Abstract
As gasoline demand increases, the efficiency of operation of Fluidized Catalytic Cracking Unit (FCCU) becomes paramount importance. In this paper, a dynamic model for FCCU is simulated and integrated with yield model in order to estimate the yield of products namely gasoline, light gases and coke. Conventional PI controllers are designed for the control of reactor and regenerator temperature. Since, the complete reaction occurs in a very short duration, the controllers are tuned so as to achieve shorter settling time and minimum overshot. Further in order to increase the yield, optimization of FCCU using Generalized Predictive Controller (GPC) at supervisory level is attempted. Through optimization of objective function, the GPC will provide optimized set point for the PI controller in order to maintain maximum gasoline yield.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
Arbel, A., Z. Huang, I. H. Rinard, R. Shinnar, and A. V. Sapre. 1995. “Dynamic and Control of Fluidized Catalytic Crackers. 1. Modeling of the Current Generation of FCC’s.” Industrial & Engineering Chemistry Research 34: 1228–43.10.1021/ie00043a027Search in Google Scholar
Avidan, A. A., and R. Shinnar. 1990. “Development of Catalytic Cracking Technology – A Lesson in Chemical Reactor Design.” Industrial & Engineering Chemistry Research 29: 931–42.10.1021/ie00102a001Search in Google Scholar
Camacho, E. F., and C. Bardos. 2007. Model Predictive Control, 81–126. London: Springer.10.1007/978-0-85729-398-5_5Search in Google Scholar
Christensen, G., M. R. Minas, K. J. Hickey, and S. F. Jaffe. 1999. “Future Directions in Modeling the FCC Process: An Emphasis on Product Quality.” Chemical Engineering Science 54: 2753–64.10.1016/S0009-2509(99)00002-0Search in Google Scholar
Clarke, D. W., C. Mohtadi, and P. S. Tuffs. 1987. “Generalized Predictive Control – Part I. The Basic Algorithm.” Automatica 23: 137–48.10.1016/0005-1098(87)90087-2Search in Google Scholar
Clarke, D. W., C. Mohtadi, and P. S. Tuffs. 1989. “Properties of Generalized Predictive Control.” Automatica 25: 859–75.10.1016/0005-1098(89)90053-8Search in Google Scholar
Dasila, P. K., I. Choudhury, D. Saraf, S. Chopra, and A. Dalai. 2011. “Parametric Sensitivity Studies in a Commercial FCC Unit.” Advances in Chemical Engineering and Science 1: 136–49.10.4236/aces.2012.21017Search in Google Scholar
Gauthier, T. A. 2009. “Current R&D Challenges for Fluidized Bed Processes in the Refining Industry.” International Journal of Chemical Reactor Engineering 7: 1–70.10.2202/1542-6580.1857Search in Google Scholar
Gianetto, A., H. I. Farag, A. P. Blasetti, and H. I. De Lasa. 1994. “Fluid Catalytic Cracking Catalyst for Reformulated Gasolines-Kinetic Modeling.” Industrial & Engineering Chemistry Research 339: 3053–62.10.1021/ie00036a021Search in Google Scholar
Hovd, M., and S. Skogestad. 1993. “Procedure for Regulatory Control Structure Selection with Application to the FCC Processes.” AIChE Journal 39: 1938–53.10.1002/aic.690391205Search in Google Scholar
Kurihara, H. 1967. Optimal Control of Fluid Catalytic Cracking Processes. PhD thesis, Cambridge: MIT.Search in Google Scholar
Lee, E., and F. R. Groves. 1985. “Mathematical Model of the Fluidized Bed Catalytic Cracking Plant.” Transactions of the Society for Computer Simulation 3: 219–36.Search in Google Scholar
Martinsa, M. A. F., A. C. Zaninb, and D. Odloaka. 2014. “Robust Model Predictive Control of an Industrial Partial Combustion Fluidized-Bed Catalytic Cracking Converter.” Chemical Engineering Research and Design 5: 917–30.10.1016/j.cherd.2013.08.005Search in Google Scholar
McFarlane, M. C., R. C. Reinemen, J. F. Bartee, and C. Georgakis. 1993. “Dynamic Simulator for a Model IV Fluid Catalytic Cracking Unit.” Computers & Chemical Engineering 17: 275–300.10.1016/0098-1354(93)80021-ESearch in Google Scholar
Mythily, M., D. Manamalli, and P. Manikandan. 2011. “Dynamic Modeling, Simulation and Multivariable Control Strategy Applied to Catalytic Cracking Unit.” In International Conference on Process Automation, Control and Computing (IEEE), 1–7, Coimbatore: IEEE.10.1109/PACC.2011.5978937Search in Google Scholar
O’Dwyer, A. 2009. Handbook of PI and PID Controller Tuning Rules. London: Imperial College Press.10.1142/p575Search in Google Scholar
Roman, R., Z. K. Nagy, F. Allgower, and S. P. Agachi. 2005. “Dynamic Modeling and Non Linear Model Predictive Control of a Fluid Catalytic Cracking Unit.” Computer Aided Chemical Engineering 20: 1363–8.10.1016/S1570-7946(05)80069-0Search in Google Scholar
Sadeghbeigi, R. 2012. Fluid Catalytic Cracking Hand Book. Design, Operation and Troubleshooting of FCC Facilities. Oxford: Butterworth-Heinemann.10.1016/B978-0-12-386965-4.00012-4Search in Google Scholar
Saez, D., A. Ordys, and M. Grimble. 2005. “Design of a Supervisory Predictive Controller and its Applications to Thermal Power Plants.” Optimal Control Applications and Methods 26: 169–98.10.1002/oca.757Search in Google Scholar
Weekman, V. M., and D. M. Nace. 1970. “Kinetic and Dynamics of Catalytic Cracking Selectivity in Fixed Bed Reactor.” American Institute of Chemical Journal 16: 397–40.10.1002/aic.690160316Search in Google Scholar
Wu, Z., A. T. Yi, M. Rena, C. S. Barnesa, S. Chena, and P. D. Christofides. 2019. “Model Predictive Control of Phthalic Anhydride Synthesis in a Fixed-Bed Catalytic Reactor via Machine Learning Modelling.” Chemical Engineering Research and Design 145: 173–83.10.1016/j.cherd.2019.02.016Search in Google Scholar
Yadav, P. K., and R. K. Garg. 2017. “Modeling and Simulation of Fluidized Catalytic Cracking Riser Reactor Using Pseudo Reaction Kinetics : A Review.” International Journal of Engineering and Technology 9: 1667–81.10.21817/ijet/2017/v9i3/170903017Search in Google Scholar
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Articles in the same Issue
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Articles in the same Issue
- Frontmatter
- Articles
- Analysis of fluid retention zones in heat exchangers with segmental baffle and helical baffle
- Effects of geometric parameters on volumetric mass transfer coefficient of non-Newtonian fluids in stirred tanks
- Modelling, control and supervisory optimization of generalized predictive control in catalytic cracking reactor
- Kinetic modelling of microalgal growth and fucoxanthin synthesis in photobioreactor
- Comparative study on photooxidation of methyl orange using various UV/oxidant systems
- Computational fluid dynamic simulations to improve heat transfer in shell tube heat exchangers
- Characteristics of carbide slag slurry flow in a bubble column carbonation reactor
- Simple microwave pyrolysis kinetics of lignocellulosic biomass (oil palm shell) with activated carbon and palm oil fuel ash catalysts