1. Introduction
The continuous exploration of new gas reserves alongside increases in global power demand necessitates the development of less demanding technologies, such that the treatment process can be accomplished at a minimized cost. One of the most common and cost-effective technologies is the chemical absorption process. This method is advantageous in its high efficiency and mature technologies as compared to other methods.1 The cost associated with using conventional amines like monoethanolamine (MEA) and diethanolamine (DEA) are steep due to high volatility, high solvent degradation rate, and high regeneration energy requirement. The high regeneration energy that severely increases the uptake of electricity by up to 70-80% has led many global researchers to explore other potential solvents.2
Absorption processes based on glycine-promoted carbonate solvents are currently of interest as a technical alternative that has the potential to overcome the high regeneration energy requirement of amine-based solvents.3−6 However, the use of the newly promoted solvent is held back by its lack of studies and performance assessments under a wide range of conditions at a larger scale. Unlike CO2 capture via amines, no dynamic analysis has been reported under both lab-based or scaled-up conditions for this process. Direct utilization of the new green solvent cannot be simply implemented without basic knowledge of its behavior in large-scale applications. Hence, modeling and simulations are required to observe the complex interplay between the chemical and physical properties under scale-up conditions, especially during the transient process.
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Potassium carbonate (PC) is well known among CO2 removal processes, with the addition of promoters being actively investigated.7−9 Process optimization, energy analysis, and economic performance have been extensively studied at the steady-state level, but this study is not sufficient in predicting the operability of the plant in the presence of continuous and sudden system fluctuations. To date, many dynamic studies and modeling are reported for the process of CO2-MEA,10−13 though none so far for the K2CO3 system, especially with glycine acting as a solvent promoter. Therefore, the novelty in this work is contributed in three aspects.
- (i) The utilization of low-concentration potassium carbonate-glycine (PCGLY) for the removal of CO2, which is mixed at the ratio of 15 wt % + 3 wt %. This is necessary to achieve the green solvent title as it has low toxicity levels and will also avoid salt precipitation, preventing the presence of acids in the solvent.6,14 In addition to that, the high operating pressure and low concentration of the solvent were successful as the flash tank managed to recover the intended solvent without passing through a stripping column. Hence, the capital cost and operating cost can be optimized.7,8,14
- (ii) In the open literature, the first principal model and complicated rate-based method are commonly found for the dynamic analysis during the MEA-CO2 absorption process.11−13 Hence, this work uses a simple equilibrium approach with a tuned vaporization efficiency in the standard simulation program of Aspen Plus/Dynamic to observe the transient behavior.
- (iii) To control the process, many control strategies are proposed13,15,16 and in this study, a basic proportional-integral (PI) feedback control strategy is installed in a closed-loop system. System identification using the pseudorandom binary sequence (PRBS) signal is conducted to generate 5000 data points and exported to the Matlab. The 2nd order state-space model is selected to produce the best fit between the measured and simulated data before the model predictive controller (MPC) can be designed.17,18 The set point change is introduced and the response from the input-output behavior is observed.
This work is the first attempt to test the performance of a CO2-PCGLY system in the dynamic state. Hence, the key input process variable (mainly gas flow rate in the GASIN stream) is disturbed to observe the key output responses (CO2 mole composition in the GASOUT stream) to ensure that the desired removal is achieved throughout the process. A +5% step change, ramp, and sinusoidal tests are conducted to observe the PI controller performances. The controller response is further improved by tuning the gain and time integral. Then, the performance between the promoted solvent and unpromoted solvent in terms of the absorption rate is observed. An advanced controller such as the MPC is always desirable since a fast action controller is very essential to correct any deviations, especially in the CO2 removal target. Therefore, the MPC model is proposed to predict the future behavior of the system. The results from the dynamic model developed for this process have the potential to provide insight regarding the continuous process at the scale-up level for the K2CO3-glycine-CO2 process. Hence, it has high candidacy as a basis to further develop control strategy mechanisms related to operability.
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