Molecular Modeling of Coprocessing Biomass Fast Pyrolysis Oil in Fluid Catalytic Cracking Unit

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Bibliographical metadata

Original languageEnglish
Pages (from-to)1989-2004
Number of pages16
JournalIndustrial & Engineering Chemistry Research
Volume59
Issue number5
Early online date8 Jan 2020
DOIs
Publication statusPublished - 8 Jan 2020

Related information

Researchers

Person

View all