Optimal tuning of a thermo-chemical equilibrium model for downdraft biomass gasifiers

A thermo-chemical equilibrium model is applied to predict the released syngas composition, char, tar content and temperature in biomass gasifiers. The accuracy of the model results is improved by proper calibration, namely by modifying the equilibrium constants through correction factors that represent the degree of approach of the analyzed system to equilibrium. To this aim, the developed model is coupled with a genetic algorithm (MOGA II), to search for the optimal correction factors able to minimize the error between the computed and the experimentally measured product yields and temperatures. The approach is repeated to simulate the thermal treatment of different biomasses with increasing carbon content, from straw to sawdust. The possibility to resort to a unique set of correction factors for different biomasses is explored, that would allow the model being of particular interest for engineering applications, to trace the design guidelines for gasification systems.