The quality analyses of olive cake fuel pellets – mathematical approach

Abstract

This article investigates the effect of processing parameters (conditioning temperature and binder content), on final quality of produced agro-pellets for heat energy generation, obtained from four different olive cultivars using different technological parameters. Technological, physical and chemical properties of pellets (carbon, hydrogen, nitrogen and sulphur content, particle density, abrasion length, moisture, ash content, higher and lower heating values, fixed carbon and volatile matter content) have been determined to assess their quality. The performance of Artificial Neural Network (ANN) was compared with the performance of second order polynomial (SOP) model, as well as with the obtained experimental data in order to develop rapid and accurate mathematical model for prediction of final quality parameters of agro-pellets. SOP model showed high coefficients of determination (r 2 ), between 0.692 and 0.955, while ANN model showed high prediction accuracy with r 2 between 0.544 and 0.994.