IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2021i1p141-d711419.html
   My bibliography  Save this article

Steam-Water Modelling and the Coal-Saving Scheduling Strategy of Combined Heat and Power Systems

Author

Listed:
  • Junshan Guo

    (Zhongshi Yitong Group, Jinan 250003, China
    State Grid Shandong Electric Power Research Institute, Jinan 250003, China)

  • Wei Zheng

    (State Grid Shandong Electric Power Research Institute, Jinan 250003, China)

  • Zhuang Cong

    (Zhongshi Yitong Group, Jinan 250003, China)

  • Panfeng Shang

    (State Grid Shandong Electric Power Research Institute, Jinan 250003, China)

  • Congyu Wang

    (Institute of Thermal Science and Technology, Shandong University, Jinan 250061, China)

  • Jiwei Song

    (Institute of Thermal Science and Technology, Shandong University, Jinan 250061, China)

Abstract

China aims to peak carbon emissions by 2030. As a result, small-scale coal-fired combined heat and power (CHP) units and self-provided units are gradually shut down, and large-scale coal-fired CHP units are a solution to undertake the industrial heat loads. From the perspective of the industrial heat load allocation during the non-heating season, the problems regarding the coal-saving scheduling strategy of coal-fired CHP units are addressed. The steam-water equations of CHP units are established to analyze the heat-power coupling characteristics. The energy utilization efficiency, exergy efficiency and the coal consumption are analyzed. The optimization model of saving coal consumption is established and the adaptive mutation particle swarm optimization (AMPSO) is introduced to solve the above model. The 330 MW coal-fired CHP unit is taken as an example, and the results show that for the constant main flow rate, each increase of 1 t/h industrial steam extraction will reduce the power output by about 0.321 MW. The energy utilization efficiency and the exergy are mainly influenced by industrial steam supply and the power load, respectively. For the CHP system with two parallel CHP units, the unequal allocation of industrial heat load between two units saves more coal than equal allocation. The coal consumption can be reduced when the unit with lower power load undertakes more industrial heat load. In the typical day, the total coal consumption after optimization is 3203.92 tons, a decrease of 14.66 tons compared to the optimization before. The two CHP units in the case can benefit about 5,612,700 CHY extra in one year.

Suggested Citation

  • Junshan Guo & Wei Zheng & Zhuang Cong & Panfeng Shang & Congyu Wang & Jiwei Song, 2021. "Steam-Water Modelling and the Coal-Saving Scheduling Strategy of Combined Heat and Power Systems," Energies, MDPI, vol. 15(1), pages 1-16, December.
    • Handle: RePEc:gam:jeners:v:15:y:2021:i:1:p:141-:d:711419
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/1/141/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/1/141/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liu, Ming & Ma, Guofeng & Wang, Shan & Wang, Yu & Yan, Junjie, 2021. "Thermo-economic comparison of heat–power decoupling technologies for combined heat and power plants when participating in a power-balancing service in an energy hub," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    2. Liu, Ming & Wang, Shan & Zhao, Yongliang & Tang, Haiyu & Yan, Junjie, 2019. "Heat–power decoupling technologies for coal-fired CHP plants: Operation flexibility and thermodynamic performance," Energy, Elsevier, vol. 188(C).
    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. Zhang, Youjun & Hao, Junhong & Ge, Zhihua & Zhang, Fuxiang & Du, Xiaoze, 2021. "Optimal clean heating mode of the integrated electricity and heat energy system considering the comprehensive energy-carbon price," Energy, Elsevier, vol. 231(C).
    2. Li, Xin & Wu, Xian & Gui, De & Hua, Yawen & Guo, Panfeng, 2021. "Power system planning based on CSP-CHP system to integrate variable renewable energy," Energy, Elsevier, vol. 232(C).
    3. Liu, Miaomiao & Liu, Ming & Chen, Weixiong & Yan, Junjie, 2023. "Operational flexibility and operation optimization of CHP units supplying electricity and two-pressure steam," Energy, Elsevier, vol. 263(PE).
    4. Haoran Ju & Yongxue Wang & Yiwu Feng & Lijun Zheng, 2024. "Numerical Study on Peak Shaving Performance of Combined Heat and Power Unit Assisted by Heating Storage in Long-Distance Pipelines Scheduled by Particle Swarm Optimization Method," Energies, MDPI, vol. 17(2), pages 1-18, January.
    5. Zhao, Pan & Gou, Feifei & Xu, Wenpan & Shi, Honghui & Wang, Jiangfeng, 2023. "Energy, exergy, economic and environmental (4E) analyses of an integrated system based on CH-CAES and electrical boiler for wind power penetration and CHP unit heat-power decoupling in wind enrichment," Energy, Elsevier, vol. 263(PC).
    6. Yang, Lijun & Jiang, Yaning & Chong, Zhenxiao, 2023. "Optimal scheduling of electro-thermal system considering refined demand response and source-load-storage cooperative hydrogen production," Renewable Energy, Elsevier, vol. 215(C).
    7. Hou, Guolian & Gong, Linjuan & Hu, Bo & Huang, Ting & Su, Huilin & Huang, Congzhi & Zhou, Guiping & Wang, Shunjiang, 2022. "Flexibility oriented adaptive modeling of combined heat and power plant under various heat-power coupling conditions," Energy, Elsevier, vol. 242(C).
    8. Wang, Di & Liu, Deying & Wang, Chaonan & Zhou, Yunlong & Li, Xiaoli & Yang, Mei, 2022. "Flexibility improvement method of coal-fired thermal power plant based on the multi-scale utilization of steam turbine energy storage," Energy, Elsevier, vol. 239(PD).
    9. Ding, Zeyu & Hou, Hongjuan & Duan, Liqiang & Huang, Chang & Hu, Eric & Yu, Gang & Zhang, Yumeng & Zhang, Nan, 2021. "Simulation study on a novel solar aided combined heat and power system for heat-power decoupling," Energy, Elsevier, vol. 220(C).
    10. Hou, Guolian & Huang, Ting & Zheng, Fumeng & Gong, Linjuan & Huang, Congzhi & Zhang, Jianhua, 2023. "Application of multi-agent EADRC in flexible operation of combined heat and power plant considering carbon emission and economy," Energy, Elsevier, vol. 263(PB).
    11. Bloess, Andreas, 2020. "Modeling of combined heat and power generation in the context of increasing renewable energy penetration," Applied Energy, Elsevier, vol. 267(C).
    12. Lingkai Zhu & Chengkun Lin & Congyu Wang & Jiwei Song, 2022. "Optimal Dispatch of Multi-Type CHP Units Integrated with Flexibility Renovations for Renewable Energy Accommodation," Energies, MDPI, vol. 15(19), pages 1-16, September.
    13. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Lin, Zhongwei & Fang, Fang & Chen, Qun, 2021. "Optimal operation of integrated electricity and heat system: A review of modeling and solution methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    14. Cao, Lihua & Wang, Zhanzhou & Pan, Tongyang & Dong, Enfu & Hu, Pengfei & Liu, Miao & Ma, Tingshan, 2021. "Analysis on wind power accommodation ability and coal consumption of heat–power decoupling technologies for CHP units," Energy, Elsevier, vol. 231(C).
    15. Yanjuan Yu & Guohua Zhou & Kena Wu & Cheng Chen & Qiang Bian, 2023. "Optimal Configuration of Power-to-Heat Equipment Considering Peak-Shaving Ancillary Service Market," Energies, MDPI, vol. 16(19), pages 1-18, September.
    16. Wang, Haichao & Hua, Pengmin & Wu, Xiaozhou & Zhang, Ruoyu & Granlund, Katja & Li, Ji & Zhu, Yingjie & Lahdelma, Risto & Teppo, Esa & Yu, Li, 2022. "Heat-power decoupling and energy saving of the CHP unit with heat pump based waste heat recovery system," Energy, Elsevier, vol. 250(C).
    17. Liu, Ming & Ma, Guofeng & Wang, Shan & Wang, Yu & Yan, Junjie, 2021. "Thermo-economic comparison of heat–power decoupling technologies for combined heat and power plants when participating in a power-balancing service in an energy hub," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    18. Coppitters, Diederik & De Paepe, Ward & Contino, Francesco, 2021. "Robust design optimization of a photovoltaic-battery-heat pump system with thermal storage under aleatory and epistemic uncertainty," Energy, Elsevier, vol. 229(C).
    19. Guo, Zheyu & Zheng, Yanan & Li, Gengyin, 2020. "Power system flexibility quantitative evaluation based on improved universal generating function method: A case study of Zhangjiakou," Energy, Elsevier, vol. 205(C).
    20. Ghasemi-Marzbali, Ali & Shafiei, Mohammad & Ahmadiahangar, Roya, 2023. "Day-ahead economical planning of multi-vector energy district considering demand response program," Applied Energy, Elsevier, vol. 332(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:15:y:2021:i:1:p:141-:d:711419. 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.