A mixed integer nonlinear programming approach for petroleum refinery topology optimisation

• Main Authors: Albahri, T.A., Khor, C.S., Elsholkami, M., Elkamel, A.
• Format: Article
• Published: 2019
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060245438&doi=10.1016%2fj.cherd.2019.01.001&partnerID=40&md5=daab624bd25f1ddfec6c27743ad26248; http://eprints.utp.edu.my/22126/

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. © 2019 Institution of Chemical Engineers