Characterization and optimization of calorific value of low grade coal by statistical experiment and modelling

Abstract

The effects of environmental factors (temperature, humidity, and airflow) on gross calorific value (GCV) and proximate analysis of low grade coal were systematically investigated. The factorial experiments were conducted according to the statistical experimental design. The results were empirically modeled, statistically tested, and experimentally verified to quantify the change in GCV and proximate analysis of coal directed by environmental factors. The GCV of the coal were most affected by the humidity followed by the temperature. The GCV was increased from 5,365 to 5,986 (kcal/kg) through the decrease in humidity from 80 to 29 (% R.H.) and increase in temperature from 28 to 36 (°C). This increase in GCV could be attributed to the decrease in moisture content of the coal from 16.2 to 7.1 (%). Also, the optimized environmental conditions were identified where GCV ≈ 6,000 kcal/kg of the coal could be obtained. This study can be helpful in (i) managing the variability in GCV of a coal at different places, environment, and weather conditions and, thereby, settling the disputes between buyers and sellers over its variability and (ii) in maintaining the optimum conditions to enhance the GCV of the low grade coal in the power plants.