Kinetic Modeling and Optimization of Biomass Gasification in Bubbling Fluidized Bed Gasifier Using Response Surface Method - Tolossa Kebede Tulu; Samson Mekbib Atnaw; Robera Daba Bededa; Demeke Girma Wakshume; Venkata Ramayya Ancha (Center of Biomass & Renewable Energy, Diponegoro University, 2022)
This paper presents the kinetic modeling of biomass gasification in bubbling fluidized bed (BFB) gasifiers and optimization methods to maximize gasification products. The kinetic model was developed based on two-phase fluidization theory. In this work, reaction kinetics, hydrodynamic conditions, convective and diffusion effect, and the thermal cracking of tar kinetics were considered in the model. The model was coded in MATLAB and simulated. The result depicted good agreement with experimental work in literature. The sensitivity analysis was carried out and the effect of temperature ranging from 650 to 850 and steam to biomass ratio (S/B) ranging from 0.1 to 2 was investigated. The result showed that an increase in temperature promoted H2 production from 18.73 % to 36.87 %, reduced that of CO from 39.97 % to 34.2 %, and CH4 from 18.01 % to 11.65 %. Furthermore, surface response was constructed from the regression model and the mutual effect of temperature and S/B on gasification products and heating value was investigated. In addition, the desirability function was employed to optimize gasification product and heating value. The maximum gasification product yield was obtained at 827.9 and 0.1 S/B. The response predicted by desirability function at these optimum operational conditions was 30.1 %, 44.1 %, 13.2 %, 12.9 %, 14.035 MJ/Nm3, and 14.5 MJ/Nm3 for H2, CO, CO2, CH4, LHV, and HHV, respectively. Kinetic modeling of the biomass gasification in BFB process is still under development, which considers the diffusion effect, tar cracking, reaction kinetics, and hydrodynamic behavior. Moreover, the large number of previous studies gave priority to a single parameter investigation. However, this investigation can be extended to various parameters analysis simultaneously, which would give solid information on system performance analysis.