University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Improvement of crude oil refinery gross margin using a NLP model of a crude distillation unit system

López, DC, Hoyos, LJ, Uribe, A, Chaparro, S, Arellano-Garcia, H and Wozny, G (2012) Improvement of crude oil refinery gross margin using a NLP model of a crude distillation unit system In: 22nd European Symposium on Computer Aided Process Engineering (ESCAPE22), 2012-06-17 - 2012-06-20, University College London, London, UK.

[img]
Preview
PDF (licence)
SRI_deposit_agreement.pdf
Available under License : See the attached licence file.

Download (33kB) | Preview

Abstract

This work presents a Non Linear Programming (NLP) model developed to optimize simultaneously a crude oil distillation unit (CDU) system and several cases of application run in a refinery as well. This model optimizes feedstock composition and operational conditions for a CDU System (ECOPETROL S.A.). The NLP Model uses a Metamodeling approach so as to represent Atmospheric Distillation Towers (ADT). The Vacuum Distillation Towers (VDT) are implemented assuming perfect separation (assay cuttings). The defined objective function is given by an economic profit. The CDU system consists basically of five industrial units and fourteen Colombian Crude Oils. Each Metamodel uses as independent variables: crude oil flow rates, operational conditions, Jet EBP, and Diesel T95% from ASTM D-86 distillation curve. The output variables of the Metamodels are product flows, temperatures, and qualities. The developed NLP model was implemented in GAMS. The time needed for its solution is around 60s while using the CONOPT solver. The NLP model results were successfully applied to a Colombian refinery for 3 consecutive weeks. The model was able to find the best use of installed equipments in CDUs through the preparation of a crude oil charge quasi-constant quality without matter the time period of the optimization. In each week, optimal crude oil flow rates towards each CDU (like new scenarios implemented in the refinery) were evaluated in a refinery global simulator with all downstream refining schemes in order to calculate the Refinery Gross Margin (RGM). In each analyzed case, the obtained RGM for new crude oil feeds was however better than that case without optimization with a economic benefit of up to 0.043 US$/bl equivalent to US$ 3.870.000 per year. This shows the effectiveness of a CDU NLP model within short term planning in the petroleum industry.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Chemical Engineering
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
AuthorsEmailORCID
López, DCUNSPECIFIEDUNSPECIFIED
Hoyos, LJUNSPECIFIEDUNSPECIFIED
Uribe, AUNSPECIFIEDUNSPECIFIED
Chaparro, SUNSPECIFIEDUNSPECIFIED
Arellano-Garcia, HUNSPECIFIEDUNSPECIFIED
Wozny, GUNSPECIFIEDUNSPECIFIED
Date : 13 June 2012
Identification Number : 10.1016/B978-0-444-59520-1.50056-7
Copyright Disclaimer : © 2012 Elsevier B.V. All rights reserved.
Contributors :
ContributionNameEmailORCID
EditorBogle, IDLUNSPECIFIEDUNSPECIFIED
EditorFairweather, MUNSPECIFIEDUNSPECIFIED
Depositing User : Symplectic Elements
Date Deposited : 02 Sep 2016 10:42
Last Modified : 02 Sep 2016 10:42
URI: http://epubs.surrey.ac.uk/id/eprint/811962

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800