Journal
ENERGY CONVERSION AND MANAGEMENT
Volume 286, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2023.117070
Keywords
Multi-scale modelling; Particle model; CFD; Fluidized bed; Biomass; Gasification
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This study applies a multi-scale modelling approach to a fluidized bed biomass gasifier of industrial size for the first time. The results are compared with a simulation using a simplified uniform conversion model (UCM), which is commonly used in literature. The validation at the particle level shows that the UCM underpredicts the time needed for pyrolysis, while the progressive conversion model (PCM) is in good agreement with experimental data. The coupled simulations using PCM demonstrate the numerical feasibility of the modelling approach and highlight the importance of a comprehensive description of the particle level.
Fluidized bed biomass gasification is a complex process whereby gas source terms are released by reactions at the particle level during the movement of fuel particles throughout the reactor. The current study presents for the first time the application of a multi-scale modelling approach for a fluidized bed biomass gasifier of industrial size, coupling a detailed one-dimensional particle model based on the progressive conversion model (PCM) with a commercial CFD software. Results of particle movement and gas source terms are compared with results of an additional simulation employing the simplified uniform conversion model (UCM) which is commonly used in literature. Validation at the particle level showed that the UCM leads to a massive underprediction of the time needed for pyrolysis whereas the PCM is in good agreement with experimental data. This heavily influences the gas sources released during pyrolysis of the biomass particles in the coupled reactor simulations. Volatiles are much more concentrated to the close proximity of the fuel feed when using the UCM whereas the PCM leads to a more homogeneous distribution over the reactor cross-section. The calculation time analysis of the coupled simulations showed that despite the increased complexity, the PCM shows only an increase of 20% in calculation time when compared to the UCM, whereas it is much better suited for these conditions. The coupled multi-scale simulations using the PCM showed the numerical feasibility of the modelling approach for 1,200,000 bed parcels and about 80,000 reacting fuel parcels and furthermore highlighted the importance of a comprehensive description of the particle level.
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