Dynamic process simulation of post-combustion CO2 capture process
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Due to the increased concern about global warming in recent years, it has been proposed that carbon capture and storage could be one of the solutions which can help reduce emissions of greenhouse gases from fossil power plants and industry. One of the problems associated with implementation of this technology is that it is expected that the volume of renewable energy sources for electricity production will increase significantly in the future. Because renewable sources provide power intermittently, it is likely that fossil power plants will be forced to operate flexibly to maintain a steady supply of power to the grid. As a result of this it is important to gain knowledge about the effects that dynamic operation of power plants have on the associated CO2 capture plant. To date, the most mature technology for CO2 capture is so called, amine based post-combustion CO2 capture. In order to study the dynamics of such plants it is necessary to use dynamic simulation models. In this thesis a steady state and a dynamic model of the amine based CO2 capture plant at the CO2 Technology Centre Mongstad (TCM) is created and validated against operating data from the facility. The simulation models are made using the process simulation software, Unisim Design Suite R430. The models are based on an equilibrium stage modeling approach and they utilize the Kent-Eisenberg model for calculation of the equilibrium constants (K-values). The created steady state model is validated against 9 different steady state operating cases from the plant. The results show that the steady state model can predict the plant performance with decent accuracy over a wide range of operating conditions. And the average relative deviation (ARD) between the steady state simulation model and operating data is found to be between 5-8 %, depending on which parameter is tested. The dynamic model functionality is verified and it is validated against two steady state cases, the results show that the dynamic model is able to predict the ARD between the simulation model and operating data for these two cases within 3-5,98%. A limitation of the dynamic validation is that because no dynamic operational data from TCM amine plant was available for the thesis, the simulation model could be dynamically validated against the dynamic response of the plant. Despite this, the dynamic model is used for simulating the dynamic response of the TCM amine plant with regards to step changes in reboiler duty, lean solvent and flue gas flowrates. The dynamic model predicts that there are moderate dead times of up to 25 minutes in the process upon change of these parameters, and that the settling time for the process is around 4 hours. The main cause of deadtime and settling time in the model appears to be the solvent hold-up volume. However, since the model could not be dynamically validated the results cannot be said to be conclusive.