hao, Ruhai & Li, Shoudong & Bao, Guangqing, 2022. "Multi-energy coupling analysis and optimal scheduling of regional integrated energy system," Energy, Elsevier, vol. 254(PC).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sharma, Abhimanyu & Padhy, Narayana Prasad, 2024. "Iterative convex relaxation of unbalanced power distribution system integrated multi-energy systems," Energy, Elsevier, vol. 294(C).
    2. Wu, Yanjuan & Wang, Caiwei & Wang, Yunliang, 2024. "Cooperative game optimization scheduling of multi-region integrated energy system based on ADMM algorithm," Energy, Elsevier, vol. 302(C).
    3. Chen, Maozhi & Lu, Hao & Chang, Xiqiang & Liao, Haiyan, 2023. "An optimization on an integrated energy system of combined heat and power, carbon capture system and power to gas by considering flexible load," Energy, Elsevier, vol. 273(C).
    4. Wang, Xuan & Wang, Shouxiang & Zhao, Qianyu, 2024. "Low-carbon economic scheduling of multi-energy system based on price interactive response," Energy, Elsevier, vol. 300(C).
    5. Pan, Chongchao & Jin, Tai & Li, Na & Wang, Guanxiong & Hou, Xiaowang & Gu, Yueqing, 2023. "Multi-objective and two-stage optimization study of integrated energy systems considering P2G and integrated demand responses," Energy, Elsevier, vol. 270(C).
    6. Hou, Hui & Ge, Xiangdi & Yan, Yulin & Lu, Yanchao & Zhang, Ji & Dong, Zhao Yang, 2024. "An integrated energy system “green-carbon” offset mechanism and optimization method with Stackelberg game," Energy, Elsevier, vol. 294(C).
    7. Chen, Zhiwei & Zhao, Weicheng & Lin, Xiaoyong & Han, Yongming & Hu, Xuan & Yuan, Kui & Geng, Zhiqiang, 2024. "Load prediction of integrated energy systems for energy saving and carbon emission based on novel multi-scale fusion convolutional neural network," Energy, Elsevier, vol. 290(C).
    8. Wu, Qunli & Li, Chunxiang, 2023. "Modeling and operation optimization of hydrogen-based integrated energy system with refined power-to-gas and carbon-capture-storage technologies under carbon trading," Energy, Elsevier, vol. 270(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:8:p:1902-:d:1376930. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.