TY - JOUR
T1 - Molecular Modeling of Coprocessing Biomass Fast Pyrolysis Oil in Fluid Catalytic Cracking Unit
AU - Al Jamri, Mohamed Yusuf Mohamed Ebrahim
AU - Li, Jie
AU - Smith, Robin
N1 - Funding Information:
We would like to acknowledge the financial support from the Research Impact Scholarship, The University of Manchester, United Kingdom.
Publisher Copyright:
© 2020 American Chemical Society.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/1/8
Y1 - 2020/1/8
N2 - Integration of renewable sources into a transportation fuels production system through FCC units in an oil refinery has gained increased attention. For better understanding of the effect of the reaction conditions, blending ratios, and feed properties on product yields and qualities, kinetic modeling of FCC units is necessary. In this Article, a novel framework for molecular-level modeling of coprocessing biomass fast pyrolysis oil (FPO) with vacuum gas oil (VGO) in an oil refinery FCC unit is developed, which includes molecular-level characterization of biomass pyrolysis oil and VGO feed blends, synthesis of large-scale and complex reaction network, molecular-level kinetic modeling, and parameter estimation. The rule "same type of reactions have similar activation energies" is employed to reduce the number of kinetic parameters. The kinetic parameters in the proposed model are estimated using a hybrid solution algorithm combining deterministic and stochastic optimization methods. The computational results demonstrate an overall good agreement between measured and predicted yields using the developed kinetic model for VGO:FPO blending ratio, C/O ratio, and reaction temperature of 95:5, 5, and 530 °C, respectively. PONA composition in each layer of product stream (e.g., gasoline, diesel, gasoil, etc.) as well as oxygen compounds compositions and oxygen content are also successfully predicted. The proposed framework can be easily extended for modeling of other refinery processes and creates potentials for rigorous simulation and optimization of refinery operations to achieve maximization of refinery profit or better product quality control.
AB - Integration of renewable sources into a transportation fuels production system through FCC units in an oil refinery has gained increased attention. For better understanding of the effect of the reaction conditions, blending ratios, and feed properties on product yields and qualities, kinetic modeling of FCC units is necessary. In this Article, a novel framework for molecular-level modeling of coprocessing biomass fast pyrolysis oil (FPO) with vacuum gas oil (VGO) in an oil refinery FCC unit is developed, which includes molecular-level characterization of biomass pyrolysis oil and VGO feed blends, synthesis of large-scale and complex reaction network, molecular-level kinetic modeling, and parameter estimation. The rule "same type of reactions have similar activation energies" is employed to reduce the number of kinetic parameters. The kinetic parameters in the proposed model are estimated using a hybrid solution algorithm combining deterministic and stochastic optimization methods. The computational results demonstrate an overall good agreement between measured and predicted yields using the developed kinetic model for VGO:FPO blending ratio, C/O ratio, and reaction temperature of 95:5, 5, and 530 °C, respectively. PONA composition in each layer of product stream (e.g., gasoline, diesel, gasoil, etc.) as well as oxygen compounds compositions and oxygen content are also successfully predicted. The proposed framework can be easily extended for modeling of other refinery processes and creates potentials for rigorous simulation and optimization of refinery operations to achieve maximization of refinery profit or better product quality control.
KW - Catalytic cracking
KW - Fast pyrolysis oil
KW - biomass
KW - molecular modelling
KW - Molecular Type and Homologous Series (MTHS) Matrix
UR - http://www.scopus.com/inward/record.url?scp=85079796684&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/2a0f44dd-9f54-3cef-ad30-1ddc5ed2bec5/
U2 - 10.1021/acs.iecr.9b05361
DO - 10.1021/acs.iecr.9b05361
M3 - Article
SN - 0888-5885
VL - 59
SP - 1989
EP - 2004
JO - Industrial & Engineering Chemistry Research
JF - Industrial & Engineering Chemistry Research
IS - 5
ER -