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Combined parametric modelling of biomass devolatilisation process

Author

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  • Erić, Aleksandar
  • Cvetinović, Dejan
  • Milutinović, Nada
  • Škobalj, Predrag
  • Bakić, Vukman

Abstract

Devolatilisation is a process of volatile components formation that takes place immediately after the drying process and precedes combustion or gasification. The paper presents the procedure for determining the composition of devolatilisation products on the wheat residue biomass sample. The components considered devolatilisation products are carbon monoxide, carbon dioxide, hydrogen, water vapor, hydrogen sulfide, ammonia, ethene, methane, and tar. The procedure relies on two independent models that adopt two distinct principles. The first model of energy and mass balance does not consider the analysis of the influence of temperature, and therefore the system is indeterminate. The second model that involves the temperature influence is based on defining the equilibrium composition of gaseous components of the devolatilisation process by applying the principle of minimum Gibbs function. This model gives the gas-phase composition of the water/carbon dioxide, carbon monoxide/carbon dioxide, and hydrocarbons/carbon dioxide systems. Combining these two models using an iterative procedure leads to an exact composition of the devolatilisation products, including tar as a condensed product. The analysis was performed in the temperature range of 700–950 K. The model is validated against already published numerical and experimental work and presented a high level of agreement. The main advantage of the proposed combined parametric modelling relies on the simplicity of its input data which refers to the proximate and the ultimate analysis of the biomass feedstock.

Suggested Citation

  • Erić, Aleksandar & Cvetinović, Dejan & Milutinović, Nada & Škobalj, Predrag & Bakić, Vukman, 2022. "Combined parametric modelling of biomass devolatilisation process," Renewable Energy, Elsevier, vol. 193(C), pages 13-22.
    • Handle: RePEc:eee:renene:v:193:y:2022:i:c:p:13-22
    DOI: 10.1016/j.renene.2022.04.129
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