Modeling and optimization of biodiesel production process from waste cooking oil using response surface methodology

Subject Areas : Renewable Energy

Ahmad Abbaszadeh-Mayvan ¹ (Assistant Prof., Department of Biosystems Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Gorgan, Iran. *(Corresponding Author))
Abbas Rezaei asl ² (Associate Prof., Department of Biosystems Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Gorgan, Iran.)
Ahmad Taghizadeh-Alisaraei ³ (Associate Prof., Department of Biosystems Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Gorgan, Iran.)

Received: 2023-04-27 Accepted : 2024-01-10 Published : 2024-06-21

Keywords: Waste cooking oil, Response surface methodology, Optimization, Fuel characterization.,

Abstract :

Background and Objective: Nowadays, due to environmental concerns and energy crises, the use of biofuel resources such as biodiesel has become very important. Therefore, the main goal of the current study is to investigate, model and, find the optimal conditions for the biodiesel production process from waste cooking oils using the response surface method.

Material and Methodology: RSM based on Box-Behnken was applied to investigate, model and, optimize the influence of reaction parameters, such as methanol to oil ratio (3:1–9:1 m/m), catalyst concentration (1–2 w/w%), and reaction temperature (45–55 ), on biodiesel yield from waste cooking oil (WCO). According to the DOE, all 17 runs were performed after applying the same reaction conditions (mixing 600 rpm and reaction time 75 min) and the biodiesel yield was considered as a response.

Findings: Based on the modeling results, the coefficient of determination, standard error and, coefficient of variation (C.V) of the regression model was 97.40%, 0.827 and 0.882%, respectively. The ANOVA results showed that all selected parameters of oil-methanol ratio, catalyst concentration and, reaction temperature had a significant effect on biodiesel yield. The results of the optimization process showed that the optimal conditions of independent variables including oil-methanol ratio, catalyst concentration and reaction temperature of 1: 6.23 (m/m), 1.63% (w/w) and, 54.24 ℃, respectively, led to the highest biodiesel yield (98.62%).

 Discussion and conclusion: Considering the equilibrium nature of the transesterification reaction and methanol evaporation from the reactor, the biodiesel yields first increased and then decreased. Therefore, finding the optimal reaction conditions will have a significant impact on achieving a higher yield. Also, no significant difference was observed between the characteristics of biodiesel produced from WCO and fresh oils, and only the pre-processing processes of WCO and glycerin separation and purification will be associated with more technical and economic challenges.

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