Calculating the Calorific value of biomass from its elemental states

Abstract

Biomass is an indirect source of solar energy and its renewable in nature. During the numerical simulations in thermo-chemical conversion systems for biomass, its calorific value is very vital. Over the years, a number of formulae have been proposed in the literature to estimate the calorific value of biomass fuels from its elementary components. These methods include proximate, ultimate and chemical analysis. In this thesis, a larger data base of biomass samples collected from the open literature was used to evaluate the correlations of these methods using statistic regression analysis. The results showed that the correlations based on the linear regression analysis is more accurate compared to that based on the non-linear regression. The low accuracy of previous correlations was attributed to limited samples used during their derivation.

In order to achieve a higher accuracy, new correlations were proposed to estimate the calorific value by regression analysis based on present data base. This new correlation between the calorific value and elemental components of biomass could be employed to estimate the calorific value from regression analysis. The new formula based on the composition of main elements (wt / %; carbon (C), hydrogen (H), oxygen (O), nitrogen (N) and Sulphur (S) based on non-linear regression analysis is;-0.02C + 0.75 H- 0.01 C x H – 0.001 O – 0.130 x N + 5.04 N + 31.6 S x O +22.32 C – 46.22 = Calorific value (MJ/Kg). The R- squared value is 0.985