(398k) CO2 Capture Process Dynamic Design of Experiments and Model Validation

With growing global CO₂ release per year to the atmosphere^[1], it is critical that CO₂ capture technologies be developed and deployed rapidly. The U.S. Department of Energy’s Carbon Capture Simulation Initiative (CCSI) recently developed a suite of advanced computational tools and models to accelerate the development and commercialization of CO₂ capture technologies. As part of CCSI, high-fidelity process models were developed to serve as a “gold-standard” reference for benchmarking solvent-based CO₂ capture processes^[2]. Rigorous thermodynamic^[3] and transport models^[4] for MEA-H₂O-CO₂ systems have been developed. In addition, a rigorous mass transfer model was developed by simultaneously estimating the parameters for the interfacial area, reaction kinetics, mass transfer coefficients and diffusivity models by concurrently using the data from wetted wall column and packed column experiments. The resulting submodels were integrated into a steady-state “gold-standard” model in Aspen Plus and was validated with pilot plant data from U.S. DOE’s National Carbon Capture Center (NCCC). Since Aspen Plus rate-based models cannot be currently exported to Aspen Plus Dynamics, a Murphree efficiencies model was developed to incorporate results from the rigorous, rate-based, steady-state model and enable satisfactory results in the Aspen Plus Dynamics platform. Hydraulics correlations previously developed by the authors were also implemented in Aspen Plus Dynamics to obtain more accurate time constants.

Dynamic test runs were also conducted at NCCC so that information about process nonlinearities could be obtained while ensuring persistence of excitation. In addition to the transient data available from the plant control system, liquid samples are analyzed every 15 min, resulting in a rich set of transient data spanning several days. A dynamic data reconciliation problem is solved to reconcile the mass and energy balances with plant data and to estimate the missing measurements. The dynamic model is found to satisfactorly predict transient behavior and is used to investigate the transient behavior of the process. The resulting model can further be used for developing an advanced control system and can offer valuable insights in the CO₂ capture behavior during plant disturbances or failures.

References

1. Global Carbon Project. Carbon budget and trends, 2016. Available at [www.globalcarbonproject.org/carbonbudget]
2. Miller, D. C., Syamlal, M., Mebane, D. S., Storlie, C., Bhattacharyya, D., Sahinidis, N. V., Sun, X. Carbon capture simulation initiative: a case study in multiscale modeling and new challenges. Annual review of chemical and biomolecular engineering 2014, 5, 301-323,.
3. Morgan, J. C., Chinen, A. S., Omell, B., Bhattacharyya, D., Tong, C., Miller, D.C. Thermodynamic Modeling and Uncertainty Quantification of CO₂-Loaded Aqueous MEA Solutions. Chemical Engineering Science 2017, (submitted).
4. Morgan, J. C., Bhattacharyya, D., Tong, C., Miller, D.C. Uncertainty Quantification of Property Models: Methodology and Its Application to CO₂-Loaded Aqueous MEA Solutions. AIChE Journal 2015. 61, 1822-1839.