Multi-objective exergoeconomic and exergoenvironmental optimization of continuous synthesis of solketal through glycerol ketalization with acetone in the presence of ethanol as co-solvent

被引:30
作者
Aghbashlo, Mortaza [1 ]
Hosseinpour, Soleiman [1 ]
Tabatabaei, Meisam [2 ,3 ]
Rastegari, Hajar [4 ]
Ghaziaskar, Hassan S. [4 ]
机构
[1] Univ Tehran, Coll Agr & Nat Resources, Fac Agr Engn & Technol, Dept Mech Engn Agr Machinery, Karaj, Iran
[2] AREEO, ABRII, Microbial Biotechnol Dept, POB 31535-1897, Karaj, Iran
[3] Biofuel Res Team BRTeam, Karaj, Iran
[4] Isfahan Univ Technol, Dept Chem, Esfahan, Iran
基金
美国国家科学基金会;
关键词
Adaptive neuro-fuzzy inference system; Continuous glycerol ketalization; Cost and environmental per unit of exergy for the product; Exergoeconomic and exergoenvironmental analyses; Non-dominated sorting genetic algorithm-II; Solketal synthesis; ENERGY-CONVERSION SYSTEMS; COOKING OIL WCO; HYDROGEN-PRODUCTION; EXERGY ANALYSIS; LOW-POWER; ULTRASONIC REACTOR; BIODIESEL; WASTE; CATALYST;
D O I
10.1016/j.renene.2018.06.103
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This work was aimed at conducting a multi-objective exergoeconomic and exergoenvironmental optimization of continuous synthesis of solketal through glycerol ketalization with acetone in the presence of ethanol as co-solvent and Purolite PD206 as catalyst. Exergoeconomic and exergoenvironmental performance parameters of the reactor were computed and discussed comprehensively after writing and solving their balance equations based on the experimental data. The effects of process parameters viz. ketalization temperature (T), acetone/glycerol molar ratio (X), feed flow rate (F), reaction pressure (P), and catalyst quantity (C) on the exergy-based variables were investigated in detail. The optimization process was performed based on minimizing two more important exergetic parameters, i.e., cost and environmental per unit of exergy for the product. To this end, an elaborated coupled version of adaptive neuro-fuzzy inference system (ANFIS) and non-dominated sorting genetic algorithm-II (NSGA-II) was employed. The ANFIS approach was used for modeling the process, while the NSGA-II was applied for finding the optimum operating conditions of the reactor. According to the results obtained, the ANFIS approach successfully predicted both objective parameters with an R-2 higher than 0.99. The optimum ketalization conditions for solketal synthesis in the developed reactor corresponded to T = 35.1 degrees C, X = 4.5, F = 0.4 mL/min, P = 26.7 bar, and C = 2.2 g, leading to the cost and environmental impact per unit of exergy for the product of 5032.9 USD/GJ and 143.9 mPts/GJ, respectively. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:735 / 748
页数:14
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