Neural network modeling of biomass gasification for hydrogen production

ABSTRACT

Hydrogen plays a significant role as an alternative feedstock in the production of several industrial chemicals such as methanol and ammonia; it can also be used as a clean fuel for power generation in the Internal Combustion (IC) engines and Proton Exchange Membrane (PEM) fuel cells. The main objective of this work is to develop a computer-based model based on the experimental data to predict the gasification behavior of biomass particles for hydrogen and syngas production. The results showed that an increase in gasification temperature significantly increased the hydrogen yield and CGE. The maximum CGE also found to be increased by about 230% when the reaction temperature increases from 700 to 900 ^◦C.

KEYWORDS:

• ANN
• hydrogen
• gasification
• CGE
• CCE