Dynamic Process Model Development and Validation with Transient Plant Data Collected from an MEA Test Campaign at the CO2 Technology Center Mongstad. (July 2017)

• Record Type: Journal Article
• Authors: Montañés, Rubén M.; Flø, Nina E.; Dutta, Rohan; Nord, Lars O.; Bolland, Olav
• Is Part Of: Energy procedia. Volume 114(2017)
• Page Start: 1538
• Page End: 1550
• Publication Date: 2017-07
• Subjects: Post-combustion -- natural gas -- transient data -- rate-based model -- model validation -- pilot plant -- dynamic modeling -- Modelica; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2017.03.1284
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: This work focuses on the development and validation of a dynamic process model of the post-combustion CO2 chemical absorption process with temperature swing absorption (TSA) using aqueous monoethanolamine (MEA) as solvent. A new set of steady-state and transient cases were generated during an MEA test campaign at the amine pilot plant at CO2 Technology Center Mongstad (TCM DA). Nine steady-state cases comprising a wide range of operating conditions of the plant and two transient tests consisting of flue gas volumetric flow rate step-changes were utilized for the purpose of dynamic process model validation of the overall pilot plant process model. It is concluded that the dynamic process model is capable of estimating the absorber and stripper columns temperature profiles with good accuracy after tuning of model parameters. An over-prediction of the model for lean and rich CO2 loadings has been reported, being mean percentage errors <1.5% for lean loading and <6.7% for rich loading. In addition, an under prediction of CO2 product flow rate has been observed (<5%). The process model is capable of predicting the variability of lean and rich loadings for the range of steady-state operating conditions. The main process dynamics of the pilot plant under flue gas volumetric flow rate set-point step changes is captured by the process model.