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

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...

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Veröffentlicht in:Industrial & engineering chemistry research 2019-02, Vol.58 (5), p.1978-1993
Hauptverfasser: Chinen, Anderson Soares, Morgan, Joshua C., Omell, Benjamin, Bhattacharyya, Debangsu, Miller, David C.
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container_end_page 1993
container_issue 5
container_start_page 1978
container_title Industrial & engineering chemistry research
container_volume 58
creator Chinen, Anderson Soares
Morgan, Joshua C.
Omell, Benjamin
Bhattacharyya, Debangsu
Miller, David C.
description 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_str_mv 10.1021/acs.iecr.8b04489
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title Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO 2 Capture Using Pilot-Plant Data
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