Fluid catalytic cracking optimisation using factorial design and genetic algorithm techniques

被引：5

作者：

Cuadros, Jose F. ^{[1
]}

Melo, Delba C. ^{[1
]}

Maciel Filho, Rubens ^{[1
]}

Wolf Maciel, Maria R. ^{[2
]}

机构：

[1] Univ Estadual Campinas, LOPCA UNICAMP Lab Optimisat Design & Adv Control, Dept Chem Proc, Sch Chem Engn,UNICAMP, BR-13083970 Campinas, SP, Brazil

[2] Univ Estadual Campinas, LDPS UNICAMP, Lab Separat Proc Dev, Dept Chem Proc,Sch Chem Engn,UNICAMP, BR-13083970 Campinas, SP, Brazil

来源：

CANADIAN JOURNAL OF CHEMICAL ENGINEERING | 2013年 / 91卷 / 02期

关键词：

modelling and simulation studies; optimisation and optimal control theory; petroleum engineering; MULTIOBJECTIVE OPTIMIZATION; UNIT; SIMULATION; PARAMETERS; GASOLINE; REACTOR; MODEL;

D O I：

10.1002/cjce.21700

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

Statistical techniques coupled with genetic algorithm (GA) were used to identify optimal values of key operational variables in fluid catalytic cracking (FCC) process. A Kellog Orthoflow F fluid catalytic cracking process model was considered. It is known as a highly nonlinear process with a large number of variables with strong interactions among them. A reduced process model was obtained through factorial design technique to be used as a process function in the optimisation work giving as result the operational conditions that maximise conversion without infringing operational restrictions with savings in computational burden and time. An increase of 8.71% in process conversion was achieved applying GA as optimisation technique. (c) 2012 Canadian Society for Chemical Engineering

引用

页码：279 / 290

页数：12

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