(569di) Modeling of a Heat-Integrated Biomass Downdraft Gasifier: Tuning of Key Model Parameters Using Experimental Data

Biomass gasification using woody biomass is a promising method for replacing fossil fuel for power generation in isolated communities, providing a more sustainable and almost carbon-neutral source of energy. A model for a heat-integrated biomass downdraft gasifier is developed and used to predict the process gas temperature, flow rate and composition. This ordinary differential equation (ODE) model accounts for reaction kinetics of pyrolysis, combustion and gasification along with heat transfer phenomena inside the gasifier and heat integration system. The ODEs are solved as a boundary value problem (BVP), ensuring that conditions for the producer gas at the bottom of the reactor match the conditions of the countercurrent annulus gas used for heating. This model contains 40 adjustable parameters that were selected from the literature. A two-step approach is used to tune key parameters in the downdraft gasifier model using pine wood as the feedstock. The first step is to rank the 40 model parameters from the most estimable to the least estimable based on sensitivity information and initial parameter uncertainties. The second step is to pick the appropriate number of parameters to estimate to achieve reliable model predictions. As a result, 27 parameters are tuned using data from 15 experimental runs and 13 parameters are kept at their initial values. A diagnosis of the 13 low-ranked parameters reveals that 8 parameters are not estimated due to correlation with high-ranked parameters and that 5 parameters have little influence on the model predictions. The model is validated using two runs that were not used for parameter tuning. The updated model is used to predict that a taller gasifier would not improve the quality of the producer gas exiting the gasifier. Simulations of gasifier operation with higher producer gas demand result in producer gas with higher CO, lower H₂ and higher tar content.