Predictive Modeling of Large-Scale Integrated Refinery Reaction and Fractionation Systems from Plant Data. Part 1: Hydrocracking Processes

Abstract

This paper presents a workflow to develop, validate, and apply a predictive model for rating and optimization of large-scale integrated refinery reaction and fractionation systems from plant data. We demonstrate the workflow with two commercial processes, a medium-pressure hydrocracking (MP HCR) unit with a feed capacity of 1 million tons per year and a high-pressure hydrocracking (HP HCR) unit with a feed capacity of 2 million tons per year in the Asia Pacific. The units include reactors, fractionators, and hydrogen recycle systems. With catalyst and hydrogen, the process converts heavy feedstocks, such as vacuum gas oil, into valuable low-boiling products, such as gasoline and diesel. We present the detailed procedure for data acquisition to ensure accurate mass balances and for implementing the workflow using Excel spreadsheets and a commercial software tool, Aspen HYSYS/Refining. Our procedure is equally applicable to other commercial software tools. The workflow includes special tools to facilitate an accurate transition from lumped kinetic components used in reactor modeling to the pseudo-components based on boiling point ranges required in the rigorous stage-by-stage simulation of fractionators. We validate the two models with 4 months of plant data, and the resulting models accurately predict unit performance, product yields, and fuel properties from the corresponding operating conditions. The MP HCR model predicts the yields of heavy naphtha, diesel fuel, and bottom products with average absolute deviations (AADs) of at most 3.4 wt %, predicts the specific gravities of heavy naphtha, diesel fuel, and bottom oil with AADs below 0.0184, predicts the flash point and freezing point of diesel fuel with AADs of 3.6 and 4.1°C, respectively, and predicts the outlet temperatures of catalyst beds with AADs of 1.9°C. The HP HCR model predicts the yields of liquefied petroleum gas (LPG), light naphtha, heavy naphtha, jet fuel, and residue oil with AADs below 1.7 wt %, predicts the specific gravities of light naphtha, heavy naphtha, jet fuel, and residue oil with AADs less than 0.134, predicts the flash point and freezing point of jet fuel with AADs of 1.6 and 2.3°C, respectively, and predicts the outlet temperatures of catalyst beds of the two HCR reactors with AADs of 1.8 and 3.2°C. We apply the validated plantwide model to quantify the effect of the H 2 /oil ratio on product distribution and catalyst life and the effect of HCR reactor temperature and feed flow rate on product distribution. The results agree well with experimental observations reported in the literature. Our resulting models only require typical operating conditions and routine analysis of feedstock and products and appear to be the only reported integrated HCR models that can quantitatively simulate all key aspects of reactor operation, fractionator performance, hydrogen consumption, product yield, and fuel properties.

An Intelligent Tray Efficiency Estimation Method for the Fractionation System of Industrial Hydrocracking Processes

“…1, which contain 97 kinetic lumps. However, these lumps cannot properly characterize the feedstock of the fractionation system [4]; a step called delumping is needed. After delumping, 39 pseudo-components are obtained by the calculation of the modeling software.…”

“…Generally, the reactions taking place in a hydrocracking process can be divided into two types: refining and cracking. The role of the refining reactor is to remove organic impurities [3,4] and to provide qualified feedstock for the cracking reactor, in which the macromolecular organics are cracked into small-molecule organics. The ''refining-cracking'' structure endows the hydrocracking process with a wide feedstock processing range and high production flexibility [5,6].…”

Energy Recovery in a Naphtha Splitter Process through Debottlenecking of Retrofitted Thermally Coupled and Double‐Effect Distillation Sequences

“…In this study, the simulation was performed using commercial software, Aspen HYSYS 8.0 with an “oil environment” that allows a calculation of the different fractions in the distillation of complex mixtures of organic compounds. Therefore, it can generate a hypothetical hydrocarbon mixture from the distillation data and simulate the performance of different process equipment 14. Figure 3 shows the compositional complexity of the three fractions to display the ASTM D86 distillation curves for the specific distillates from the proposed process.…”

Modeling and Simulation of Reaction and Fractionation Systems for the Industrial Residue Hydrotreating Process

“…As the outermost layer of residue hydrogenation model, the process model seeks to integrate the reactor model with the fractionation model. Due to the complexity of residues, most previous works paid attention to only one aspect of the reactor model or the fractionator model for the for the plant wide residue hydrogenation process [24]. To make contribution to this aspect, a residue hydroconversion process model is comprehensively developed by exploiting delumping, which is a committed step to concatenate the reactor with the fractionation model.…”