Optimization of Process Parameters for Biodiesel Production Using Response Surface Methodology
American Journal of Energy Engineering
Volume 4, Issue 2, March 2016, Pages: 8-16
Received: Nov. 17, 2015;
Accepted: Nov. 29, 2015;
Published: Apr. 20, 2016
Views 5411 Downloads 311
Emmanuel I. Bello, Department of Mechanical Engineering, Federal University of Technology, Akure, Nigeria
Tunde I. Ogedengbe, Department of Mechanical Engineering, Federal University of Technology, Akure, Nigeria
Labunmi Lajide, Department of Chemistry, Federal University of Technology, Akure, Nigeria
Ilesanmi. A. Daniyan, Department of Mechanical & Mechatronics Engineering, Afe Babalola University, Ado-Ekiti, Nigeria
The effect of five process parameters namely: reaction time, reaction temperature, stir speed, catalyst concentration and methanol-oil ratio on the transesterification process of waste frying oil to biodiesel were investigated. Optimization of the five process parameters and their quadratic cross effect was carried out using a four level-five factor central composite experimental design model and response surface methodology with each factor varied over four levels. Taking the biodiesel yield as the response of the designed experiment, the data obtained were statistically analysed to get a suitable model for optimization of biodiesel yield as a function of the five independent process parameters. The optimization produced 30 feasible solutions whose desirability equals to 1 and the selected (most desirable) condition was found to be: reaction time (3 hrs), reaction temperature (58°C), stir speed (305.5 rpm), catalyst concentration (1.4 wt%) and methanol to oil ratio (6:1), while the optimum yield of biodiesel for this condition was found to be 91.6%. The developed model was tested and validated for adequacy by substituting random experimental values as input parameters and the output parameters from the developed model were close to the experimental values. The biodiesel properties were characterized and the results obtained were found to satisfy the standard for both the ASTM D 6751 and EN 14214.
Emmanuel I. Bello,
Tunde I. Ogedengbe,
Ilesanmi. A. Daniyan,
Optimization of Process Parameters for Biodiesel Production Using Response Surface Methodology, American Journal of Energy Engineering.
Vol. 4, No. 2,
2016, pp. 8-16.
Aworanti, O. A., S. E. Agarry and A. O. Ajani (2013). Statistical Optimization of Process Variables for Biodiesel Production from Waste Cooking Oil Using Heterogeneous Base Catalyst. British Biotechnology Journal. 3(2)116-132.
Basiron, Y. and May, C. Y. (2005). Crude Palm Oil as a Source of Biofuel, Malaysian Palm Oil Board, Malaysia, Technical Report.
Bello, E. I. (2008). Evaluation of Coconut Oil Methyl Esters as an Alternative Fuel for Diesel Engine. Ph.D thesis. Federal University of Technology, Akure.
Box G. E. P. and N. R. Draper. (1987). Empirical Model-building and Response Surfaces, John Wiley and Sons, New York, p.663.
Canacki, M. and Van Gerpen, J. (2005). “A Pilot Plant to Produce Biodiesel from High Fatty Acid Feedstock”.
Enweremadu, C. C. and Rutto, H. L. (2015). Optimization and Modelling of Process Variables of Biodiesel Production from Manula Oil Using Response Surface Methodology. (2015). Journal of Chemical Society, Pakistan, 37(2)256-265.
European Biodiesel Board (2006). Biodiesel Chains: Promotng Faourable Conditions to Establish Biodiesel Market Actions WP 2 “Biodiesel Market Status” Deliverable 7: EU-27 Biodiesel Report.
Ghadge S. V. and H. Raheman (2006), Optimization of Biodiesel Production by Sunflower Oil Transesterification, Bioresour. Technol., 97, 379.
Goyal, P., M. P. Sharma and S. Jain (2012). Optimization of Esterification and Transesterification of High Free Fatty Acid Jatropha Curcas Oil Using Response Surface Methodology. Journal of Petroleum Science Research, 1(3)36-43.
Hai, T. C. (2002). The Palm Oil Industry in Malaysia, WWF, Malaysia.
Highina, B. K., I. M. Bugaje and B. Umar (2012). Liquid Biofuel as Alternative Transport Fuel in Nigeria. Int. Journal of Petroleum Technology Development Vol. 1, pp 1-15.
Jeong G. T. and D. H. Park. (2009). “Optimization of Biodiesel Production from Castor Oil Using Response Surface Methodology,” Appl. Biochem Biotechnol., vol. 156, pp. 431–441.
Jeong, G. T. H., S. Yang and D. H. Park. (2009). “Optimization of Transesterification of Animal Fat Ester Using Response Surface Methodology,” Bioresour Technol., vol. 100, pp. 25–30.
Kansedo, J. K. T. Lee and S. Bhatia. (2009). Biodiesel Production from Palm Oil via Heterogeneous Transesterification, Biomass Bioenergy, 33, 271.
Martin M. and I. E. Grossman (2011). Optimization of Heat and Water Integration for Biodiesel Production from Cooking Oil and Algae. pp. 1-38
Monyem A., J. H. Van Gerpen and Canacki (2001). The Effect of Timing of Oxidation on Emission from Biodiesel Fuelled Engines. Transactions of the ASAE 44(1) pp. 35- 42.
Nie K, Xie F, Wang F, Tan T. (2006). Lipase catalyzed methanolysis to produce biodiesel optimization of the biodiesel production. J. Mol. Catalysis B: Enzymatic. 43:142-17.
Salamatinia, B., I. Hashemizadeh and A. Z. Abdullah. (2013). Alkaline Earth Metal Oxide Catalysts for Biodiesel Production from Palm Oil: Elucidation of Process Behaviors and Modeling using Response Surface Methodology, Iranian J. Chemistry Chem. Eng. , 32.
Salamatinia, B., I. Hashemizadeh and A. Z. Abdullah. (2013). Intensification of Biodiesel Production from Vegetable Oils using Ultrasonic-assisted Process: Optimization and Kinetics, Chem. Eng. Process.: Process Intensification, 73.
Shibasaki-Kitakawa N, Honda H, Kuribayashi H, Toda T, Fukumura T, Yonemoto T. (2007). Biodiesel production using anionic ion-exchange resin as heterogeneous catalyst. Bioresour. Technol. 98:416-421.
Silva, N. D. L. D., M. R. W. M Maciel, C. B. Batistella and R. M. Filho. (2006). “Optimization of Biodiesel Production from Castor oil,” Appl Biochem Biotech., vol. 130, pp. 405–414. Uosukainen, E., M. Lamsa, Y. Y. Linko, P. Linko and M. Leisola. (1999). Optimization of Enzymatic Transesterification of Rapeseed Oil Ester using Response Surface and Principal Component Methodology, Enzyme Microb. Technol., 25, 236.