Fluid Catalytic Cracking Environmental Impact: Factorial Design Coupled with Genetic Algorithms to Minimize Carbon Monoxide Pollution

Abstract

Fluid Catalytic Cracking (FCC) process is a complex process in petroleum refining industry; it cracks long chain molecules from gas oil and residues to produce high value products like diesel and gasoline. FCC process is composed by two reactors: the riser where cracking reactions take place and the regenerator where combustion reactions eliminate coke deposition from catalyst surface; the last reactors are connected by two transport lines where catalyst circulates. Regenerator flue gas emissions are composed by carbon oxides (CO and CO2), sulfur oxides (SO2 and SO3), nitrogen oxides (NO, N2O, N2), and particulates. This work focuses on the minimization of carbon monoxide (CO) in flue gases while maintaining high process conversion. A multi-objective optimization problem was established to maximize conversion and minimize emissions of CO. The problem was solved using genetic algorithms coupled with factorial design used to identify key process variables and to formulate objective optimization functions. Results showed a reduction in CO emissions in the order of 12.8 % with a conversion of 73 %, indicating genetic algorithms as an useful tool to comply environmental regulations and process demands with low computational burden and time.