Simulation of the Steam Gasification of Japanese Waste Wood in an Indirectly Heated Downdraft Reactor Using PRO/II™: Numerical Comparison of Stoichiometric and Kinetic Models

• Published in: Energies (Basel) Vol. 15; no. 12; p. 4181
• Main Authors: Talero, Gabriel, Kansha, Yasuki
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.06.2022
• Subjects: Alternative energy sources; Biomass; Carbon; Carbon cycle (Biogeochemistry); Composition; Deforestation; Design; Downdraft; Emissions; Energy industry; Equilibrium; equilibrium model; error; Errors; Evaluation; Food security; Gasification; kinetic model; Lignin; Mass ratios; Organic chemicals; Petrochemicals; Reaction mechanisms; Reactors; Simulation; Solar energy; Steam; Stoichiometry; Synthesis gas; Topology; Wood waste; Japan
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en15124181

The conversion of biomass to olefin by employing gasification has recently gained the attention of the petrochemical sector, and syngas composition is a keystone during the evaluation of process design. Process simulation software is a preferred evaluation tool that employs stoichiometric and kinetic approaches. Despite the available literature, the estimation errors of these simulation methods have scarcely been contrasted. This study compares the errors of stoichiometric and kinetic models by simulating a downdraft steam gasifier in PRO/II. The quantitative examination identifies the model that best predicts the composition of products for the gasification of Japanese wood waste. The simulation adopts reaction mechanisms, flowsheet topology, reactions parameters, and component properties reported in the literature. The results of previous studies are used to validate the models in a comparison of the syngas composition and yield of products. The models are used to reproduce gasification at temperatures of 600∼900 °C and steam-to-biomass mass ratios of 0∼4. Both models reproduce experimental results more accurately for changes in the steam-to-biomass mass ratio than for temperature variations. The kinetic model is more accurate for predicting composition and yields, having global errors of 3.91%-mol/mol and 8.16%-g/gBM, respectively, whereas the simple stoichiometric model has an error of 7.96%-mol/mol and 16.21%-g/gBM.