Hydrotreatment modeling for a variety of VGO feedstocks: A continuous lumping approach. (1st January 2015)

• Record Type: Journal Article
• Authors: Becker, Per Julian; Celse, Benoit; Guillaume, Denis; Dulot, Hugues; Costa, Victor
• Is Part Of: Fuel. Volume 139(2015)
• Page Start: 133
• Page End: 143
• Publication Date: 2015-01-01
• Subjects: Hydrotreatment -- Kinetic modeling -- Continuous lumping -- VGO; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2014.08.032
• Languages: English
• ISSNs: 0016-2361

Abstract

Graphical abstract: Highlights: A continuous lumping model for hydrotreatment of VGO is presented and validated. Decomposition into five distinct families. Five distinct feedstocks of different geographic origin. Good results are obtained for total conversion and yield structure for both calibration and validation data. Abstract: The hydrotreatment of different VGO feedstocks in a pilot plant is modeled using the continuous lumping approach. A model with five continuous families (paraffins, naphtenes, sulfur-containing aromatics, nitrogen-containing aromatics, and sulfur and nitrogen free aromatics) is proposed and validated in this work. The model considers the five families to be a continuous distribution. A reaction network, including hydrogenation, desulfurization, denitrogenation, and cracking is established and used to derive the kinetic rate expressions for each family. A total of 46 model parameters are adjusted, using data from 44 experimental runs, using a pilot plant. Three feedstocks of different origin and thus different characteristics (e.g. True Boiling Point, sulfur- and nitrogen content) were used in this study. The same set of parameters was used to simulate hydrotreatment of all three feedstocks, which extends the range of applicability of the model beyond the models which are typically proposed in literature, which rely on feedstock-specific parameters. The model was validated using 14 additional tests with 2 different feeds. The results show that this modeling approach is capable of accurately predicting the total hydrocarbon conversion and yield regardless of feed composition. Furthermore, insights into the underlying reaction mechanisms can be gained from the kinetic parameters.