(716f) Design and Control Optimization of Pressure Swing Adsorption Systems for Hydrogen Recovery from IGCC Plants with Co-Capture of Carbon Dioxide

The vast emission of pollutants into the environment from current processes is causing significant environmental problems. In addition to the search for alternative sources for energy production, the implementation of more efficient energy processes has been explored with particular interest [1]. Integrated gasification combined cycle (IGCC) power plants provide an efficient way to obtain syngas from the gasification of coal. Syngas is used as fuel in a gas turbine to generate electricity. However, these processes contribute adversely to the generation of carbon dioxide emissions, so it is important to implement carbon capture and storage technologies as part of the design [2]. On the other hand, the produced syngas is rich in hydrogen, so a fraction of the product can be purified to produce hydrogen in addition to power [3]. Hydrogen has been considered with interest as a clean energy source due to its properties, among which are the zero emissions of carbon dioxide during its combustion [4]. Hydrogen purification from syngas with carbon capture can be achieved using a pressure swing adsorption (PSA) system [2]. PSA is an efficient cyclic process used for gas separation with low energy demand. It consists of a minimum of two interconnected columns that contain beds with an adsorbent material. However, PSA systems are very complex for both design and operation due their periodic behavior. The cyclic operation prevents a continuous steady state to be reached; instead, PSA shows cyclic steady states (CSS) for periods of time with the fixed operating conditions that define each cycle [5]. In addition to its periodicity, the non-linearity of the system makes its optimization complicated, with has also affected the development of control studies for these types of systems [6].

In this project, it is performed a detailed design and model-based control optimization study of a PSA system used to recover high-purity hydrogen from the syngas of an IGCC plant with carbon dioxide capture. The PSA system consists of two adsorbent beds with activated carbon and zeolite as adsorbent materials. The feed syngas is considered with composition of H2 88.75%, CO2 2.12%, CO 2.66%, N2 5.44% and Ar 1.03%. The key control objective is to fast track H2 purity to 99.9mol% in the presence of process disturbances. Thus, the PSA system is considered as a single input / single output (SISO) system with the product purity as a control variable and the adsorption time as the manipulated variable. To perform this task, the PAROC (PARametric Optimisation and Control) framework [7] is employed for the design, operational optimization, and explicit/multi-parametric model predictive control (mp-MPC) of this PSA system. Specifically, a high-fidelity dynamic PSA model is first developed, which consists of partial differential and algebraic (PDAE) equations including mass balance, momentum balance (Ergun equation), adsorption equilibria (Dual site Langmuir model), mass transfer (Linear driving force) and energy balance [8,9] The PDAE model is then approximated as a linear state-space model using system identification methods, with the goal of reducing the model complexity while maintaining desired accuracy. Based on the reduced model, explicit model predictive control strategies are developed via offline multi-parametric quadratic programming [9]. The resulting mp-MPC controller is tested against the original high-fidelity model to ensure that the hydrogen purity specification is satisfied under process disturbances.

References
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[7] E. N. Pistikopoulos, N. A. Diangelakis, R. Oberdieck, M. M. Papathanasiou, I. Nascu and M. Sun, "PAROC—An integrated framework and software platform for the optimisation and advanced model-based control of process systems," Chemical Engineering Science, vol. 136, p. 24, 2015.
[8] D.-K. Moon, D.-G. Lee and C.-H. Lee, "H2 pressure swing adsorption for high pressure syngas from an integrated gasification combined cycle with a carbon capture process," Applied Energy, vol. 183, p. 15, 2016.
[9] H. Khajuria and E. N. Pistikopoulos, "Dynamic modeling and explicit/multi-parametric MPC control of pressure swing adsorption systems," Journal of Process Control, vol. 21, p. 13, 2011.