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Chapter 5. Simultaneous Design and Control Optimization of PSA Systems Under Uncertainty for the purpose of optimization studies. The details of the first principles based dynamic model of PSA employed in this work are already mentioned in chapter 3 of this thesis, while the boundary conditions are listed in Tables 5.4 and 5.5. Furthermore, the velocity dependent terms in the axial heat and mass transfer dispersion coefficients [162, 163] have been neglected. 5.2.2 Objective Function A commonly used objective function for PSA optimization is product recovery (see also Table 5.3). The main reason towards this trend is its direct relation to the plant operating cost [36], under the assumption that the PSA feed is already available at high pressure and does not require considerable compression work. In some cases, especially in air separation for O2 and N2 production, where the feed (air) is available only at atmospheric pressure, recovery alone is not a true indicator of PSA operating performance, and PSA overall compression work can also play a significant role. On the other hand, the key controller objective is to fast track the closed loop product purity to its desired set point in the event of process disturbances [21, 20, 72, 73]. In a PSA operation, since recovery and purity vary in opposite direction [73] with respect to important decision variables, a simultaneous optimization and control strategy appears to be an ideal platform to take account of the impact of these two conflicting objectives on the real- time PSA performance. In this study, an optimal PSA operational policy and controller configuration is desired which provides the maximum value of closed loop hydrogen recovery (Eq. 5.6) while obeying all operational constraints, for the separation of 70 % H2 and 30 % CH4 feed mixture to a product stream of hydrogen purity (Eq. 5.7) greater than 99.99 %, in the presence of the following disturbances and uncertainty. 109PDF Image | Operation and Control of Pressure Swing Adsorption Systems
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