Optimal Design of Petroleum Refinery Configuration Using a Model-Based Mixed-Integer Programming Approach with Practical Approximation

We present a model-based optimization approach to determine the configuration of a petroleum refinery for grassroots (new) or existing site that considers a large number of commercial technologies particularly for heavy oil processing of crude oil residue from an atmospheric distillation unit. First...

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Main Authors: Albahri, T.A., Khor, C.S., Elsholkami, M., Elkamel, A.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.21502 /
Published: American Chemical Society 2018
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047426256&doi=10.1021%2facs.iecr.7b04507&partnerID=40&md5=c49ccc71e79ddb36edfa6bfa8ce41fdb
http://eprints.utp.edu.my/21502/
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spelling utp-eprints.215022018-08-01T03:15:35Z Optimal Design of Petroleum Refinery Configuration Using a Model-Based Mixed-Integer Programming Approach with Practical Approximation Albahri, T.A. Khor, C.S. Elsholkami, M. Elkamel, A. We present a model-based optimization approach to determine the configuration of a petroleum refinery for grassroots (new) or existing site that considers a large number of commercial technologies particularly for heavy oil processing of crude oil residue from an atmospheric distillation unit. First, we develop a superstructure representation for the refinery configuration to encompass all possible topology alternatives comprising 96 technologies and their interconnectivities. The superstructure is postulated by decomposing it to incorporate representative heavy oil processing scheme alternatives that center on the technologies for atmospheric residual hydrodesulfurization (ARDS), vacuum residual hydrodesulfurization (VRDS), and residual fluid catalytic cracking (RFCC). We formulate a mixed-integer linear program (MILP) based on the superstructure by devising logic propositions on design and structural specifications that represent these processing options to aid convergence to an optimal refinery configuration. A numerical example is illustrated to implement the proposed technique in which an equivalent of more than two million refinery plot plans is evaluated. To assess the applicability and value of the approach, we validate the results against the literature as well as compare with existing real-world refinery configurations. A main contribution of this work is to demonstrate how a mixed-integer programming approach can be applied to a large-scale petroleum refinery design problem with suitable approximations informed by practical considerations to obtain results with reasonable computational load. © 2018 American Chemical Society. American Chemical Society 2018 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047426256&doi=10.1021%2facs.iecr.7b04507&partnerID=40&md5=c49ccc71e79ddb36edfa6bfa8ce41fdb Albahri, T.A. and Khor, C.S. and Elsholkami, M. and Elkamel, A. (2018) Optimal Design of Petroleum Refinery Configuration Using a Model-Based Mixed-Integer Programming Approach with Practical Approximation. Industrial and Engineering Chemistry Research, 57 (22). pp. 7555-7565. http://eprints.utp.edu.my/21502/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description We present a model-based optimization approach to determine the configuration of a petroleum refinery for grassroots (new) or existing site that considers a large number of commercial technologies particularly for heavy oil processing of crude oil residue from an atmospheric distillation unit. First, we develop a superstructure representation for the refinery configuration to encompass all possible topology alternatives comprising 96 technologies and their interconnectivities. The superstructure is postulated by decomposing it to incorporate representative heavy oil processing scheme alternatives that center on the technologies for atmospheric residual hydrodesulfurization (ARDS), vacuum residual hydrodesulfurization (VRDS), and residual fluid catalytic cracking (RFCC). We formulate a mixed-integer linear program (MILP) based on the superstructure by devising logic propositions on design and structural specifications that represent these processing options to aid convergence to an optimal refinery configuration. A numerical example is illustrated to implement the proposed technique in which an equivalent of more than two million refinery plot plans is evaluated. To assess the applicability and value of the approach, we validate the results against the literature as well as compare with existing real-world refinery configurations. A main contribution of this work is to demonstrate how a mixed-integer programming approach can be applied to a large-scale petroleum refinery design problem with suitable approximations informed by practical considerations to obtain results with reasonable computational load. © 2018 American Chemical Society.
format Article
author Albahri, T.A.
Khor, C.S.
Elsholkami, M.
Elkamel, A.
spellingShingle Albahri, T.A.
Khor, C.S.
Elsholkami, M.
Elkamel, A.
Optimal Design of Petroleum Refinery Configuration Using a Model-Based Mixed-Integer Programming Approach with Practical Approximation
author_sort Albahri, T.A.
title Optimal Design of Petroleum Refinery Configuration Using a Model-Based Mixed-Integer Programming Approach with Practical Approximation
title_short Optimal Design of Petroleum Refinery Configuration Using a Model-Based Mixed-Integer Programming Approach with Practical Approximation
title_full Optimal Design of Petroleum Refinery Configuration Using a Model-Based Mixed-Integer Programming Approach with Practical Approximation
title_fullStr Optimal Design of Petroleum Refinery Configuration Using a Model-Based Mixed-Integer Programming Approach with Practical Approximation
title_full_unstemmed Optimal Design of Petroleum Refinery Configuration Using a Model-Based Mixed-Integer Programming Approach with Practical Approximation
title_sort optimal design of petroleum refinery configuration using a model-based mixed-integer programming approach with practical approximation
publisher American Chemical Society
publishDate 2018
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047426256&doi=10.1021%2facs.iecr.7b04507&partnerID=40&md5=c49ccc71e79ddb36edfa6bfa8ce41fdb
http://eprints.utp.edu.my/21502/
_version_ 1741196470421291008
score 11.62408

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