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through PSA processes. Some experimental studies have been conducted both with zeolites [48-50] and with activated carbons [36, 51, 52]. However, not much has been done regarding modeling. This can be considered as a big gap, especially when considering post-combustion application where significant amount of water is present in the flue gas. The common approach suggested in the literature is to remove water prior the CO2 capture unit by means of a separate PSA unit or a pre-layer of selective adsorbents like activated alumina or silica gel desiccants [16, 53]. These methods have to prove to perform satisfactorily integrated in the complex arrangement of a power plant with CO2 capture systems. Further, they will result in additional power consumption. In the post-combustion simulation proposed, water is removed to as large extent as possible by condensation, and the remaining water is neglected in the PSA process due to lack of modeling data. The effect of this approximation could not be evaluated and would need to be investigated. For pre-combustion applications the content of water in the syngas entering the PSA unit is down to trace level (0.03%). As long as a more efficient regeneration procedure (e.g., heating of the bed) is planned after a certain number of cycles, in order to avoid water accumulation, the performance should not be significantly affected [7]. Thus, the water content was neglected in the present work without further concerns. 3.4. Solution of the PSA model The described modeling framework for the PSA process results in a set of partial differential and algebraic equations (PDAEs). The solution was obtained implementing the modeling equations in gPROMS environment (Process System Enterprise, London, UK). The set of PDAEs requires a considerable computational effort in order to be solved. One way to simplify the model, thus to reduce the computational time, was to adopt a one-column approach. This modeling strategy consists in simulating just one of the columns of the whole train [7, 25, 54, 55]. The interactions between different columns are accounted for by virtual gas streams which are defined through the information stored in the previous cycles. The rinse, purge and pressure equalization-pressurization steps rely on this modeling technique. Adopting this simplification, it is essential to assure that the mass balances are always closed. This is rather straightforward for the rinse and purge steps, while the pressure equalization steps requires an additional effort. In fact, an appropriate value of the equalization pressure needs to be set, in order to avoid inconsistency in the mass balances. The procedure outlined by Casas et al. [25] was applied to determine this pressure level. The discretization algorithm applied for the numerical solution of the model is the Centered Finite Difference Method (CFDM). The spatial domain was discretized in 150 intervals. A higher number of discretization points was not used, because it would have significantly increased the computational time, without increasing in a similar manner the accuracy of the simulation. The columns are considered to be initially filled with nitrogen and hydrogen, respectively in the post and pre- combustion scenario. The simulation is stopped when the Cycle Steady State (CSS) arises. At CSS the process repeats itself invariably, meaning that the conditions at the end of each cycle are the same as those at the beginning. Whilst the operation of a single column remains batchwise, the process reaches a steady condition. All the results presented refer to the cycles at CSS. 4. Results and discussion 4.1. Definition of the performance parameters The CO2 separation performance is primarily evaluated in terms of CO2 recovery (RCO2) and purity (PCO2). In the pre-combustion scenario it is also useful to define the H2 recovery (RH2), giving that H2 is fuelling the downstream gas turbine cycle. The CO2 recovery may be misleading when large energy penalties result from the CO2 separation process. For this reason, an additional parameter was introduced, namely the CO2 capture efficiency (ηCO2). The CO2 capture efficiency is the real measure to what extent the CO2 is captured from a power plant, relatively to a reference plant without CO2 capture. The aforementioned parameters are defined as following:PDF Image | Evaluating Pressure Swing Adsorption as a CO2 separation technique in coal-fired
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