Development, simulation and ANN validation of thermodynamic and kinetic models for optimised biomass gasification for CO2 reduction and enhanced syngas yield

Extensive use of fossil fuels causes environmental degradation as well as an energy crisis. Despite past research efforts, biomass remains one of the most promising resources due to its ease of availability, high energy content and low-emission fuels. In the present study, the stoichiometric equilibrium minimum Gibbs free energy method is developed to describe a detailed chemical conversion process of pine needles. The primary objective of this study is to optimise process parameters, including reactor temperature, gasifying medium (air, steam, and oxygen), equivalence ratio and steam-to-biomass ratio. A significant advancement in this optimisation is to enrich the synthesis gas as well as to reduce carbon dioxide emissions based on mass and energy balancing in the gasification system. Further, computational models are developed based on equilibrium method-optimised process parameters. The primary objective of developing these models is to optimise the various design parameters, including reactor configuration, specifically the height and diameter, as well as the mass flow rate of biomass and air, particle size and residence time, aiming to enrich the syngas quality. At the end, these model results are validated using the artificial neural network model. As a result, the producer gas compositions comprise 18.5 % carbon monoxide, 22.5 % hydrogen, 12.3 % carbon dioxide, and 2.0 % methane mole fractions when air is used as a gasifying medium. Further, the producer gas compositions are increased to 42.4 % carbon monoxide, 36 % hydrogen, and 3 % methane, and there is an 11.5 % reduction in carbon dioxide mole fractions when oxygen is used as a gasifying medium.