Numerical Analysis of Tar and Syngas Formation during the Steam Gasification of Biomass in a Fluidized Bed

Abolhasan Hashemisohi, Lijun Wang () and Abolghasem Shahbazi
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Abolhasan Hashemisohi: Department of Computational Data Science and Engineering, North Carolina Agricultural and Technical State University, 1601 East Market Street, Greensboro, NC 27411, USA
Lijun Wang: Department of Natural Resources and Environmental Design, North Carolina Agricultural and Technical State University, 1601 East Market Street, Greensboro, NC 27411, USA
Abolghasem Shahbazi: Department of Natural Resources and Environmental Design, North Carolina Agricultural and Technical State University, 1601 East Market Street, Greensboro, NC 27411, USA

Energies, 2023, vol. 16, issue 14, 1-13

Abstract: A sequential modular hydrodynamic model integrated with detailed reaction kinetics (SMHM-RK) was developed and validated to predict tar and syngas components produced by the steam gasification of biomass in a fluidized bed gasifier. The simulations showed that the prediction accuracy is sensitive to both models for hydrodynamics and reaction kinetics. The simulations showed that the tar composition predicted by the SMHM-RK was more close to the measured values than those predicted by the well-mixed hydrodynamic model integrated with the same reaction kinetics (WMHM-RK). The predictions showed that the total tar decreased, but the polycyclic aromatic tar compounds increased with the increase in gasification temperature. There was an optimum steam-to-biomass ratio (SBR) for minimizing tar formation. The simulations found that the contents of total tar and heavy tar compounds decreased by increasing the SBR from 0.3 to 0.9, and then increased by further increasing the SBR. The injection of a small amount of oxygen in steam gasification cannot reduce tar formation. The injection of oxygen in steam gasification changed the reaction pathways of naphthalene to produce more naphthalene in the syngas. The de-volatilization rate affects pyrolytic volatile compositions and subsequent tar formation. Therefore, biomass devolatilization and homogeneous gas reactions should be solved simultaneously to accurately predict the syngas and tar composition.

Keywords: fluidized bed; biomass gasification; tar reduction; reaction kinetics; mathematical modeling; sequential modular model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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