(257b) CO2 Capture From Post-Combustion Flue Gas On a Carbon Molecular Sieve | AIChE

(257b) CO2 Capture From Post-Combustion Flue Gas On a Carbon Molecular Sieve

Authors 

Haghpanah, R. - Presenter, Nanyang Technological University
Rajendran, A. - Presenter, Nanyang Technological University


In the past decade, a general consensus that global warming is real and there is a close correspondence between the increase in atmospheric CO2 and the global climate change has been reached. Carbon dioxide capture and sequestration is now considered a  potential solution for mitigating climate change. Power plants that use fossil fuels contribute to a significant percentage of  global CO2 emissions. Further, the majority of existing power plants employ post-combustion technology, where the fossil fuel is burnt in the presence of air. The flue gas from these plants consists of predominantly N2 and CO2 saturated in moisture. The goal is to separate and concentrate CO2 from this mixture for sequestration.

In this study, we systematically evaluate the possibility of kinetically controlled Vacuum Swing Adsorption (VSA) CO2/N2 separation on CMS. The idea of using CMS as an adsorbent stems from the relative insensitivity of the adsorbent for moisture - an important consideration that can limit the performance of classical adsorbents such as zeolites. The effect of moisture  will be addressed in the next stage and the idea of kinetic separation is first tested with dry gas to make a preliminary evaluation of the process performance.

Single component isotherms of N2 and CO2 have been measured in our laboratories both volumetrically and gravimetrically. Mixture equilibrium and kinetics have also been measured in CMS and appropriate predictive models have been verified. These data have been incorporated into a rigorous process simulation model that is flexible to capture various modes of operation of VSA processes. The various process configurations are compared and evaluated by considering the effect of design parameters on their performance.

In order to reduce the time required for a rigorous optimization, a fuzzy logic based model is developed to characterize the effect of various process variables on the performance indicators. In the optimization problem, the duration of the steps and the corresponding pressures have been be defined as decision variables. The following two cases have been investigated:

Case 1.  Maximization of CO2 purity and recovery simultaneously.

Case 2. Maximization of CO2 productivity and minimization of energy consumption with purity and recovery being constraints.

The two case studies demonstrate that the while the kinetic VSA shows modest productivity, it has the capability to produce very high purity CO2 at high recovery making it an option for further consideration. The results of these studies will be presented at the meeting.

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