A mixed integer nonlinear programming approach for petroleum refinery topology optimisation

•Proposed strategy to devise configuration then optimize conversion and temperature.•Implemented on case study of a real-world refinery in Kuwait.•Obtained resulting configuration that agrees with industrial practice. This work presents a mixed integer nonlinear programming (MINLP)-based superstruct...

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Veröffentlicht in:Chemical engineering research & design Jg. 143; S. 24 - 35
Hauptverfasser: Albahri, Tareq A., Khor, Cheng Seong, Elsholkami, Mohamed, Elkamel, Ali
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Rugby Elsevier B.V 01.03.2019
Elsevier Science Ltd
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ISSN:0263-8762, 1744-3563
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Zusammenfassung:•Proposed strategy to devise configuration then optimize conversion and temperature.•Implemented on case study of a real-world refinery in Kuwait.•Obtained resulting configuration that agrees with industrial practice. This work presents a mixed integer nonlinear programming (MINLP)-based superstructure optimisation approach to synthesize an optimal petroleum refinery topology or configuration for large-scale grassroots refinery systems. We develop a superstructure to include many possible prospective configurations and formulate rigorous models for the 32 commercial refinery processes that constitute the configurations, which gives rise to a convex MINLP model. The objective function is to maximize the total refinery profit for a given crude oil feed subject to material and energy balance constraints. We apply a two-level optimisation procedure: a master module to construct configurations from the superstructure and a submodule to optimize the process unit conversions and product temperatures of the configurations. A numerical example based on an actual operating refinery in Kuwait is illustrated to implement the approach with a resulting configuration that agrees with real-world practices.
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ISSN:0263-8762
1744-3563
DOI:10.1016/j.cherd.2019.01.001