Simulation of biomass to syngas: Pyrolysis and gasification processes

This chapter reviews previous simulations of gasification and pyrolysis processes based on equilibrium and kinetic models. However, most of these studies only consider the composition of the gas and its lower heating value (LHV), ignoring efficiency parameters such as Ygas, hot gas efficiency (HGE), and cold gas efficiency (CGE). Therefore, this book chapter also uses the findings and methodology of prior works to simulate the gasification of blends of high-density polyethylene (HDPE) with pine chips, considering efficiency parameters. The equilibrium model is based on the direct minimization of Gibbs free energy with phase splitting to calculate equilibrium and equilibrium ratios. The kinetic model divides the process into three major stages: pyrolysis, oxidation, and reduction. Both simulations provide gas composition, gas LHV, and efficiency parameters. The models consider three distinct blends (0, 25, and 50% wt. HDPE), with a fixed equivalence ratio (ER) of 0.25. The gasification and pyrolysis simulation results were compared with experimental results developed at the University of Aveiro, using pine chips as raw material. It is shown that the equilibrium model offers LHV similar to the experimental values, but gas composition values are quite different than the experimental values. Furthermore, it assumes tars are not formed, resulting in higher Ygas than experimental results. On the other hand, the kinetic model yields extremely near the experimental gas composition, especially for CO2, CO, CH4, and C2H4. However, the produced gas LHV is higher than the experimental values, resulting in higher HGE and CGE than experimental results. Finally, an empirical model developed based on a system of linear equations is analyzed regarding pyrolysis. The results of the wood pyrolysis are compared with experimental results under the same conditions. Furthermore, some points to optimize are proposed, based on the analysis of the pyrolysis and gasification processes.