(634d) Modeling, Simulation and Optimization of Pressure Swing Adsorption (PSA) Processes for Post-Combustion Carbon Dioxide (CO2) Capture from Flue Gas
This work presents a mathematical modeling framework developed from our research group [8,9] for the simulation and optimization of PSA/VSA processes for post-combustion CO2 capture from dry flue gas (15% CO2, 85% N2). The core of the modeling framework represents a detailed adsorption column model relying on a coupled set of mixed partial differential and algebraic equations (PDAEs) for mass, heat and momentum balance at both bulk gas and particle level, equilibrium isotherm equations, transport and thermo-physical properties of the gas mixture and boundary conditions according to the operating steps. The proposed modeling equations have been implemented in the gPROMS™ modeling environment. The modeling framework is first validated against data available from the literature , illustrating good agreement in terms of several process performance indicators . Accordingly, the developed modeling framework is employed for a comparative evaluation of three available potential adsorbents for CO2 capture, namely, zeolite 13X, activated carbon and Mg-MOF-74 . A two-bed configuration (six-step VSA cycle) with light product pressurization has been employed in all simulations in accord with recent studies [13, 14]. The results from systematic comparative simulations demonstrate that zeolite 13X has the best process performance among the three adsorbents, in terms of CO2 purity and CO2 recovery. On the other hand, Mg-MOF-74 appears to be a promising adsorbent for CO2 capture, as it has considerably higher CO2 productivity compared to the other two adsorbents. Furthermore process optimization studies using zeolite 13X and Mg-MOF-74, have been performed to minimize energy consumption for specified minimum requirements in CO2 purity and in CO2 recovery at nearly atmospheric feed pressures. The optimization results indicate that there is a complex relationship between optimal process performance indicators and operating conditions that varies among the different adsorbents and cannot be quantified by simple comparison of CO2/N2 adsorption isotherms and selectivity data. Evidently, detailed process modeling, simulation and optimization strategies, provide the most reliable way to evaluate both qualitatively and quantitatively potential adsorbents for CO2 capture. Finally, the reduction of CO2 emissions from dry flue gas employing two successive PVSA units, using zeolite 13X and Mg-MOF-74 as adsorbents, is considered and the effects of operating parameters on the separation quality are investigated by simulation and optimization. With the proposed two-stage PVSA process, a CO2 purity higher than 95% with a relatively high CO2 recovery unit (greater than 90%) is obtained.
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