@inbook{70779f99ba0e49be927e91faba634855,
title = "Molecular Modelling of Co-processing Biomass Pyrolysis Oil with Vacuum Gasoil in an Oil Refinery Fluid Catalytic Cracking Unit",
abstract = "Integration of biomass resources in petroleum refining for sustainable production of transportation fuels has gained increased attention in the last few decades (IEA, 2013). One potential integration option is to mix biomass-based pyrolysis oil (BPO) with petroleum gas oil (VGO) and then co-process the blend in oil refinery fluidised catalytic cracking (FCC) units (Naik et al., 2017). It is important to establish the prediction model of product yield and quality with such coprocessing in FCC units. In this work, a novel molecular-level modelling approach is proposed for kinetic modelling of co-processing BPO with VGO in an oil refinery FCC unit. Molecular-level characterisation of BPO and VGO blends using Molecular Type and Homologous Series matrix is first conducted. Then, a novel reaction network is synthesized and a reaction model is developed for the proposed reaction network which considers not only the complex intermolecular interactions between various types of molecular attributes in the feed, but also the interactions between individual molecules and catalyst surface. A hybrid optimisation strategy combining genetic algorithm with deterministic optimisation algorithm is developed to obtain the optimal parameters in the reaction model. The results demonstrate an overall good agreement between measured and predicted yields using the developed kinetic model for VGO: BPO blending ratio of 90:10, C/O ratio between 5 and 8, and reaction temperature of 525°C. PONA composition, oxygen compounds compositions and oxygen content in each product fraction such as gasoline, diesel and gas oil can also be predicted. The effect of different blending ratios of BPO and VGO on oxygenates compositions is demonstrated.",
keywords = "biomass, Catalytic cracking, Fast pyrolysis oil, MTHS matrix, refinery",
author = "{Al Jamri}, Mohamed and R. Smith and Jie Li",
year = "2019",
doi = "10.1016/B978-0-12-818634-3.50166-1",
language = "English",
series = "Computer Aided Chemical Engineering",
publisher = "Elsevier BV",
pages = "991--996",
booktitle = "Computer Aided Chemical Engineering",
address = "Netherlands",
}