4.7 Article

Empirical and chemical equilibrium modelling for prediction of biomass gasification products in bubbling fluidized beds

Journal

ENERGY
Volume 202, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2020.117654

Keywords

Biomass; Bubbling fluidized bed; Gasification; Producer gas; Chemical equilibrium; Empirical modelling

Funding

  1. Portuguese Foundation for Science and Technology [POCI-01-0247-FEDER-021874, CENTRO-01-0145-FEDER-000005, PD/BDE/128620/2017]
  2. CESAM [UID/AMB/50017/2019]
  3. FEDER, within the PT2020 Partnership Agreement
  4. FEDER, within Compete 2020
  5. Navigator Company [PD/BDE/128620/2017]
  6. Fundação para a Ciência e a Tecnologia [PD/BDE/128620/2017] Funding Source: FCT

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In this work, two approaches to predict the producer gas composition obtained by direct (air) biomass gasification in bubbling fluidized beds were developed and compared, namely empirical modelling based on reported experimental results in the literature and non-stoichiometric chemical equilibrium modelling. For this purpose, an extensive database containing a set of 19 published experimental results from the literature was compiled and a non-stoichiometric chemical equilibrium model developed. The prediction capability of the empirical and chemical equilibrium model was evaluated by comparison with experimental data obtained in an 80 kW(th) bubbling fluidized bed direct (air) biomass gasifier. The empirical model shows moderate accuracy in the determination of the producer gas composition (CO, H-2 and CH4), whereas the chemical equilibrium clearly overestimates the concentration of H-2 and CO, and underestimates the concentration of CH4, leading to subpar accuracy in the determination of typical gasification efficiency parameters. Thus, the empirical model is suited for preliminary estimates of gasification products, while black-box chemical equilibrium modelling, without experimental knowledge integration, is considered as unreliable for these gasification conditions. (C) 2020 Elsevier Ltd. All rights reserved.

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