Prediction and optimization of syngas production from a kinetic-based biomass gasification process model

Abstract

This work presents a robust method for prediction and optimization of syngas production by taking advantage of the established kinetic-based process model and data analysis techniques for constructing a surrogate model. Compared with the widely-used equilibrium model, herein, we first develop a process model of biomass gasification by incorporating updated biomass reaction kinetics and dense bed hydrodynamics. A parallel comparison of model predictions and experimental results illustrates a good agreement under a wide range of operating conditions. The sensitivity results indicate that the initial volatile composition from the pyrolysis step is crucial for final gas product distribution and the gasification temperature is most sensitive to the syngas composition and yield, followed by the equivalence ratio (ER), steam-to-biomass ratio (S/B ratio), and biomass moisture content (MC). More importantly, a multivariable analysis is further carried out by running the model for 864 combinations of four input parameters. A surrogate model is established for predicting and optimizing the syngas yield under various operating conditions. A selective set of response surfaces illustrates the mutual effects of two parameters simultaneously and reveals optimal syngas yields ranging from 61.4 vol% to 78.5 vol% on a dry N2-free basis. The global optimization model demonstrates a maximum syngas yield of 78.6 vol% at a temperature of 900 °C, ER of 0.23, S/B ratio of 0.21, and MC of 30 wt%.