@article{scholars16653,
           pages = {18213--18228},
       publisher = {American Chemical Society},
         journal = {ACS Omega},
            year = {2022},
           title = {CO2 Removal via an Environmental Green Solvent, K2CO3-Glycine (PCGLY): Investigative Analysis of a Dynamic and Control Study},
             doi = {10.1021/acsomega.1c06254},
          number = {22},
            note = {cited By 2},
          volume = {7},
            issn = {24701343},
          author = {Isa, F. and Zabiri, H. and Harun, N. and Shariff, A. M.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131899361&doi=10.1021\%2facsomega.1c06254&partnerID=40&md5=306feb789b45631f8106d47961841ae4},
        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. {\^A}{\copyright} 2022 The Authors.}
}