The main limitation of rate-based approach in Aspen Plus is the unavailability of the method under dynamic analysis. Hence, to support the development of the integrated process of natural gas treatment at a higher scale, a comprehensive equilibrium and rate-based simulations of CO2 removal via potassium carbonate promoted with glycine (PCGly) is conducted. The purpose of this study is to observe the efficiency of the equilibrium-based model to represent the CO2 removal system before the dynamic simulation can be developed. The validation is conducted based on published experimental data and the result shows that at steady state, the equilibrium-based method is able to predict the CO2 removal as satisfactorily as the rate-based approach. The error deviation between both methods is 2.11 % and through this study, it is shown that the equilibrium-based method is able to simulate the CO2-PGly system efficiently. Thus, this would enable further investigation of the CO2-PGly system under dynamic simulation using the equilibrium-based method.
Multivariable model predictive control (MMPC) was applied in CO2 removal process in a natural gas treatment from an industry located in Subang field, which used chemical absorption. MMPC is a variation of model predictive control (MPC) which can account for more than one control variable at once and is classified in advanced control category. MMPC is expected to give a better performance in handling the process as well as being able to overcome intervariable interaction that is prone to happen in multiple input multiple output (MIMO) system. MMPC was applied in the process to get a better process control performance compared to the one using PI controller and to make any intervariable interaction in the process more manageable. The indicator for each goal was integral square error (ISE). The result showed that identified intervariable interaction was between the pressure of gas feed in and the flow of make-up water to absorber. By using MMPC, the ISE of controller’s performance was improved from the PI-controller that was used in the plant. The improvement for ISE was 32.62% (PIC-1101) and 72.67% (FIC-1102) in the SP tracking, and 52.54% (PIC-1101) and 57.41% (FIC-1102) in the disturbance rejection. MMPC implementation also showed a better response in handling intervariable interaction in the process.
The polycrystalline CHA-type zeolite layer with Si/Al = 18 was formed on the porous α-Al2O3 tube in this study, and the gas permeation properties were determined using single-component H2, CO2, N2, CH4, n-C4H10, and SF6 at 303–473 K. The membrane showed permeation behavior, wherein the permeance reduced with the molecular size, attributed to the effect of molecular sieving. The separation performances were also determined using the equimolar mixtures of N2–SF6, CO2–N2, and CO2–CH4. As a result, the N2/SF6 and CO2/CH4 selectivities were as high as 710 and 240, respectively. However, the CO2/N2 selectivity was only 25. These results propose that the high-silica CHA-type zeolite membrane is suitable for the separation of CO2 from CH4 by the effect of molecular sieving.
Gas Separation Process for CO2 Removal from Natural Gas with DDR-type Zeolite Membrane