Integrated FCC riser—regenerator dynamics studied in a fluid catalytic cracking pilot plant

In this paper a dynamic simulator of the fluid catalytic cracking (FCC) pilot plant, operating in the Chemical Process Engineering Research Institute (CPERI, Thessaloniki, Greece), is presented. The operation of the pilot plant permits the execution of case studies for monitoring of the dynamic responses of the unit, by imposing substantial step changes in a number of the manipulated variables. The comparison between the dynamic behavior of the unit and that predicted by the simulator arise useful conclusions on both the similarities of the pilot plant to commercial units, along with the ability of the simulator to depict the main dynamic characteristics of the integrated system. The simulator predicts the feed conversion, coke yield and heat of catalytic reactions in the FCC riser on the basis of semi-empirical models developed in CPERI and simulates the regenerator according to the two-phase theory of fluidization, with a dilute phase model taking account of postcombustion reactions. The riser and regenerator temperature, the stripper and regenerator pressure drop and the composition of the regenerator flue gas are measured on line and are used for verification of the ability of the simulator to predict the dynamic transients between steady states in both open- and closed-loop unit operation. All the available process variables such as the reaction conversion, the coke yield, the carbon on regenerated catalyst and the catalyst circulation rate are used for the validation of the steady-state performance of the simulator. The comparison between the dynamic responses of the model and those of the pilot plant to step changes in the feed rate and preheat temperature reveals the ability of the simulator to accurately depict the complex pilot process dynamics in both open- and closed-loop operation. The dynamic simulator can serve as the basis for the development of a model-based control structure for the pilot plant, alongside its use as a tool for off-line process optimization studies.