Prediction model of higher heating value of torrefied biomass based on the kinetics of biomass decomposition

• The HHV prediction model was developed base on kinetics of one-step decomposition.
• The cassava rhizome (Manihot esculenta species) was used as feedstock in this study.
• The parameter “HHVc” was introduced to determine the HHV of torrefied char.
• The average absolute error of the HHV prediction model was 7.03%.

This work presented the Higher Heating Value (HHV) prediction model of torrefied biomass based on the kinetics of biomass decomposition. The prediction values were compared with experimental data of torrefied cassava rhizome (Manihot esculenta species). Moreover, the model developed in this work was used to explain the effect of torrefaction temperature and residence time on the heating value of the torrefied biomass. The results show that the HHV prediction model gave an over prediction value compared to the HHV obtained by the bomb calorimeter. The average absolute error of the HHV prediction model was 7.03%. At the beginning of torrefaction, the HHV of the torrefied biomass rapidly increased when residence time increased. When a certain residence time was reached, the HHV tended to asymptote to a constant value, i.e. HHV at termination point of thermal degradation reaction (HHVc). The value of HHVc strongly depended on the torrefaction temperature. Increasing of HHVc and decreasing of residue mass (Mt) resulted in increasing of HHV of torrefied biomass. The model developed in this work gave a clear view of the change of HHV at various conditions of torrefaction temperature and time. This understanding leads to production planning with an efficient use of energy in torrefaction process.