Parameter estimation and optimization of a PSA process for CO2 capture

The pressure swing adsorption (PSA) process is one of the potentially viable options for CO₂ capture from large CO₂ generating sources. The operating cost of a PSA process for CO₂ capture is mostly contributed by the operation of blowers and vacuum pumps. Hence, how to reduce the operation cost of blowers and vacuum pumps is an important issue in the concerned PSA process. The aim of this research is placed in the auditing the economy of the two-stage PSA process for CO₂ capture using zeolite 13X as adsorbent through numerical simulation and optimization. The performance curves of commercial vacuum pumps were used for realistic calculation of the operating cost. In addition, a new mass transfer model was proposed to represent the adsorption behavior on an energetically heterogeneous surface, and the coefficients of the rate model were estimated through experiments. For numerically stable calculation, a novel numerical procedure using gradient-directed adaptive predictive collocation with a cubic spline interpolation function and far-side boundary conditions were adopted. First, effects of the process variables such as the P/F ratio, desorption pressure, bed utilization factors, and so forth on the operating cost and CO₂ recovery were investigated to select the decision variables for optimization. Then, the economy of the PSA process was evaluated for the optimized process conditions as a function of CO₂ contents of the inlet flue gas and CO₂ recovery rate.