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Kinetic prediction study of carbon capture pretreatment system driven by mechanism and data fusion
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Yuanyuan CHEN1, 2, Yueyue JIANG3, Quanzhi JIN3, Yin ZHANG2, Qirong WU1, 4
Thermal Power Generation | 2026, 55(6) : 115 - 124
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Thermal Power Generation | 2026, 55(6): 115-124
• Thermal energy science research •
Kinetic prediction study of carbon capture pretreatment system driven by mechanism and data fusion
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Yuanyuan CHEN1, 2, Yueyue JIANG3, Quanzhi JIN3, Yin ZHANG2, Qirong WU1, 4
Affiliations
  • 1.College of Smart Energy, Shanghai Jiao Tong University, Shanghai 200240, China
  • 2.Shanghai Electric Power Company Limited, Shanghai 200126, China
  • 3.Shanghai Minghua Electric Power Science & Technology Co., Ltd., Shanghai 200090, China
  • 4.Technology Branch of Chongqing Yuanda Flue Gas Control Franchise Co., Ltd., Chongqing 401122, China
Published: 2026-06-25 doi: 10.19666/j.rlfd.202509037
Outline
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[Objective]

The carbon capture pretreatment system faces challenges such as high energy consumption, unstable purification efficiency, and significant fluctuations in SO2 absorption efficiency due to variations in pH value of washing solution. This study proposes a hybrid modeling method combining mechanism models with data-driven by taking the carbon capture pretreatment system in a power plant as the research object.

[Methods]

By integrating chemical reaction kinetics and decision tree algorithms, the model is implemented in Python to predict key parameters accurately, including the pH value of the washing solution and the SO2 mass concentration at the system outlet.

[Results]

The model yields a correlation coefficient of 0.85 and 0.80 for the pH value of the washing solution and the SO2 mass concentration at the system outlet, respectively. The values fall within an acceptable error band, indicating the proposed model has good simulation performance. Moreover, a sensitivity analysis driven by baseline plant data further reveals that the model faithfully reproduces the system response to perturbations in inlet flue-gas temperature, liquid-to-gas ratio, and alkali feed rate.

[Conclusion]

These outcomes furnish a quantitative foundation for subsequent optimization of the CO2-capture pretreatment system, offering clear avenues for energy minimization and robust steady-state operation.

carbon capture  /  flue gas pretreatment  /  mechanism modeling  /  data-driven  /  pH value prediction
Yuanyuan CHEN, Yueyue JIANG, Quanzhi JIN, Yin ZHANG, Qirong WU. Kinetic prediction study of carbon capture pretreatment system driven by mechanism and data fusion[J]. Thermal Power Generation, 2026 , 55 (6) : 115 -124 . DOI: 10.19666/j.rlfd.202509037
Funding
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  • National Key Research and Development Program(2024YFB4106404)
  • Shanghai Major Science and Technology Projects(BH0200090)
Appendix
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Year 2026 volume 55 Issue 6
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Article Info
doi: 10.19666/j.rlfd.202509037
  • Receive Date：2025-09-13
  • Online Date：2026-08-14
  • Published：2026-06-25
Article Data
Affiliations
History
  • Received：2025-09-13
  • Revised：2025-10-19
  • Accepted：2025-11-18
Funding
National Key Research and Development Program(2024YFB4106404)
Shanghai Major Science and Technology Projects(BH0200090)
Affiliations
    1.College of Smart Energy, Shanghai Jiao Tong University, Shanghai 200240, China
    2.Shanghai Electric Power Company Limited, Shanghai 200126, China
    3.Shanghai Minghua Electric Power Science & Technology Co., Ltd., Shanghai 200090, China
    4.Technology Branch of Chongqing Yuanda Flue Gas Control Franchise Co., Ltd., Chongqing 401122, China
References
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https://castjournals.cast.org.cn/joweb/rlfd/EN/10.19666/j.rlfd.202509037
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