Transesterification of waste cooking oil by heteropoly acid (HPA) catalyst: Optimization and kinetic model

被引:150
作者
Talebian-Kiakalaieh, Amin [1 ]
Amin, Nor Aishah Saidina [1 ]
Zarei, Alireza [1 ]
Noshadi, Iman [2 ]
机构
[1] UTM, Fac Chem Engn, CREG, Skudai 81310, Johor, Malaysia
[2] Univ Connecticut, Dept Chem Mat & Biomol Engn, Storrs, CT 06269 USA
关键词
Biodiesel; Heterogeneous; Transesterification; Waste cooking oil; Optimization; Kinetic; RESPONSE-SURFACE METHODOLOGY; ARTIFICIAL NEURAL-NETWORKS; BIODIESEL PRODUCTION; ESTIMATION CAPABILITIES; PROCESS PARAMETERS; TECHNICAL ASPECTS; LIPASE; ANN; ESTERIFICATION; PREDICTION;
D O I
10.1016/j.apenergy.2012.07.018
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Transesterification of waste cooking oil with heterogeneous (heteropoly acid) catalyst and methanol has been investigated. Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were employed to study the relationship between process variables and free fatty acid conversion and for predicting the optimal parameters. The highest conversion was 88.6% at optimum condition being 14 h, 65 degrees C, 70:1 and 10 wt% for reaction time, reaction temperature, methanol to oil molar ratio and catalyst loading, respectively. The RSM and ANN could accurately predict the experimental results, with R-2 = 0.9987 and R-2 = 0.985, respectively. Kinetics studies were investigated to describe the system. The reaction followed first-order kinetics with the calculated activation energy, Ea = 53.99 kJ/mol while the pre-exponential factor, A = 2.9 x 10(7) min(-1). These findings can help improve an environmentally friendly biodiesel process that conforms to ASTM D6751 standards. (c) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:283 / 292
页数:10
相关论文
共 60 条
[11]   Performance and exhaust emissions of a biodiesel engine [J].
Canakci, M ;
Erdil, A ;
Arcaklioglu, E .
APPLIED ENERGY, 2006, 83 (06) :594-605
[12]   Biodiesel production from high acid value waste frying oil catalyzed by superacid heteropolyacid [J].
Cao, Fenghua ;
Chen, Yang ;
Zhai, Fengying ;
Li, Jing ;
Wang, Jianghua ;
Wang, Xiaohong ;
Wang, Shengtian ;
Zhu, Weimin .
BIOTECHNOLOGY AND BIOENGINEERING, 2008, 101 (01) :93-100
[13]   Modelling aggregate heterogeneous ATM sources using neural networks [J].
Casilari, E ;
Jurado, A ;
Pansard, G ;
DiazEstrella, A ;
Sandoval, F .
ELECTRONICS LETTERS, 1996, 32 (04) :363-365
[14]   RESPONSE-SURFACE DESIGNS FOR QUANTITATIVE AND QUALITATIVE VARIABLES [J].
DRAPER, NR ;
JOHN, JA .
TECHNOMETRICS, 1988, 30 (04) :423-428
[15]   Technical aspects of production and analysis of biodiesel from used cooking oil-A review [J].
Enweremadu, C. C. ;
Mbarawa, M. M. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2009, 13 (09) :2205-2224
[16]   VARIABLES AFFECTING THE YIELDS OF FATTY ESTERS FROM TRANSESTERIFIED VEGETABLE-OILS [J].
FREEDMAN, B ;
PRYDE, EH ;
MOUNTS, TL .
JOURNAL OF THE AMERICAN OIL CHEMISTS SOCIETY, 1984, 61 (10) :1638-1643
[17]   Application of sweet sorghum for biodiesel production by heterotrophic microalga Chlorella protothecoides [J].
Gao, Chunfang ;
Zhai, Yan ;
Ding, Yi ;
Wu, Qingyu .
APPLIED ENERGY, 2010, 87 (03) :756-761
[18]   Evaluation of anaerobic codigestion of microalgal biomass and swine manure via response surface methodology [J].
Gonzalez-Fernandez, Cristina ;
Molinuevo-Salces, Beatriz ;
Cruz Garcia-Gonzalez, Maria .
APPLIED ENERGY, 2011, 88 (10) :3448-3453
[19]   Simulation of biomass gasification with a hybrid neural network model [J].
Guo, B ;
Li, DK ;
Cheng, CM ;
Lü, ZA ;
Shen, YT .
BIORESOURCE TECHNOLOGY, 2001, 76 (02) :77-83
[20]   Artificial neural networks modelling of engine-out responses for a light-duty diesel engine fuelled with biodiesel blends [J].
Ismail, Harun Mohamed ;
Ng, Hoon Kiat ;
Queck, Cheen Wei ;
Gan, Suyin .
APPLIED ENERGY, 2012, 92 :769-777