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Model calibration for the carbon dioxide-amine absorption system

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  • Errico, Massimiliano
  • Madeddu, Claudio
  • Pinna, Daniele
  • Baratti, Roberto

Abstract

Carbon dioxide absorption by monoethanolamine (MEA) is a very extensively studied process and its modeling represents an open issue in the specialized literature. In the present work, the key parameters necessary to set the absorber model are discussed and evaluated based on rigorous analysis. The experimental data from two different absorption plants size were considered to validate the model. The material and the thermal Peclet number were evaluated for both plants in order to quantify the influence of the axial diffusion/dispersion. The results obtained from the Peclet number evaluation were used to correctly define the number of segments required in the rate-based model. Moreover, the uncertainty in the kinetic parameters associated to the reaction between MEA and CO2 reaction was examined to define a new set of values that minimize the standard error between the experimental and predicted temperature and composition values. The model proposed describes correctly the experimental data and particularly the bulge in the temperature profile, independently on its location. This result is particularly significant when it is required to examine the dynamic behavior of the column or when it is necessary to set an appropriate control system.

Suggested Citation

  • Errico, Massimiliano & Madeddu, Claudio & Pinna, Daniele & Baratti, Roberto, 2016. "Model calibration for the carbon dioxide-amine absorption system," Applied Energy, Elsevier, vol. 183(C), pages 958-968.
    • Handle: RePEc:eee:appene:v:183:y:2016:i:c:p:958-968
    DOI: 10.1016/j.apenergy.2016.09.036
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    References listed on IDEAS

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    1. Li, Bao-Hong & Zhang, Nan & Smith, Robin, 2016. "Simulation and analysis of CO2 capture process with aqueous monoethanolamine solution," Applied Energy, Elsevier, vol. 161(C), pages 707-717.
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    4. Sipöcz, Nikolett & Tobiesen, Finn Andrew & Assadi, Mohsen, 2011. "The use of Artificial Neural Network models for CO2 capture plants," Applied Energy, Elsevier, vol. 88(7), pages 2368-2376, July.
    5. Kang, Charles A. & Brandt, Adam R. & Durlofsky, Louis J. & Jayaweera, Indira, 2016. "Assessment of advanced solvent-based post-combustion CO2 capture processes using a bi-objective optimization technique," Applied Energy, Elsevier, vol. 179(C), pages 1209-1219.
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    Cited by:

    1. Zhu, Chuanqi & Tian, Wei & Yin, Baoquan & Li, Zhanyong & Shi, Jiaxin, 2020. "Uncertainty calibration of building energy models by combining approximate Bayesian computation and machine learning algorithms," Applied Energy, Elsevier, vol. 268(C).
    2. Putta, Koteswara Rao & Tobiesen, Finn Andrew & Svendsen, Hallvard F. & Knuutila, Hanna K., 2017. "Applicability of enhancement factor models for CO2 absorption into aqueous MEA solutions," Applied Energy, Elsevier, vol. 206(C), pages 765-783.
    3. Madeddu, Claudio & Errico, Massimiliano & Baratti, Roberto, 2018. "Process analysis for the carbon dioxide chemical absorption–regeneration system," Applied Energy, Elsevier, vol. 215(C), pages 532-542.

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