Process Simulation Of Co-Combustion Of Coal And Biomass In Fluidized Bed Combustor

Abstract

With ever-increasing usage of biomass to curb environmental pollution, it is imperative to develop new insights into coal combustion processes, for efficient and optimal usage. Many process models have been developed for combustion process, including fixed and fluidized bed combustion for different types of coal; however, they are designed for specific process and lack generality. More recently, Aspen Plus has introduced new tools, and particularly featured a built-in unit operation model, to design fluidized bed processes. Herein, a process simulation model has been developed to simulate and predict the condition of co-combustion of coal and biomass in fluidized bed combustor (CFBC) based on Aspen Plus with considering gas-solid hydrodynamics via Aspen Plus in-line FORTRAN codes and combustion reaction kinetics via some external FORTRAN subroutines simultaneously. In this study, a novel hybrid approach for modelling coal combustion has been implemented to comprehensively design a model for conversion of low-grade coal under various operating conditions. The proposed model combines sequential modeling of drying/pyrolysis (devolatilization) and combustion of coal by means of conventionally used units (RYIELD and RGIBBS), & a newly used unit (FLUIDBED) in Aspen Plus. The model validation was performed by experiments on the combustion of low-grade coal in a pilot-scale circulating fluidized bed reactor (CFBR). Experimental data were used to further calibrate the Aspen Plus model and decrease model uncertainties. The results obtained from the developed simulation model were found to be in good agreement with the experimental data. Discrepancies of less than 15% were observed, in most of the predictions of molar fractions for the resultant flue gas composition, including NO_x& SO_x, emissions which were at ppm levels. As a result, the model can easily be used for design, scale-up, and simulation of coal combustion as well as for other feedstock like biomass in fluidized bed with process optimization based on sensitivity analysis.