Simulation of the Catalytic Gasification of Banana Biomass in the Production of Hydrogen, Using Glucose as a Model Compound

Abstract

Abstract: In the face of the climate change problem caused by fossil fuels, it is essential to seek efficient alternative energies with a lower environmental impact that are derived from renewable resources. Biomass gasification technology continues to generate significant interest in sustainable energy research as an alternative to traditional combustion technology. Gasification involves the thermochemical conversion of raw materials, resulting in a highly valuable gaseous product known as synthesis gas, commonly used as a fuel. Its numerous advantages include the availability of raw materials, the reduction in harmful emission streams, performance, and costs. As this topic gains momentum in the global energy framework, it is imperative to advance the maturity of this technology by addressing its weaknesses, primarily in terms of efficiency. The objective of this project was to investigate the hydrogen production process through the simulation of glucose gasification as a representative compound for biomass. This was achieved by conducting an integrated simulation of glucose gasification, encompassing both the heat transfer in the external system and the conversion of glucose into hydrogen gas, using the results obtained in the external system as initial conditions. Interrelated aspects of this complex process, including heat transfer and the kinetics of the gasification process, were modeled. Glucose was selected as the model compound due to its availability, simplicity, fundamental understanding, reproducibility, comparability, knowledge of reaction pathways, and simplification of mathematical models. The simulation resulted in a H2:CO ratio of 2.2, and molar fluxes were obtained for H2, CO, CO2, CH4, and H2O consistent with those typically observed in the gasification process of organic ma􀀻er. These models were constructed, laying the foundation for the adaptability of subsequent optimization studies.