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Title: Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO 2 Capture Using Pilot-Plant Data

Abstract

This paper is focused on the development and validation of a dynamic model for an MEA-based CO2 capture unit. Starting with a rigorous steady-state process model, the dynamic model is developed in Aspen Plus Dynamics® using a modified Murphree-efficiency approach and is validated using dynamic data collected from the National Carbon Capture Center (NCCC) in Wilsonville, Alabama. The dynamic test runs were designed with due consideration of process excitation and process nonlinearities constrained by the available time to conduct the test runs and implement the experimental designs in the plant control system. The experimental data include solvent composition and loading. Since the experimental data were found to violate mass and energy balances, filtering algorithms coupled with dynamic data reconciliation techniques were used. Without adjusting any model parameters, the dynamic model satisfactorily predicted dynamic response of CO2 capture due to step changes in the solvent flowrate, flue gas flowrate, and steam flowrates. Transient studies show that the process gain and time constants can considerably change depending on the direction of the disturbance or manipulated variables, indicating process nonlinearities. Due to a storage tank between the absorber and stripper, the time constant of the full plant can be considerably longer than themore » time constants of the absorber or stripper individually. Furthermore, impact of the control system on the process efficiency while following an optimal CO2 capture schedule was also studied.« less

Authors:
 [1];  [2];  [3]; ORCiD logo [4];  [3]
+ Show Author Affiliations
  1. West Virginia Univ., Morgantown, WV (United States). Dept. of Chemical and Biomedical Engineering; National Energy Technology Lab. (NETL), Morgantown, WV (United States)
  2. West Virginia Univ., Morgantown, WV (United States). Dept. of Chemical and Biomedical Engineering; National Energy Technology Lab. (NETL), Pittsburgh, PA, (United States)
  3. National Energy Technology Lab. (NETL), Pittsburgh, PA, (United States)
  4. West Virginia Univ., Morgantown, WV (United States). Dept. of Chemical and Biomedical Engineering
Publication Date:
Research Org.:
National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)
Sponsoring Org.:
USDOE Office of Fossil Energy (FE)
OSTI Identifier:
1532533
Resource Type:
Accepted Manuscript
Journal Name:
Industrial and Engineering Chemistry Research
Additional Journal Information:
Journal Volume: 58; Journal Issue: 5; Journal ID: ISSN 0888-5885
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Chinen, Anderson Soares, Morgan, Joshua C., Omell, Benjamin, Bhattacharyya, Debangsu, and Miller, David C. Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO 2 Capture Using Pilot-Plant Data. United States: N. p., 2019. Web. doi:10.1021/acs.iecr.8b04489.
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Chinen, Anderson Soares, Morgan, Joshua C., Omell, Benjamin, Bhattacharyya, Debangsu, & Miller, David C. Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO 2 Capture Using Pilot-Plant Data. United States. https://doi.org/10.1021/acs.iecr.8b04489
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Chinen, Anderson Soares, Morgan, Joshua C., Omell, Benjamin, Bhattacharyya, Debangsu, and Miller, David C. Wed . "Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO 2 Capture Using Pilot-Plant Data". United States. https://doi.org/10.1021/acs.iecr.8b04489. https://www.osti.gov/servlets/purl/1532533.
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@article{osti_1532533,
title = {Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO 2 Capture Using Pilot-Plant Data},
author = {Chinen, Anderson Soares and Morgan, Joshua C. and Omell, Benjamin and Bhattacharyya, Debangsu and Miller, David C.},
abstractNote = {This paper is focused on the development and validation of a dynamic model for an MEA-based CO2 capture unit. Starting with a rigorous steady-state process model, the dynamic model is developed in Aspen Plus Dynamics® using a modified Murphree-efficiency approach and is validated using dynamic data collected from the National Carbon Capture Center (NCCC) in Wilsonville, Alabama. The dynamic test runs were designed with due consideration of process excitation and process nonlinearities constrained by the available time to conduct the test runs and implement the experimental designs in the plant control system. The experimental data include solvent composition and loading. Since the experimental data were found to violate mass and energy balances, filtering algorithms coupled with dynamic data reconciliation techniques were used. Without adjusting any model parameters, the dynamic model satisfactorily predicted dynamic response of CO2 capture due to step changes in the solvent flowrate, flue gas flowrate, and steam flowrates. Transient studies show that the process gain and time constants can considerably change depending on the direction of the disturbance or manipulated variables, indicating process nonlinearities. Due to a storage tank between the absorber and stripper, the time constant of the full plant can be considerably longer than the time constants of the absorber or stripper individually. Furthermore, impact of the control system on the process efficiency while following an optimal CO2 capture schedule was also studied.},
doi = {10.1021/acs.iecr.8b04489},
journal = {Industrial and Engineering Chemistry Research},
number = 5,
volume = 58,
place = {United States},
year = {2019},
month = {1}
}
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https://doi.org/10.1021/acs.iecr.8b04489
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    Works referencing / citing this record:

    Control of Solvent-Based Post-Combustion Carbon Capture Process with Optimal Operation Conditions
    journal, June 2019

    • Chen, Yih-Hang; Shen, Ming-Tien; Chang, Hsuan
    • Processes, Vol. 7, Issue 6
    • DOI: 10.3390/pr7060366
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