Prediction of higher heating values of biomass from proximate and ultimate analyses

Two new empirical correlations based on proximate and ultimate analyses of biomass used for prediction of higher heating value (HHV) are presented in this paper. The correlations have been developed via stepwise linear regression method by using data of biomass samples (from the open literature) of varied origin and obtained from different geographical locations. The correlations have been validated via incorporation of additional biomass data. The correlation based on ultimate analysis (HHV = 0.2949C + 0.8250H) has a mean absolute error (MAE) lower than 5% and marginal mean bias error (MBE) at just 0.57% which indicate that it has good HHV predictive capability. The other correlation which is based on proximate analysis (HHV = 0.1905VM + 0.2521FC) is a useful companion correlation with low absolute MBE (0.67%). The HHV prediction accuracies of 12 other correlations introduced by other researchers are also compared in this study.