Dynamic Modeling and Analysis of Amine-based Carbon Capture Systems

Abstract

Carbon capture technologies are studied widely to curb the rising trend in the atmospheric concentration of CO2 causing global warming. The post-combustion carbon capture technology using amine solvents is one of the mature technologies that can be deployed to existing power plants. Chemical absorption based on an amine solvent has a fast reaction rate with a high capacity to capture CO2. However, a large amount of energy is needed to regenerate the CO2 rich solvent after the absorption. Flexible operation with a properly chosen control structure is a way to alleviate this problem and developing a simple, yet accurate dynamic model is a key to finding stable operation conditions while maximizing the flexibility of the process. In this research, chemical absorption process based on the most widely used amine solvent, monoethanolamine (MEA), is developed using the commercial software of gPROMS. The Kent-Eisenberg model and a rigorous rate-based approach are used to develop a dynamic column model. The process model is simulated and the results are compared with experimental data in the literature. The developed model is consistent with the experimental data within about 10% error. The model was used to compare two control strategies. As a result, the control strategy that control CO2 capture with the lean solvent flow showed faster settling time than with the regeneration heat.