Abstract :
[en] During the combustion of fossil fuels in power plants, large carbon dioxide quantities are produced and released into the atmosphere. Carbon dioxide is a greenhouse gas and its role in the current global warming is widely accepted by the scientific community. Many projects have been launched in the last few years that aimed at developing processes for the mitigation of carbon-dioxide emissions. Among the different carbon capture and storage technologies (CCS), the post-combustion capture of CO2 in power plants seems promised to a large development.
The objective of the present work is to model a pilot installation that should be built in the next few months. This pilot installation will be retrofitted in an existing coal-fired power plant in order to treat 5000 Nm³/h flue gas in two process trains. It is planed that 90% of the CO2 present in the flue gas can be removed, which corresponds to a capture rate of about 1 ton CO2/h. The role of this simulation is to facilitate the comprehension of the capture phenomena and to highlight the key process parameter and their influence on the obtained results. Furthermore, some technical improvements are studied that aim at a reduction of the energy consumption of the CO2-capture process.
The simulation tool Aspen Plus has been employed to model the pilot installation. It has been assumed for the simulation requirement that the equilibrium state was achieved for each stage of the mass transfer columns. Mass transfer limitations and reaction kinetics have then been neglected.
The model described in this work has been successfully developed for one process train treating a flue gas flow of 2500 Nm³/h. The solvent is monoethanolamine (MEA), which is the most employed solvent in CO2-capture technologies. The CO2-recovery rate has been fixed to 90%.
The most relevant process parameter that have been studied with the developed model are the solvent flow rate, the solvent concentration, and the stripper pressure. An optimum for the solvent flow rate has been identified at 11,75 m³/h, corresponding to a thermal energy consumption of 3,76 GJ/ton CO2.
When increasing the stripper pressure, the thermal energy consumption decreased up to 16%. The fact that a pressure increase in the stripper leads to a temperature increase and the strong temperature dependence of the CO2-partial pressure explained this reduction of the thermal energy consumption. However, an increase of the stripper pressure induces solvent degradation problems, corrosion and a more complex equipment design.
The MEA-concentration has been varied between 27 and 37 wt-%. When using a more concentrated solvent solution, the solvent is easier to regenerate. Consequently, the thermal energy consumption of the process decreased up to 12,5%. However, corrosion problems limit the use of concentrated solvents so that the MEA-concentration in capture-processes is generally adjusted to 30 wt-%.
Furthermore, two process modifications have been tested successfully. First, a partial evaporation of the regenerated solvent after the stripper outlet has been studied. The gaseous product of this partial evaporation was compressed and recycled to the stripper. A decrease by 25% of the thermal energy consumption could be achieved. However, compression work has to be furnished. When calculating the improvement on the basis of exergy, then the exergy of the capture process decreased by 18%.
The second modification that has been studied is a solvent intercooling between two absorber stages. It has been observed that intercalating the intercooler between absorber bottom stages gives better results than between absorber top stages. Simulation results have shown that the thermal energy consumption decreased by up to 6%. In the case of a flue gas pre-cooling before the absorber inlet, about the same reduction of the thermal energy requirement could be achieved.
Finally, a thermal energy consumption of 2,82 GJ/ton CO2 has been achieved in the best case, corresponding to a process exergy reduction by approximately 18%. The developed model allows further improvements so that the optimization of the CO2-capture process could be pursued. Since a detailed study of the process model could help the planning of an experimental test phase, the test-campaigns with the new pilot plant could be optimized.
