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6927446 
Journal Article 
Predictive Modeling of Large-Scale Integrated Refinery Reaction and Fractionation Systems from Plant Data. Part 3: Continuous Catalyst Regeneration (CCR) Reforming Process 
Pashikanti, K; Liu, YA; , 
2011 
Yes 
Energy and Fuels
ISSN: 0887-0624
EISSN: 1520-5029 
AMER CHEMICAL SOC 
WASHINGTON 
25 
11 
5320-5344 
English 
This work presents a model for the rating and optimization of an integrated catalytic reforming process with UOP-style continuous catalyst regeneration (CCR) using Aspen HYSYS/Petroleum Refining. The model relies on routinely monitored data, such as American Society for Testing and Materials (ASTM) distillation curves, paraffin napthene aromatic (PNA) analysis, and operating conditions. We use a lumped kinetic network with 64 species over a broad C1-C14 range. This network can represent the key dehydrogenation, dehydrocyclization, isomerization, and hydrocracking reactions that typically occur with petroleum feedstock. The lumped kinetic scheme also allows us to make accurate predictions of benzene, toluene, ethylbenzene, and xylenes (BTEX). In addition, this work accounts for the coke deposited on the catalyst and the associated catalyst regeneration. We implement the hydrogen recycle and product recontacting sections as separate unit operations connected to the CCR reformer model. In addition, we include rigorous tray-by-tray simulation models for primary product recovery. We validate this model using 6 months of plant data from a commercial CCR reforming process handling a feed capacity of 1.4 million tons per year in the Asia Pacific. The validated model predicts key process yields and aromatic yields to within an average absolute deviation (AAD) of 1%. In addition, the model predicts liquid petroleum gas (LPG) composition to within 2.0% AAD. We also present several industrially useful case studies that display common interactions among process variables, such as feed composition, reaction temperature, space velocity, and hydrogen/hydrocarbon ratio (H-2/HC). These case studies accurately quantify the effect of key process variables on the process performance and demonstrate the model applications for improving energy efficiency and optimizing the reformer performance for chemical feedstock production. This work differentiates itself from the reported studies in the literature through the following contributions: (1) detailed kinetic model that accounts for coke generation and catalyst deactivation, (2) complete implementation of a recontactor and primary product fractionation, (3) feed lumping from limited feed information, (4) detailed procedure for kinetic model calibration, (5) industrially relevant case studies that highlight the effects of changes in key process variables, and (6) application of the model to refinery-wide production planning.