Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO₂ Capture Using Pilot-Plant Data

This paper is focused on the development and validation of a dynamic model for a monoethanolamine-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 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. Because 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 the dynamic response of CO₂ capture due to step changes in the solvent flow rate, flue gas flow rate, and steam flow rates. 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. Because of 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.