Design and simulation of pressure swing adsorption cycles for CO2 capture

Carbon capture and storage technologies (CCS) are expected to play a key role in the future energy matrix. Different gas separation processes are under investigation with the purpose of becoming a more economical alternative than solvent based post combustion configurations. Previous works have proved that pressure swing adsorption (PSA) cycles manage to reach similar carbon capture targets than conventional amine process but with approx. a 50% lower specific energy consumption when they are applied at lab scale. These encouraging results suggest that research must be undertaken to study the feasibility of this technology at a low to medium power plant scale. The simulation of PSA cycles is a computationally challenging and time consuming task that requires as well a large set of experimentally measured data as input parameters. The assumption of Equilibrium Theory reduces the amount of empirically determined input variables that are necessary for modelling adsorption dynamics as well as enabling a simpler code implementation for the simulators. As part of this work, an Equilibrium Theory PSA cycle solver (Esim) was developed, the novel tool enables the quantification of the thermodynamic limit for a given PSA cycle allowing as well a pre-selection of promising operating conditions and configurations (high separation efficiency) for further investigation by using full governing equation based software The tool presented in this thesis is able to simulate multi-transition adsorption systems that obey any kind of equilibrium isotherm function without modifying its main code. The second part of this work is devoted to the design, simulation and optimisation of two stage two bed Skarmstrom PSA cycles to be applied as a pre-combustion process in a biomass gasification CHP plant. Simulations were carried out employing an in house software (CySim) in which full governing equations have been implemented. An accurate analysis of the operating conditions and cycle configurations was undertaken in order to improve the performance of the carbon capture unit. It was estimated that the energy penalty associated with the incorporation of the adsorptive pre combustion process was lower for a conventional post combustion solvent unit, leading as well to lower specific energy consumption per unit of captured CO2 and higher overall efficiencies for the CHP plant with installed pre-combustion PSA cycles. This work is pioneer in its kind as far as modelling, simulation, optimisation and integration of PSA units in energy industries is concerned and its results are expected to contribute to the deployment of this technology in the future energy matrix

Modelling and simulation of adsorption process for removal of CO2 from natural gas in an offshore platform

The presence of CO2 in natural gas causes pipeline corrosion and increases operating costs during transfer from the offshore production platforms to the storage terminal. Due to space limitation and harsh operating environment, a robust and compact process such as pressure swing adsorption is preferable. To facilitate the study of process dynamics, simulation studies based on a derived mathematical model on a MATLAB software is presented. The effect of design parameters, focusing on the column height is considered, and it is found that for a typical laboratory scaled apparatus having diameter of 0.5 m. The maximum height required to adsorb 99 % CO2 is 3 m when the feed flow rate is fixed at 2.5 m3/s. The size of adsorbent particles is also impacting separation efficiency, and the optimum particle radius is found to be 1.25x10-3 m and the bed porosity was 0.2. Sensitivity analyses on the main operating parameters are also investigated. It is found that the initial CO2 feed composition has positive relationship to the adsorption efficiency. The 0.4 mole fraction was found to have sufficient separation efficiency of 90 %. The model is also tested for representing a typical industrial operation with 120 mmscfd. In this case, for a 4 m diameter column, a column height of 20 m is required. This is achieved with a 4 bed PSA system at a flow rate of 10.05 m3/s for each, and an optimum separation of 87 % is established. Based on the results obtained in this work it can be concluded that the model is a reasonable representation of the system and can be used to obtain the necessary process insights for further process development

Mathematical modelling of a low-temperature hydrogen production process with In Situ CO2 capture

Imperial Users onl

A multi-criteria design framework for the synthesis of complex pressure swing adsorption cycles for CO2 capture

Pressure Swing Adsorption (PSA) is the most efficient option for middle scale separation processes. PSA is a cyclic process whose main steps are adsorption, at high pressure, and regeneration of the adsorbent, at low pressure. The design of PSA cycles is still mainly approached experimentally due to the computational challenges posed by the complexity of the simulation and by the need to detect the performance at cyclic steady state (CSS). Automated tools for the design of PSA processes are desirable to allow a better understanding of the the complex relationship between the performance and the design variables. Furthermore, the operation is characterised by trade-o�ffs between conflicting criteria. A multi-objective flowsheet design framework for complex PSA cycles is presented. A suite of evolutionary procedures, for the generation of alternative PSA con�figurations has been developed, including simple evolution, simulated annealing as well as a population based procedure. Within this evolutionary procedure the evaluation of each cycle confi�guration generated requires the solution of a multi-objective optimisation problem which considers the conflicting objectives of recovery and purity. For this embedded optimisation problem a multi-objective genetic algorithm (MOGA), with a targeted fi�tness function, is used to generate the approximation to the Pareto front. The evaluation of each alternative design makes use of a number of techniques to reduce the computational burden. The case studies considered include the separation of air for N2 production, a fast cycle operation which requires a detailed di�ffusion model, and the separation of CO2 from flue gases, where complex cycles are needed to achieve a high purity product. The novel design framework is able to determine optimal configurations and operating conditions for PSA for these industrially relevant case studies. The results presented by the design framework can help an engineer to make informed design decisions

Model-based Design, Operation and Control of Pressure Swing Adsorption Systems

This thesis is concerned with the design, operation and control of pressure swing adsorption (PSA) systems, employing state of the art system engineering tools. A detailed mathematical model is developed which captures the hydrodynamic, mass transfer and equilibrium effects in detail to represent the real PSA operation. The first detailed case study presented in this work deals with the design of an explicit/multi-parametric model predictive controller for the operation of a PSA system comprising four adsorbent beds undergoing nine process steps, separating 70 % H2, 30 % CH4 mixture into high purity hydrogen. The key controller objective is to fast track H2 purity to a set point value of 99.99 %, manipulating time duration of the adsorption step, under the effect of process disturbances. To perform the task, a rigorous and systematic framework is employed comprising four main steps of model development, system identification, the mp-MPC formulation, and in-silico closed loop validation, respectively. Detailed comparison studies of the derived explicit MPC controller are also performed with the conventional PID controllers, for a multitude of disturbance scenarios. Following the controller design, a detailed design and control optimization study is presented which incorporates the design, operational and control aspects of PSA operation simultaneously, with the objective of improving real time operability. This is in complete contrast to the traditional approach for the design of process systems, which employs a two step sequential method of first design and then control. A systematic and rigorous methodology is employed towards this purpose and is applied to a two-bed, six-step PSA system represented by a rigorous mathematical model, where the key optimization objective is to maximize the expected H2 recovery while achieving a closed loop product H2 purity of 99.99 %, for separating 70 % H2, 30 % CH4 feed. Furthermore, two detailed comparative studies are also conducted. In the first study, the optimal design and control configuration obtained from the simultaneous and sequential approaches are compared in detail. In the second study, an mp-MPC controller is designed to investigate any further improvements in the closed loop response of the optimal PSA system. The final area of research work is related to the development of an industrial scale, integrated PSA-membrane separation system. Here, the key objective is to enhance the overall recovery of "fuel cell ready" 99.99 % pure hydrogen, produced from the steam methane reforming route, where PSA is usually employed as the purification system. In the first stage, the stand-alone PSA and membrane configurations are optimized performing dynamic simulations on the mathematical model. During this procedure, both upstream and downstream membrane configuration are investigated in detail. For the hybrid configuration, membrane area and PSA cycle time are chosen as the key design parameters. Furthermore, life cycle analysis studies are performed on the hybrid system to evaluate its environmental impact in comparison to the stand-alone PSA system

Kinetics of CO2 adsorption on cherry stone-based carbons in CO2/CH4 separations

Most practical applications of solids in industry involve porous materials and adsorption processes. A correct assessment of the equilibrium and kinetics of adsorption is extremely important for the design and operation of adsorption based processes. In our previous studies we focused on the evaluation of the equilibrium of CO2/CH4 adsorption on cherry stone-based carbons. In the present paper the kinetics of adsorption of CO2 on two cherry stone-based activated carbons (CS-H2O and CS-CO2), previously prepared in our laboratory, has been evaluated by means of transient breakthrough experiments at different CO2/CH4 feed concentrations, at atmospheric pressure and 30 °C. A commercial activated carbon, Calgon BPL, has also been evaluated for reference purposes. Three models have been applied to estimate the rate parameters during the adsorption of CO2 on these carbons, pseudo-first, pseudo-second and Avrami´s fractional order kinetic models. Avrami´s model accurately predicted the dynamic CO2 adsorption performance of the carbons for the different feed gas compositions. To further investigate the mechanism of CO2 adsorption on CS-H2O, CSCO2 and Calgon BPL, intra-particle diffusion and Boyd´s film-diffusion models were also evaluated. It was established that mass transfer during the adsorption of CO2 from CO2/CH4 is a diffusion-based process and that the main diffusion mechanisms involved are intra-particle and film diffusion. At the initial stages of adsorption, film diffusion resistance governed the adsorption rate, whereas intra-particle diffusion resistance was the predominant factor in the following stages of adsorption.This work has received financial support from the Spanish MINECO (Project ENE2011-23467), co-financed by the European Regional Development Fund (ERDF), and from the Gobierno del Principado de Asturias (PCTI 2013-2017 GRUPIN14-079). N.A-G. also acknowledges a fellowship awarded by the Spanish MINECO (FPI program), and co-financed by the European Social Fund.Peer reviewe

Dynamic Modeling, Predictive Control and Optimization of a Rapid Pressure Swing Adsorption System

Rapid Pressure Swing Adsorption (RPSA) is a gas separation technology with an important commercial application for Medical Oxygen Concentrators (MOCs). MOCs use RPSA technology to produce high purity oxygen (O2) from ambient air, and provide medical oxygen therapy to Chronic Obstructive Pulmonary Disease (COPD) patients. COPD is a lung disease which prevents O2 from entering a patient\u27s blood, and reduces the blood oxygen level. The standard therapy for COPD is to provide the patient with high purity (~90%) O2. MOCs have become more popular than traditional O2 gas cylinders due to their improved safety, and smaller device size and weight. The MOC market is growing rapidly and was expected to grow from $358 million in 2011 to$1.8 billion in 2017. Recently, a novel, single-bed MOC design was developed and tested to further reduce the size and weight of the device, and provide a continuous supply of O2 to the patient. This single-bed design uses a complex RPSA cyclic process with many nonlinear effects. Flow reversals, discrete valve switching, nonlinear adsorption effects, and complex fluid dynamics all make operating the RPSA system very challenging. Feedback control is necessary in a final commercial product to ensure the device operates reliably, but feedback control of PSA systems is not well studied in the current literature.In this work, a study of dynamic modeling, predictive control and optimization of this single-bed RPSA device is presented. A detailed, nonlinear plant model of the RPSA device is used to study the dynamics of the system as well as design a Model Predictive Controller (MPC) for the RPSA system. The plant model is a fully coupled, nonlinear set of Partial and Ordinary Differential Equations (PDEs and ODEs) which act as a representation of reality when design and evaluating the MPC. A sub-space model identification technique using Pseudo-Random Binary Sequence (PRBS) input signals generate a linear model which reduces the computational cost of MPC, and allows the algorithm to be implemented as an embedded controller for the RPSA device. The multivariable MPC independently manipulates the RPSA cycle step durations to control both the product composition and pressure. This MPC strategy was designed and tested in simulation before being implemented on a lab-scale device.The MPC is implemented onto a lab-scale MOC prototype using Raspberry Pi hardware, and evaluated using several MOC-relevant disturbance scenarios. The MPC is also expanded using piece-wise linear modeling to improve the performance of an RPSA device for other concentrated O2 applications. The embedded MPC features a convex quadratic optimization problem which is solved in real time using online output measurements. Additional hardware in the embedded controller operates the RPSA cycle and implements control actions supplied by the MPC.Design and optimization of RPSA systems remains an active area of research, and many PSA models have been used to optimize RPSA cycles in simulation. In this work, a model-free steady state optimization approach using the embedded hardware is presented which does not require a detailed process model, and uses experimental data and a nonlinear solver to optimize the RPSA operation given various objectives