Six-step Pressure Swing Adsorption Process Research Articles

Optimization of a Six-Step Pressure Swing Adsorption Process for Biogas Separation on a Commercial Scale

Pressure swing adsorption (PSA) appears to be an effective technology for biogas upgrading under different operating conditions with low greenhouse gas emissions. This study presents the simulation of biomethane adsorption with the adsorption bed filled with a carbon molecular sieve (CMS). A six dual-bed six-step PSA process was studied which produced a high purity of biomethane. The design of the adsorption bed was followed by the real process of which the biomethane capacity was more than 5000 Nm3/h. For the adsorbent, a CMS-3K was used, and a biomethane gas with a minimum 92% purity was produced at 6.5 bar adsorption pressure. To understand the adsorption characteristics of the CH4 and CO2 gases, the Langmuir isotherm model was used to determine the isotherm of a mixed gas containing 55% CH4 and 45% CO2. Furthermore, the experimental data from the work of Cavenati et al. were used to investigate the kinetic parameter and mass transfer coefficient. The mass transfer coefficients of two species were determined to be 0.0008 s−1 and 0.018 s−1 at 306 K for CH4 and CO2, respectively. The PSA process was then simulated with a cyclic steady state until the relative tolerance was 0.0005, which was then used to predict the CH4 and CO2 mole fraction along the adsorption bed length at a steady state. Moreover, the optimal conditions were analyzed using Aspen Adsorption to simulate various key operating parameters, such as flowrate, adsorption pressure and adsorption time. The results show a good agreement between the simulated results and the real operating data obtained from the company REBiofuel. Finally, the sensitivity analysis for the major parameters was presented. The optimal conditions were found to be an adsorption pressure of 6 bar, an adsorption time of 250 s and a purity of up to 97.92% with a flowrate reducing to 2000 Nm3/h. This study can serve as a commercial approach to reduce operating costs.

Experimental Study of High Purity CO2 Concentration from Syngas by a Dual-bed Six-step Pressure Swing Adsorption Process

With the industry development, the concentration of greenhouse gas increases year by year. Consequently, how to reduce the emission of greenhouse gas has become an important issue all over the world. This research is the experimental study of concentrating high purity CO2 from syngas after oxy-fuel combustion by a dual-bed six-step pressure swing adsorption (PSA) process. The composition of feed gas used in the process was simulated as 95% CO2, with N2 balanced. We chose UOP 13X zeolite as the adsorbent according to the adsorption capacity and selectivity of CO2 over N2 comparing to other adsorbents studied. The breakthrough and desorption curves were discussed by changing different feed flow rate and temperature. Next the carbon dioxide was purified by a dual-bed six-step PSA process. After exploring the effects of variables on performance of PSA process, we found the best operating conditions for obtaining high purity carbon dioxide among our experiments. The best operating conditions are feed pressure 3.45 atm, countercurrent depressurization pressure 0.48 atm and purge to feed ratio 0.105. The experimental results of best conditions are 99.94% purity and 42.84% recovery of carbon dioxide at bottom product, energy consumption 0.304 GJ/tonne CO2 and productivity 0.136 kg CO2/kg adsorbenth.

Design of a Hybrid Controller for Pressure Swing Adsorption Processes

The aim of this paper is to synthesize a hybrid controller for pressure swing adsorption (PSA) processes. Since the process is described by a set of partial differential algebraic equations, first a local reduced-order model (LROM) for the process is developed and is formalized as a hybrid system. A hybrid controller is designed for purity control of the process in the presence of external disturbances by determining the maximal safe set of the LROM. A hybrid backward reachability analysis is performed for this purpose. Considering a realistic scenario for PSA processes where the states are not available and the number of measurement sensors is very limited, the desired states are estimated by using a hybrid observer. The controller is designed and applied to a two-bed, six-step PSA process whose dynamical behavior is simulated by a full-order principle-based model of the process. An excellent performance of the controller is obtained.

Design of a dynamical hybrid observer for pressure swing adsorption processes

As an integral part of a hybrid control system for Pressure Swing Adsorption (PSA) processes, a dynamical hybrid observer is proposed for online reconstruction of the active mode and continuous states of these processes. Hybrid systems feature both continuous and discrete-event dynamics and hence are very suited to describe PSA processes. For estimation of the active mode, a mode observer is designed, and the continuous spatial profiles in each mode are estimated by distributed and decentralized Kalman filters. The proposed hybrid observer has been applied, in silico, for a two-bed, six-step PSA process used for Hydrogen purification. The active mode of the process along with the continuous spatial profiles of its adsorption beds have been estimated quite accurately based on the measured temperatures and pressures at a few points in the process, these measured signals are all noise-corrupted and measured discretely.

Dynamical Hybrid Observer for Pressure Swing Adsorption Processes

A dynamical hybrid observer is proposed for online reconstruction of the active mode and continuous states of Pressure Swing Adsorption (PSA) processes as an integral part of a hybrid control system. A mode observer is designed for estimation of the active mode, and the continuous spatial profiles are estimated by a Distributed and Decentralized Switching Kalman Filter. The proposed hybrid observer has been applied, in silico, for a two-bed, six-step PSA process. The active mode of the process along with the continuous spatial profiles of its adsorption beds have been estimated quite accurately based on very limited number of noise corrupted temperature and pressure measurements.

Adsorption processes for CO2capture from flue gas using polyaniline solid sorbent

In this simulation study, the temperature swing adsorption (TSA) process and the pressure swing adsorption (PSA) process were utilized to separate flue gas (15.03% CO2 and 84.97% N2) from a power plant with a solid polyaniline sorbent. CO2 can be recovered and sequestrated to reduce greenhouse-gas effects. The method of lines is utilized, combined with upwind differences, cubic spline approximation and LSODE of ODEPACK software to solve the problem. The concentration, temperature, and adsorption quantity in the bed are integrated with respect to time by LSODE of ODEPACK software. The simulation is stopped when the system reaches a cyclic steady state. In this study, experimental data was first regressed to obtain the parameters of the isotherm curves; then the breakthrough curve of the solid polyaniline sorbent was simulated. The feasibility of the adsorption process simulation program became obvious through a comparison of the experimental and simulation results. Four different processes were used in this study: the single-bed five-step TSA process, the single-bed two-step PSA process, the single-bed three-step PSA process and the dual-bed six-step PSA process. The optimal operating conditions were obtained by varying the operating variables, such as adsorption temperature, desorption temperature, feed pressure, bed length, step time, etc. After the variables discussion, the best process is found to be the single-bed three-step PSA process and the best operating conditions are a feed pressure of 6.0 atm, a co-current depressurization pressure of 1.0 atm, a vacuum pressure of 0.1 atm, a bed length of 98.3 cm and step times of 1200, 10 and 500 s. The results of the aforementioned operating conditions are 97.13% purity and 87.26% recovery of CO2.