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Flexibility oriented adaptive modeling of combined heat and power plant under various heat-power coupling conditions

Author

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  • Hou, Guolian
  • Gong, Linjuan
  • Hu, Bo
  • Huang, Ting
  • Su, Huilin
  • Huang, Congzhi
  • Zhou, Guiping
  • Wang, Shunjiang

Abstract

The flexible operation of thermal power plant has become a research hotspot for its safety and validity in eliminating power grid fluctuation from large-scale integration of renewable energy. Heat-power decoupling is effective technique to promote flexibility of combined heat and power plant. To address the insufficient dynamics investigation of combined heat and power plant under different heat-power decoupling strategies, an adaptive modeling approach is proposed. This method systematically fuses the mechanism analysis and data-driven fuzzy modeling to prepare for the controller design for rapid and deep load regulation in flexible operation. Firstly, the model structures with unknown parameters are determined by mechanism analyses to reflect the effects of various decoupling techniques on the characteristics of plant. Secondly, in view of the on-site data under wide load operation conditions, corresponding model structure is adaptively matched, and a new Takagi–Sugeno fuzzy modeling scheme depend on biquantum pigeon optimization algorithm is constructed for model parameters acquisition. The effectiveness of the proposed approach is illustrated based on a 350 MW supercritical combined heat and power unit. Simulation results illustrate that the adopted method can rapidly characterize dynamics of plant under different heat-power coupling conditions. All the model identification and verification errors in wide load operation conditions are less than 3.1% plant output, which reveals high modeling precision more than 97%. Thus, the established model provides solid foundation on highly matched controller for ensuring operational flexibility.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:242:y:2022:i:c:s036054422102778x
    DOI: 10.1016/j.energy.2021.122529
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    References listed on IDEAS

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    Cited by:

    1. Wang, Congyu & Song, Jiwei, 2023. "Performance assessment of the novel coal-fired combined heat and power plant integrating with flexibility renovations," Energy, Elsevier, vol. 263(PC).
    2. 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).
    3. Hou, Guolian & Huang, Ting & Huang, Congzhi, 2023. "Flexibility improvement of 1000 MW ultra-supercritical unit under full operating conditions by error-based ADRC and fast pigeon-inspired optimizer," Energy, Elsevier, vol. 270(C).
    4. Hou, Guolian & Huang, Ting & Jiang, Hao & Cao, Huan & Zhang, Tianhao & Zhang, Jianhua & Gao, He & Liu, Yong & Zhou, Zhenhua & An, Zhenyi, 2024. "A flexible and deep peak shaving scheme for combined heat and power plant under full operating conditions," Energy, Elsevier, vol. 299(C).
    5. Jiakui Shi & Shuangshuang Fan & Jiajia Li & Jiangnan Cheng & Jie Wan & Peng E, 2023. "An Optimization Method of Steam Turbine Load Resilient Adjustment by Characterizing Dynamic Changes in Superheated Steam Energy," Energies, MDPI, vol. 16(8), pages 1-15, April.
    6. Huang, Congzhi & Li, Zhuoyong, 2023. "Data-driven modeling of ultra-supercritical unit coordinated control system by improved transformer network," Energy, Elsevier, vol. 266(C).

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