Abstract
The climate crisis and dependence on fossil fuels make the transition to renewable energy sources imperative, with biomass standing out for promoting decarbonization and circular economy. In this context, fluidized bed gasification emerges as an efficient route for converting waste into syngas, applicable to power and hydrogen generation. Given the variability of real operating conditions, dynamic models are essential to represent coupled fluid dynamic, thermal, and kinetic phenomena over time. In this work, a dynamic phenomenological model was developed using a lumped 0D approach, in which the reactor is divided into two interacting zones represented as continuous stirred-tank reactors (CSTRs): a dense bed, where drying, devolatilization, and heterogeneous reactions occur, and a freeboard, dominated by homogeneous gas-phase reactions. The model was validated against experimental data from a bubbling fluidized bed gasifier, showing good agreement for major syngas species (CO and H2, mean absolute error below 2%), with minor deviations for CH4 due to simplified devolatilization and tar conversion kinetics. Transient simulations revealed strong sensitivity of process performance to particle size and biomass composition. Compared with the reference case (6 mm), reducing particle size to 1 mm enhanced hydrogen gas efficiency, cold gas efficiency, and carbon conversion due to intensified heterogeneous reactions and improved solid-gas heat transfer. Additionally, biomass switching simulations demonstrated that real-time air flow control effectively stabilizes syngas quality under feedstock variability. Overall, the model provides a computationally efficient tool for process optimization, control strategy development, and integration of biomass gasification into flexible and hybrid low-carbon energy systems.