Optimization of Heat-Integrated Crude Oil Distillation Systems. Part I: The Distillation Model

This work presents a methodology for optimizing heat-integrated crude oil distillation systems. Part I of this three-part series presents a modeling strategy where artificial neural networks are used to represent the distillation process. Part II presents a new methodology to retrofit heat exchanger...

Full description

Saved in:
Bibliographic Details
Published in:Industrial & engineering chemistry research 2015-05, Vol.54 (18), p.4988-5000
Main Authors: Ochoa-Estopier, Lluvia M, Jobson, Megan
Format: Article
Language:English
Subjects:
Computer simulation
Crude oil
Distillation
Methodology
Networks
Neural networks
Optimization
Retrofitting
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This work presents a methodology for optimizing heat-integrated crude oil distillation systems. Part I of this three-part series presents a modeling strategy where artificial neural networks are used to represent the distillation process. Part II presents a new methodology to retrofit heat exchanger networks (HENs) and Part III presents the application of this distillation model to perform operational optimization of the crude oil distillation unit while proposing retrofit modifications to the associated HEN. Independent variables of the distillation model include flow rates of products, stripping steam, pump-around specifications, and furnace exit temperature. Dependent variables include those related to product quality, and temperatures, duties, and heat capacities of process streams involved in heat integration. The resulting neural network model is able to overcome convergence problems presented by rigorous or simplified models. Simulation time is significantly improved using neural networks, compared to rigorous models, with practically no detriment to model accuracy.
ISSN:0888-5885
1520-5045
DOI:10.1021/ie503802j