An Overview of the Biomass Torrefaction Technology and Characterization of Solid Waste Fuels

Abstract

Torrefaction has been shown to increase the energy density, stability, and handling properties of biomass, making it a more suitable feedstock for use in power generation and other applications. This paper reviewed the torrefaction of biomass solid waste and its energy content using ultimate, proximate, calorific value, and volatile matter content analyses to check biomass-specific compositions. The diverse biomass feedstocks are agricultural residues, forestry residues, energy crops, leaves, fruit wastes, and sewage sludge. Biomass torrefaction approaches and torrefied solid fuels were discussed with their essential constituents. Torrefied products were characterized using torrefaction principles and mathematical modelling to estimate the exact quantity and quality. The significance of machine learning approaches to predicting energy content was stated. The bulk density content of the torrefied biomass is increased with an increment in torrefaction temperature, resulting in an increase in the porosity property modelling, thereby improving its grindability status and energy content. Machine learning algorithms served as predictive models for the quality of the torrefied biomass. It provides valuable insights into the accuracy and efficiency of trusted techniques for predicting energy contents and their potential for industrial applications.