Estimating The Correlation Between The Calorific Value And Elemental Components Of Biomass Using Regrassion Analysis
The calorific value is one of the most important properties of biomass fuels for design calculations or numerical
simulations in thermo chemical conversion systems for biomass. There are a number of formulae proposed in the literature to
estimate the calorific value of biomass fuels from its elementary components by i.e. proximate, ultimate and chemical
analysis composition. In this project, these correlations were evaluated statistically by Regression Analysis using SPSS
software based on a database of biomass samples collected from the open literature. It was found that the correlations based
on linear multiple regression analysis is the most accurate.The correlation between the Calorific value and elemental
components of biomass could be conveniently used to estimate the Calorific Value from Regression analysis. The data points
considered for correlation by regression analysis ranges in carbon content from (27.80% to 92.70)%, hydrogen content (0.10
to 8.80)%, oxygen content (0.20 to 49.50)%, nitrogen content (0.00 to 5.95)% and sulphur (0.00 to 1.05) wt. % on dry basis,
the derived correlation can be accepted as ‘general correlation’ for the estimation of calorific value of biomass from its
elemental components within the above specified ranges..
Keywords: Biomass, Calorific Value, Regression Analysis, Correlation.