Assessment of Lagrangean decomposition for short-term planning of integrated refinery-petrochemical operations. (June 2023)
- Record Type:
- Journal Article
- Title:
- Assessment of Lagrangean decomposition for short-term planning of integrated refinery-petrochemical operations. (June 2023)
- Main Title:
- Assessment of Lagrangean decomposition for short-term planning of integrated refinery-petrochemical operations
- Authors:
- Uribe-Rodríguez, Ariel
Castro, Pedro M.
Guillén-Gosálbez, Gonzalo
Chachuat, Benoît - Abstract:
- Highlights: Short-term planning of a full-scale integrated refinery-petrochemical complex under realistic scenarios. Corresponding MIQCQP model consists of 7000 equations and 35, 000 bilinear terms in the base-case scenario. Lagrangean decomposition closes the optimality gap to below 4% in all investigated scenarios and within 1% in two scenarios. Paves the way towards tractable global otpimization for large-scale planning problems in similar applications. Abstract: We present an integrated methodology for optimal short-term planning of integrated refinery-petrochemical complexes (IRPCs) and demonstrate it on a full-scale industrial case study under four realistic planning scenarios. The large-scale mixed-integer quadratically constrained optimization models are amenable to a spatial Lagrangean decomposition through dividing the IRPC into multiple subsections, which comprise crude management, refinery, fuel blending, and petrochemical production. The decomposition algorithm creates virtual markets for trading crude blends and intermediate petrochemical streams within the IRPC and seeks an optimal tradeoff in such markets, with the Lagrange multipliers acting as transfer prices. The best results are obtained for decompositions with two or three subsections, achieving optimality gaps below 4% in all four planning scenarios. The Lagrangean decomposition provides tighter primal and dual bounds than the global solvers BARON and ANTIGONE, and it also improves the dual boundsHighlights: Short-term planning of a full-scale integrated refinery-petrochemical complex under realistic scenarios. Corresponding MIQCQP model consists of 7000 equations and 35, 000 bilinear terms in the base-case scenario. Lagrangean decomposition closes the optimality gap to below 4% in all investigated scenarios and within 1% in two scenarios. Paves the way towards tractable global otpimization for large-scale planning problems in similar applications. Abstract: We present an integrated methodology for optimal short-term planning of integrated refinery-petrochemical complexes (IRPCs) and demonstrate it on a full-scale industrial case study under four realistic planning scenarios. The large-scale mixed-integer quadratically constrained optimization models are amenable to a spatial Lagrangean decomposition through dividing the IRPC into multiple subsections, which comprise crude management, refinery, fuel blending, and petrochemical production. The decomposition algorithm creates virtual markets for trading crude blends and intermediate petrochemical streams within the IRPC and seeks an optimal tradeoff in such markets, with the Lagrange multipliers acting as transfer prices. The best results are obtained for decompositions with two or three subsections, achieving optimality gaps below 4% in all four planning scenarios. The Lagrangean decomposition provides tighter primal and dual bounds than the global solvers BARON and ANTIGONE, and it also improves the dual bounds computed using piecewise linear relaxation strategies. … (more)
- Is Part Of:
- Computers & chemical engineering. Volume 174(2023)
- Journal:
- Computers & chemical engineering
- Issue:
- Volume 174(2023)
- Issue Display:
- Volume 174, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 174
- Issue:
- 2023
- Issue Sort Value:
- 2023-0174-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-06
- Subjects:
- Spatial Lagrangean decomposition -- Large-scale nonconvex optimization -- Integrated refinery-petrochemical complex -- Short-term planning
Chemical engineering -- Data processing -- Periodicals
660.0285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00981354 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compchemeng.2023.108229 ↗
- Languages:
- English
- ISSNs:
- 0098-1354
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.664000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 27023.xml