Evaluating HHV Prediction Equations Using Proximate and Ultimate Analyses

Biomass, in rural areas, is obtained through variety of crops and biomass residues from forestry, agriculture and the agro-industry and is an abundantly available fuel source. Usage of biomass residue as a solid fuel result in air pollution affects both indoor and outdoor environments. Considering the pollution problem and many more, gasification emerges as an environmentally and economically fit alternative to conventional biomass combustion. The current study evaluates the potential of various biomass resources as fuel source by analyzing their calorific values, proximate and ultimate values. Wheat straw, paddy straw (PB-370, PR-1121, PR-44 and PR-126), maize and bajra were chosen for analysis due to their abundance in Punjab. Proximate and ultimate analysis values are used to predict higher heating value (HHV) from twelve different equations (six from proximate values and six from ultimate values). The investigation conducted in this study delved into a comprehensive analysis of predicted HHV calculations derived from various equations, which provide significant insights into the energy potential of the examined biomass. A comprehensive evaluation of the equations was performed in this study, utilizing statistical measures including R2, mean absolute error (MAE), and mean bias error (MBE). Equation 3.3, which clarifies the relationship between HHV and volatile matter and fixed carbon, appeared to be the most promising from the perspective of proximate analysis. It demonstrated a significant R2 of 0.87, although it did contain a noteworthy overestimation (MBE = 7.5). In contrast, within the context of ultimate analysis, Eq. 4.1 exhibited enhanced predictive accuracy by integrating multiple elemental components (MBE = 10.83) and having an R2 of 0.82.