Integration of crude-oil scheduling and refinery planning by Lagrangean Decomposition

Author(s)

Yang, Haokun ^[1] ; Bernal, David E. ^[1] ; Franzoi, Robert E. ^[2] ; Engineer, Faramroze G. ^[3] ; Kwon, Kysang ^[3] ; Lee, Sechan ^[3] ; Grossmann, Ignacio E. ^[1]

Affiliation

^[1] Carnegie Mellon Univ, Dept Chem Engn, Pittsburgh, PA 15213 - USA

^[2] Univ Sao Paulo, Dept Chem Engn, BR-05508010 Sao Paulo, SP - Brazil

^[3] SK Innovat, Optimizat & Analyt Lab, Seoul 110728 - South Korea

• Document type: Journal article
• Source: Computers & Chemical Engineering; v. 138, JUL 12 2020.
• Web of Science Citations: 0

Abstract

In this work, a Mixed-Integer Nonlinear Programming (MINLP) modeling framework for integrating short-term Crude-oil Scheduling (CS) and mid-term Refinery Planning (RP) has been developed and effectively solved by a proposed Lagrangean Decomposition (LD) algorithm. The principles of this integration are based on the fact that both Crude-oil Scheduling and Refinery Planning have their economic net values as their objectives, and that they are physically linked by Crude Distillation Units (CDUs). A multi-scale approach is proposed in the framework to aggregate continuous- and discrete-time formulations in CS and RP, respectively. Compared to hierarchically solving the non-integrated CS and RP, computational results show significant improvement regarding the economic objective values. Moreover, the proposed LD approach requires less CPU time converging to a small (1%-5%) optimality gap when compared to the monolithic approach using state-of-the-art MINLP solvers. (C) 2020 Elsevier Ltd. All rights reserved. (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)