Multi-objective optimization of a fluidized bed catalytic cracker unit to minimize CO2 emissions

  • Mr Mohmmad Al-Mayyahi, Monash university, Australia
  • Dr Andrew Hoadley, Monash University, Australia
  • Mr Nicholas Smith, Monash University, Australia
  • Prof Gade Rangaiah, National University of Singapore, Singapore

Fluidized bed catalytic cracker (FCC) is one of the major CO2 emitters in oil refineries due to the large amount of CO2 produced from the catalyst regenerating system. Minimizing the CO2 emissions from FCC has direct impacts on economical and operational objectives such as total profit, total conversion, and product yields. In order to investigate the trade-off between the CO2 emissions and other conflicting objectives, this paper presents the results of a multi-objective optimization (MOO) of a rigorous model of the FCC unit. A steady state FCC model has been formulated using Aspen Hysys. The model includes, in addition to the reactor/regenerator section, the feed preheat train, main fractionator and flue gas heat and power recovery sections. A real-coded, elitist non-dominated sorting genetic algorithm (NSGA-II) has been used to generate a set of optimal non-dominated solutions (Pareto front). The pinch analysis via the Grand Composite Curve (GCC) has been integrated with the FCC model to minimize the external hot utilities required by maximizing the energy recovery at the FCC unit. The resulting optimal solutions in terms of Pareto curves for the FCC model are presented and their significant features are discussed. Implementing MOO to the FCC unit provides important physical insights into economical targets, associated emissions limits and values of decision variables, for better decision making.