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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Cutpoint Temperature Surrogate Modeling for Distillation Yields and Properties

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Author(s):
Franzoi, Robert E. [1] ; Menezes, Brenno C. [2] ; Kelly, Jeffrey D. [3] ; Gut, Jorge A. W. [1] ; Grossmann, Ignacio E. [4]
Total Authors: 5
Affiliation:
[1] Univ Sao Paulo, Dept Chem Engn, Sao Paulo - Brazil
[2] Hamad Bin Khalifa Univ, Qatar Fdn, Coll Sci & Engn, Div Engn Management & Decis Sci, Doha - Qatar
[3] Ind Algorithms Ltd, Toronto, ON - Canada
[4] Carnegie Mellon Univ, Chem Engn Dept, Pittsburgh, PA 15213 - USA
Total Affiliations: 4
Document type: Journal article
Source: Industrial & Engineering Chemistry Research; v. 59, n. 41, p. 18616-18628, OCT 14 2020.
Web of Science Citations: 1
Abstract

For high-performance operations in crude oil refinery processing, it is important to properly determine yields and properties of output streams from distillation units. To address such complex representation, we propose a cutpoint temperature-modeling framework using a coefficient setup MIQP (mixed-integer quadratic programming) technique to determine optimizable surrogate models to correlate independent X variables (crude oil compositions, temperatures, etc) to dependent Y variables (such as stream yields and properties of distillates). The X inputs are systematically generated by Latin hypercube sampling (LHS), and the experiments to obtain the synthetic Y outputs are simulated using the well-known conventional and improved swing-cut methods. By using these optimizable surrogate models (which are suitable to handle continuous data from the process) with measurement feedback (for adjustments and improvements), distillation outputs can be continuously updated when needed. The proposed approach successfully builds accurate surrogates for the distillation unit, which can be embedded into complex planning, scheduling, and control environments. Moreover, this MIQP surrogate identification technique may also be applied to other types of downstream process optimization problems such as reacting and blending unit operations, as well as other separating processes. (AU)

FAPESP's process: 18/04942-4 - Integration of the nonlinear distillation cutpoint modeling into the online refinery scheduling optimization
Grantee:Robert Eduard Franzoi Junior
Support Opportunities: Scholarships abroad - Research Internship - Doctorate (Direct)
FAPESP's process: 17/03310-1 - Integrated scheduling optimization in the crude-oil refinery industry: from crude-oil unloading to fuel deliveries
Grantee:Robert Eduard Franzoi Junior
Support Opportunities: Scholarships in Brazil - Doctorate (Direct)