Enhancement of reaction rate prediction of biomass: A focus on experimental and numerical simulation approaches

While the biomass gasification and cofiring technology is promising for future energy, including green technologies, such as carbon capture and storage and bioresource feedstock, negative carbon emissions are simultaneously possible using these technologies. However, despite these functions, our previous study established that for simulating a biomass reactor, a new model needed to be designed that could improve the accuracy of both real and lab-scale simulations for carbonaceous fuels, such as coal-based applications. Hence, in this study, a biomass experiment utilizing a thermogravimetric analyzer was conducted to obtain varying reaction rate data over carbon conversion, which may then be used to simulate the biomass conversion model and 3D simulation was also conducted for a 500 MWe coal-biomass cofiring boiler. Gasification was obtained at 1000 degrees C and 1200 degrees C using CO2 at constant temperature for different biomasses. Compared to the peak exhibited by the random pore model, biomass gasification reaction rates shifted into the later stage of the reaction, thereby yielding irregular reaction rate developments and poor prediction accuracies. With flexibility-enhanced random pore model(FERPM), we observed that correlation factors increased from the previously reported value of 0.7-0.95. In the coal-biomass cofiring boiler, the difference between the Kinetics/Diffusion-limited model and FERPM in biomass combustion aspect was examined, and it was ultimately determined that characteristics of particle reactions through FERPM are valid in 3D analysis. Therefore, this paper proposed a flexibility-enhanced random pore model proven to enhance the prediction accuracy of a simulation.