Estimation of Gross Calorific Value of Wood Pellet Using Multiple Regression Analysis

Dulong, Steuer and Scheurer-Kestner equations have been widely used to predict the gross calorific value of a solid fuel. However, these equations require the additional analysis for the contents of sulfur and oxygen. The objective of this study is to develop the model predicting the gross calorific value from the contents of carbon, hydrogen, nitrogen and ash within a wood pellet sample. Wood pellet samples obtained from five countries (Korea, Vietnam, Malaysia, Indonesia, and Russia) were analyzed for the contents of carbon, hydrogen, nitrogen and ash in 2023. A regression model predicting the gross calorific value was then developed. The regression model was evaluated using wood pellet samples obtained from six countries (Korea, Vietnam, Malaysia, Indonesia, Russia, and Thailand) in 2024. It was found that the regression model appropriately predicts the gross calorific value of wood pellet samples, as 57 out of 60 wood samples analyzed in 2024 fell within the 95% prediction interval of the model. It was also found that all Korean wood pellet samples analyzed in 2024 fell within the 95% prediction interval of the regression model.