CO2 Removal via an Environmental Green Solvent, K2CO3-Glycine (PCGLY): Investigative Analysis of a Dynamic and Control Study

Faezah Isa; Haslinda Zabiri; Noorlisa Harun; Azmi M Shariff

doi:10.1021/acsomega.1c06254

CO₂ Removal via an Environmental Green Solvent, K₂CO₃-Glycine (PCGLY): Investigative Analysis of a Dynamic and Control Study

ACS Omega. 2022 May 26;7(22):18213-18228. doi: 10.1021/acsomega.1c06254. eCollection 2022 Jun 7.

Authors

Faezah Isa¹, Haslinda Zabiri¹, Noorlisa Harun², Azmi M Shariff¹

Affiliations

¹ CO2 Research center (CO2RES), Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia.
² Faculty of Chemical and Natural Resources Engineering, Universiti Malaysia Pahang, Kuantan 26300, Malaysia.

Abstract

Promoted potassium carbonate with glycine has been actively investigated as a chemical solvent for the removal of CO₂. Though a vast number of studies have been reported for potassium carbonate, dynamic studies regarding this promoted solvent are not yet extensively reported in the literature. In this work, a steady-state simulation has been performed via an equilibrium stage model in Aspen Plus V10 using the experimental data of an absorber from the bench scale pilot plant (MINI CHAS) located in Universiti Teknologi PETRONAS. In this study, 15 wt % K₂CO₃ + 3 wt % glycine is utilized as the medium for absorption, and the operating pressure is set at 40 bar to imitate the natural gas treatment process. The removal observed from the pilot plant is about 75% and the steady-state simulation with a tuned vaporization efficiency managed to replicate a similar result. The transient analysis is performed via activating a flow-driven method, and the simulation is transferred into Aspen Dynamic. A simple control strategy using a proportional-integral (PI) controller is installed at the gas outlet to monitor the CO₂ composition, and further disturbances are introduced at the inlet gas flow rate using a step test and ramp test. The controller is tuned using a trial-and-error method and a satisfactory response is achieved under varying changes in the inlet gas flow rate. Further investigation is carried out using the model predictive controller (MPC), in which 5000 data points are generated through pseudorandom binary sequence (PRBS) analysis for state-space model system identification. The state-space model identified as the best is then used to design the MPC controller. A disturbance rejection test on the MPC controller is conducted via changing the gas flow rate at 5% and a quick response is observed. In conclusion, both MPC and PI controllers managed to produce a good response once the disturbance was introduced within the CO₂-potassium carbonate-glycine (PCGLY) system.