Estimation of Gross Calorific Value of Coal from Its Proximate Analysis Using Non-Linear Regression Analysis

Abstract

The gross calorific value (GCV) is an important property defining the energy content of coal. There exists a variety of correlations for the estimation of coal calorific value based on ultimate analysis. However, the ultimate analysis is expensive and needs special instrument. Therefore, in this study, the relationship between the proximate analysis of coal samples and their GCVs have been investigated using a multivariate non-linear regression analysis. A high degree of correlation between actual and predicted GCVs was observed. The non-linear regression model was also compared with the published correlations. The proposed in this study is highly promising for use in designing and operating of thermolysis process and offers capability to compute GCV of any coal samples from its proximate analysis.