Dynamic model validation of the post-combustion CO2 absorption process

Abstract A general dynamic process model of the post-combustion carbon dioxide (CO 2 ) absorption process based on aqueous monoethanolamine (MEA) is developed and implemented in MATLAB. The overall process model contains several unit models developed from first principle conservation laws for mass and energy, each representing individual process equipment. An equation based numerical integration method is used to solve the overall equation system simultaneously in MATLAB. Pilot plant data from specifically designed dynamic experiments with 30 wt% MEA is collected from a pilot plant at NTNU and SINTEF laboratories. This includes steady state data for eight different conditions along with six dynamic data sets with relevant step changes in lean solvent flow rate and reboiler duty. The pilot plant data show a very good steady state mass balance which indicates that the generated data sets are reliable. Two of the dynamic data sets are used for model validation and the results shows adequate agreement between model and pilot plant data. An average of 0.3% and −2.8% deviation in absorbed CO 2 is seen for the two simulated cases compared to pilot plant results and it is concluded that the model is able to capture the main dynamics of the experiments. The main cause of deviation is believed to concern uncertainties in mass transfer and effective mass transfer area correlations.

[1]  Mai Bui,et al.  Dynamic modelling and optimisation of flexible operation in post-combustion CO2 capture plants - A review , 2014, Comput. Chem. Eng..

[2]  T. Mejdell,et al.  CO2 post combustion capture with a phase change solvent. Pilot plant campaign , 2014 .

[3]  Axel Meisen,et al.  Predict amine solution properties accurately , 1996 .

[4]  Eric Croiset,et al.  Dynamic Simulation of MEA Absorption Processes for CO2 Capture from Fossil Fuel Power Plant , 2011 .

[5]  Paul Feron,et al.  Dynamic operation of post-combustion CO2 capture in Australian coal-fired power plants , 2014 .

[6]  Sigurd Skogestad,et al.  Economically efficient operation of CO2 capturing process. Part II. Design of control layer , 2012 .

[7]  Chechet Biliyok,et al.  Dynamic modelling, validation and analysis of post-combustion chemical absorption CO2 capture plant , 2012 .

[8]  Eric Croiset,et al.  Dynamic modelling and control of MEA absorption processes for CO2 capture from power plants , 2014 .

[9]  B. Metz.  IPCC special report on carbon dioxide capture and storage , 2005 .

[10]  Magne Hillestad,et al.  Selection of model parameter correlations in a rate-based CO2 absorber model aimed for process simulation , 2012 .

[11]  Shi-Shang Jang,et al.  Control strategies for flexible operation of power plant with CO2 capture plant , 2012 .

[12]  Bernt Lie,et al.  NEQ rate based modeling of an absorption column for post combustion CO2 capturing , 2011 .

[13]  Eric Croiset,et al.  Dynamic Modeling and Evaluation of an Industrial-Scale CO2 Capture Plant Using Monoethanolamine Absorption Processes , 2014 .

[14]  R. Reid,et al.  The Properties of Gases and Liquids , 1977 .

[15]  Finn Andrew Tobiesen,et al.  Experimental validation of a rigorous desorber model for CO2 post-combustion capture , 2008 .

[16]  R. Billet,et al.  Prediction of Mass Transfer Columns with Dumped and Arranged Packings , 1999 .

[17]  Meihong Wang,et al.  Demonstrating full-scale post-combustion CO2 capture for coal-fired power plants through dynamic modelling and simulation , 2012 .

[18]  Carl D. Laird,et al.  Nonlinear Model Predictive Control of a CO2 Post-Combustion Absorption Unit , 2012 .

[19]  Ana-Maria Cormos,et al.  Dynamic modeling and validation of absorber and desorber columns for post-combustion CO2 capture , 2011, Comput. Chem. Eng..

[20]  Finn Andrew Tobiesen,et al.  Experimental validation of a rigorous absorber model for CO2 postcombustion capture , 2007 .

[21]  Magne Hillestad,et al.  Investigation of the dynamic behavior of different stripper configurations for post-combustion CO2 capture , 2012 .

[22]  Ali Zakeri,et al.  A comparison of different parameter correlation models and the validation of an MEA-based absorber model , 2011 .

[23]  Sigurd Skogestad,et al.  Economically efficient operation of CO2 capturing process part I: Self-optimizing procedure for selecting the best controlled variables , 2011 .

[24]  H. M. Kvamsdal,et al.  Dynamic modeling and simulation of a CO2 absorber column for post-combustion CO2 capture , 2009 .

[25]  H. Yeung,et al.  Dynamic modelling and analysis of post-combustion CO2 chemical absorption process for coal-fired power plants , 2010 .

[26]  Graeme Puxty,et al.  Carbon dioxide postcombustion capture: a novel screening study of the carbon dioxide absorption performance of 76 amines. , 2009, Environmental science & technology.

[27]  Hallvard F. Svendsen,et al.  Mass transfer and kinetics of carbon dioxide absorption into loaded aqueous monoethanolamine solutions , 2015 .

[28]  Meihong Wang,et al.  Dynamic modelling of CO2 absorption for post combustion capture in coal-fired power plants , 2009 .

[29]  Angela Mangiaracina,et al.  Validation of a Dynamic Model of the Brindisi Pilot Plant , 2014 .

[30]  Gary T. Rochelle,et al.  Effects of the Temperature Bulge in CO2 Absorption from Flue Gas by Aqueous Monoethanolamine , 2008 .

[31]  Luis A. Ricardez-Sandoval,et al.  Controllability and optimal scheduling of a CO2 capture plant using model predictive control , 2014 .