Process modeling and optimization of biomass solar gasification for hydrogen production

Abstract

This study presents a numerical investigation of biomass gasification aimed at maximizing hydrogen production through the evaluation of different feedstocks, catalysts, insulation materials, and operating conditions. A numerical model based on Python was developed to estimate syngas composition based on temperature dependent reaction kinetics and process parameters such as the steam-to-biomass ratio. Three different biomass types were analyzed alongside three catalysts. The results show a clear enhancement in hydrogen yield with increasing the steam to biomass ratio, attributed to the intensification of steam reforming and water-gas shift reactions. For instance, hydrogen volume fraction increased from 14.5% to 37% for wood and from 16.9% to 41.4% for straw as SBR rose from 0.2 to 1.0. Catalyst performance also played a significant role, with Ni/Al<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>O<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</inf> providing the highest hydrogen output across all biomass types. Additionally, insulation materials had a considerable impact on thermal retention and hydrogen yield, with ceramic fiber outperforming other materials. Algae biomass, tested in comparative analysis, demonstrated superior hydrogen production potential compared to straw and wood. These findings provide useful insights for optimizing biomass gasifier design and operation for sustainable hydrogen production.