The paper deals with numerical modelling of carbon dioxide capture by amine solvent from flue gases in post-combustion technology. A complex flow system including a countercurrent two-phase flow in a porous region, chemical reaction and heat transfer is considered to resolve CO 2 absorption. In order to approach the hydrodynamics of the process a two-fluid Eulerian model was applied. At the present stage of model development only the first part of the cycle, i.e. CO 2 absorption was included. A series of parametric simulations has shown that carbon dioxide capture efficiency is mostly influenced by the ratio of liquid (aqueous amine solution) to gas (flue gases) mass fluxes. Good consistency of numerical results with experimental data acquired at a small-scale laboratory CO 2 capture installation (at the Institute for Chemical Processing of Coal, Zabrze, Poland) has proved the reliability of the model.
This paper demonstrates the use of a combined software package including IPSEpro and MATLAB in the optimisation of a modern thermal cycle. A 900 MW power plant unit (operating at ultra-supercritical conditions) was considered as the study object. The Nelder-Mead simplex-based, direct search method was used to increase power plant efficiency and to find the optimal thermal cycle configuration. As the literature reveals, the Nelder-Mead approach is very sensitive to the simplex size and to the choice of method coefficients, i.e., reflection, expansion and contraction. When these coefficients are improperly chosen, the finding of the optimal solution cannot be guaranteed, particularly in such complex systems as thermal cycles. Hence, the main goal of the present work was to demonstrate the capability of an integrated software package including IPSEpro, MATLAB and MS Excel in the optimisation process of a complex thermal cycle, as well as to examine the effectiveness of the most popular sets of Nelder-Mead coefficients previously proposed by other researchers. For the investigation purposes, the bleed and outlet pressures from the turbines were considered as decision variables, and the power plant efficiency was used as an objective function.
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