Prediction of higher heating value of solid fuel produced by hydrothermal carbonization of empty fruit bunch and various biomass feedstock

There are many influencing variables when it comes to designing a thermal conversion system for biomass and other fuels. One of the most important factors is the higher heating value (HHV). HHV is commonly measured using a bomb calorimeter; however, in order to reduce analysis costs, many correlation models have also been developed to estimate HHV. Various models have been proposed in existing literature to predict the HHV of biomass and other fuels based on proximate and ultimate analysis composition. Unfortunately, correlations for the prediction of the HHV of fuels using the hydrothermal carbonization process or hydrochar are still difficult to find in open literature. In this study, two new correlations based on proximate and ultimate analysis of biomass and hydrothermally carbonized biomass (hydrochar) used for the prediction of HHV are presented. The multiple linear regression method is used to generate correlations from data on biomass collected from open literature. It was found that the correlation derived from the ultimate analysis (HHV = 0.441 C − 0.043 O) is more accurate than that derived from proximate analysis, since the former has the lowest average absolute error and an average bias error below 1.