Influence of biomass blends on the particle temperature and burnout characteristics during oxy-fuel co-combustion of coal

The difference in combustion performance between brown coal and black coal blended with Eucalyptus woodchip and woodchar in varying blending ratios were examined in the air and oxy firing conditions. On top of the experimental investigation using a drop tube furnace (DTF), a computational fluid dynamics (CFD) model was further developed to interpret these results, validated using the experimental data. The CFD model incorporates a comprehensive reaction for devolatilisation reaction to predict the gas release utilising predictions based on chemical percolation devolatilisation (CPD) model. The heterogeneous reactions are defined based on the intrinsic reaction model that accounts for the influence of char properties in chemical and pore diffusion reactions using a user-defined function (UDF). Moreover, the C-CO2 gasification reaction rate which is critical in an oxy-firing mode was further studied using the CFD tool to determine how the role of gasification varied for various fuel blends. Based on carbon burnout and average particle temperature profiles, the blending of woodchips is highly beneficial to the overall combustion performance in particular for low reactive black coal while its effect on brown coal is marginal. Woodchar and black coal are comparable with similar temperature plots and relatively constant burnout but it behaves relatively inert with a highly reactive brown coal. During oxy firing, increasing the woodchip content enhanced the effect of C-CO2 gasification due to its extremely large pre-exponential factor for the CO2 gasification reactivity which explains the improved burnout. The blending of woodchar caused a gradual reduction in the gasification extent for both coals explained by the low heating rates under which woodchar was pyrolysed and also due to the decrease in the peak particle temperature. However, the observed gasification was found to be less than the expected value based on the linear addition of the two single fuels for both biomass blends. (C) 2019 Energy Institute. Published by Elsevier Ltd. All rights reserved.