Title page for ETD etd-09012011-170120


Type of Document Dissertation
Author Pashikanti, Kiran
URN etd-09012011-170120
Title Predictive Modeling of Large-Scale Integrated Refinery Reaction and Fractionation Systems from Plant Data: Fluid Catalytic Cracking (FCC) and Continuous Catalyst Regeneration (CCR) Catalytic Reforming Processes
Degree PhD
Department Chemical Engineering
Advisory Committee
Advisor Name Title
Liu, Y. A. Committee Chair
Achenie, Luke E. K. Committee Member
Davis, Richey M. Committee Member
Durrill, Preston L. Committee Member
Keywords
  • modeling
  • refining
  • fractionation
  • CCR
  • reforming
  • FCC
Date of Defense 2011-08-31
Availability unrestricted
Abstract
This dissertation includes two accounts of rigorous modeling of petroleum refinery modeling using rigorous reaction and fractionation units. The models consider various process phenomena and have been extensively used during a course of a six-month study to understand and predict behavior. This work also includes extensive guides to allow users to develop similar models using commercial software tools.

(1) Predictive Modeling of Large-Scale Integrated Refinery Reaction and Fractionation Systems from Plant Data: Fluid Catalytic Cracking (FCC) Process with Planning Applications: This work presents the methodology to develop, validate and apply a predictive model for an integrated fluid catalytic cracking (FCC) process. We demonstrate the methodology by using data from a commercial FCC plant in the Asia Pacific with a feed capacity of 800,000 tons per year. Our model accounts for the complex cracking kinetics in the riser-regenerator and associated gas plant phenomena. We implement the methodology with Microsoft Excel spreadsheets and a commercial software tool, Aspen HYSYS/Petroleum Refining from Aspen Technology, Inc. The methodology is equally applicable to other commercial software tools. This model gives accurate predictions of key product yields and properties given feed qualities and operating conditions. This work differentiates itself from previous work in this area through the following contributions: (1) detailed models of the entire FCC plant, including the overhead gas compressor, main fractionator, primary and sponge oil absorber, primary stripper and debutanizer columns; (2) process to infer molecular composition required for the kinetic model using routinely collected bulk properties of feedstock; (3) predictions of key liquid product properties not published alongside previous related work (density, D-86 distillation curve and flash point); (4) case studies showing industrially useful applications of the model; and (5) application of the model with an existing LP-based planning tool.

(2) Predictive Modeling of Large-Scale Integrated Refinery Reaction and Fractionation Systems from Plant Data: Continuous Catalyst Regeneration (CCR) Reforming Process: This work presents a model for the rating and optimization of an integrated catalytic reforming process with UOP-style continuous catalyst regeneration (CCR). We validate this model using plant data from a commercial CCR reforming process handling a feed capacity of 1.4 million tons per year in the Asia Pacific. The model relies on routinely monitored data such ASTM distillation curves, paraffin-napthene- aromatic (PNA) analysis and operating conditions. We account for dehydrogenation, dehydrocyclization, isomerization and hydrocracking reactions that typically occur with petroleum feedstock. In addition, this work accounts for the coke deposited on the catalyst and product recontacting sections. 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.

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