Optimization, production, and environmental sustainability of clean energy fuel utilizing reused cooking oil employing CaO catalysts

Abstract

The low free fatty acid content waste cooking oil, was collected from the MANIT canteen, and employed during this study. The transesterification process parameters were enhanced, and the biodiesel yield was optimized using response surface methodology, artificial neural networks, and genetic algorithms. Three key process variables were considered including reaction time (minutes), reaction temperature (°C), and the methanol to oil concentration ratio (mol/mol), with the addition of 1 gm of catalyst and a magnetic stir speed of 500 rpm. The optimal reaction conditions were determined to be an optimal methanol to oil ratio of 8.45 (mol/mol), a reaction time of 97 min, and a reaction temperature of 56 °C, resulting in a biodiesel yield of 92.26 % when using response surface methodology. Notably, the study findings indicate that the genetic algorithm, coupled with the backpropagation neural network model, exhibits strong predictability, achieving an optimal biodiesel production efficiency of 94.21 %. Furthermore, the quality of the biodiesel produced was examined and compared against the standardized ASTM biodiesel specifications. The results suggest that the thermophysical properties of the biodiesel closely aligns with that of conventional diesel fuel which can be used as blended fuel in diesel engine.