Artificial neural networks modelling for biodiesel production from waste cooking oil

Year 2020, Volume: 7 Issue: 3, 74 - 80, 05.10.2020

Suleyman Karacan Büşra Gedikaslan Mehmet Çağatay

https://doi.org/10.31593/ijeat.675275

Abstract

The objective of the present work is to develop models inculcating the effect of operating conditions of waste cooking oil methyl esters production in the reactive distillation column, namely waste cooking oil (WCO) flow rate, methanol/WCO molar ratio, reboiler heat duty and feed inlet temperature on the estimation of parameters like the biodiesel conversion by using Artificial Neural Networks technique. In our study, at the maximum biodiesel conversion of 99.48% and at steady state time of 1.69 hour were determined as WCO flow rate of 2.90 ml/min, methanol/oil molar ratio of 8.19 and reboiler heat duty of 0.419 kW. Experiments were conducted in the laboratory and the results obtained were used to develop the ANN model using MATLAB. The developed model was in good agreement with the experimental values.

Keywords

Biodiesel, artificial neural network, Simulation, Waste cooking oil

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