Dynamic Modelling of Carbon Dioxide Absorber for Different Solvents

In the recent era, the green house alleviation technologies have been fully emphasized and implemented due to the rapid climate change. Fossil fuelled power plants contribute to the globally carbon dioxide (CO2) emission. Post combustion CO2 capture (PCC) and natural gas processing plant CO2 capture processes have attained a high consideration and interest which led to significant progress in CO2 capture. Chemical absorption is the well-established and commercialized technology compare to other technologies in CO2 capture. Choice of solvent is very important to optimize the performance of absorber.
The aim of this project is to simulate the rate based CO2 absorber model using two different types of solvent to check the CO2 removal efficiency considering the same operational conditions of the absorption column. This project emphasis only on the solvent parameters since the manipulate variable of this project is solvent, while the inlet gas stream is considered constant parameters. For this project, the CO2 absorption process modelling was done using air as the gas inlet stream. The developed models for each solvent were implemented in Matlab.
The developed models are comprised of mass balance, energy balance, rate transfer, interface and hydraulic model. The scope of this project involved the evaluation of three different solvents which are monoethanolamine (MEA) and sodium hydroxide (NaOH).
The results of developed models are validated with the literature. The analysis of simulation results highlights that the CO2 absorption process more likely happens at the lower segment of the absorber. As the gas flow from bottom to top of the absorber, the gas phase CO2 concentration and the gas temperature decrease. The solvent concentration declines from upper to lower segment of the absorber while the solvent temperature rises from upper to lower segment of the absorber. Both MEA and NaOH solvents results are agreed to the pilot scale experimental results.
The developed model can be used to evaluate the efficacy and capability of ANY novel solvent in a simulated environment before it is being tested on actual experimental set-up. Therefore the best solvent can be determined. The objective of the project is accomplished