Integrated gasoline blending and order delivery operations: Part I. short-term scheduling and global optimization for single and multi-period operations
Gasoline is one of the most valuable products in an oil refinery and can account for as much as 60–70% of total profit. Optimal integrated scheduling of gasoline blending and order delivery operations can significantly increase profit by avoiding ship demurrage, improving customer satisfaction, mini...
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| Vydané v: | AIChE journal Ročník 62; číslo 6; s. 2043 - 2070 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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New York
Blackwell Publishing Ltd
01.06.2016
American Institute of Chemical Engineers |
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| ISSN: | 0001-1541, 1547-5905 |
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| Abstract | Gasoline is one of the most valuable products in an oil refinery and can account for as much as 60–70% of total profit. Optimal integrated scheduling of gasoline blending and order delivery operations can significantly increase profit by avoiding ship demurrage, improving customer satisfaction, minimizing quality give‐aways, reducing costly transitions and slop generation, exploiting low‐quality cuts, and reducing inventory costs. In this article, we first introduce a new unit‐specific event‐based continuous‐time formulation for the integrated treatment of recipes, blending, and scheduling of gasoline blending and order delivery operations. Many operational features are included such as nonidentical parallel blenders, constant blending rate, minimum blend length and amount, blender transition times, multipurpose product tanks, changeovers, and piecewise constant profiles for blend component qualities and feed rates. To address the nonconvexities arising from forcing constant blending rates during a run, we propose a hybrid global optimization approach incorporating a schedule adjustment procedure, iteratively via a mixed‐integer programming and nonlinear programming scheme, and a rigorous deterministic global optimization approach. The computational results demonstrate that our proposed formulation does improve the mixed‐integer linear programming relaxation of Li and Karimi, Ind. Eng. Chem. Res., 2011, 50, 9156–9174. All examples are solved to be 1%‐global optimality with modest computational effort. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2043–2070, 2016 |
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| AbstractList | Gasoline is one of the most valuable products in an oil refinery and can account for as much as 60–70% of total profit. Optimal integrated scheduling of gasoline blending and order delivery operations can significantly increase profit by avoiding ship demurrage, improving customer satisfaction, minimizing quality give‐aways, reducing costly transitions and slop generation, exploiting low‐quality cuts, and reducing inventory costs. In this article, we first introduce a new unit‐specific event‐based continuous‐time formulation for the integrated treatment of recipes, blending, and scheduling of gasoline blending and order delivery operations. Many operational features are included such as nonidentical parallel blenders, constant blending rate, minimum blend length and amount, blender transition times, multipurpose product tanks, changeovers, and piecewise constant profiles for blend component qualities and feed rates. To address the nonconvexities arising from forcing constant blending rates during a run, we propose a hybrid global optimization approach incorporating a schedule adjustment procedure, iteratively via a mixed‐integer programming and nonlinear programming scheme, and a rigorous deterministic global optimization approach. The computational results demonstrate that our proposed formulation does improve the mixed‐integer linear programming relaxation of Li and Karimi, Ind. Eng. Chem. Res., 2011, 50, 9156–9174. All examples are solved to be 1%‐global optimality with modest computational effort. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2043–2070, 2016 Gasoline is one of the most valuable products in an oil refinery and can account for as much as 60-70% of total profit. Optimal integrated scheduling of gasoline blending and order delivery operations can significantly increase profit by avoiding ship demurrage, improving customer satisfaction, minimizing quality give-aways, reducing costly transitions and slop generation, exploiting low-quality cuts, and reducing inventory costs. In this article, we first introduce a new unit-specific event-based continuous-time formulation for the integrated treatment of recipes, blending, and scheduling of gasoline blending and order delivery operations. Many operational features are included such as nonidentical parallel blenders, constant blending rate, minimum blend length and amount, blender transition times, multipurpose product tanks, changeovers, and piecewise constant profiles for blend component qualities and feed rates. To address the nonconvexities arising from forcing constant blending rates during a run, we propose a hybrid global optimization approach incorporating a schedule adjustment procedure, iteratively via a mixed-integer programming and nonlinear programming scheme, and a rigorous deterministic global optimization approach. The computational results demonstrate that our proposed formulation does improve the mixed-integer linear programming relaxation of Li and Karimi, Ind. Eng. Chem. Res., 2011, 50, 9156-9174. All examples are solved to be 1%-global optimality with modest computational effort. [copy 2016 American Institute of Chemical Engineers AIChE J, 62: 2043-2070, 2016 |
| Author | Floudas, Christodoulos A. Xiao, Xin Li, Jie |
| Author_xml | – sequence: 1 givenname: Jie surname: Li fullname: Li, Jie organization: Artie McFerrin Dept. of Chemical Engineering, Texas A&M University, 77843, College Station, TX – sequence: 2 givenname: Xin surname: Xiao fullname: Xiao, Xin organization: State Key Laboratory of Multiphase Complex Systems, Institute of Process Engineering, Chinese Academy of Sciences, 100190, Beijing, P. R. China – sequence: 3 givenname: Christodoulos A. surname: Floudas fullname: Floudas, Christodoulos A. email: floudas@tamu.edu organization: Artie McFerrin Dept. of Chemical Engineering, Texas A&M University, 77843, College Station, TX |
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| Cites_doi | 10.1021/ie0204843 10.1016/j.compchemeng.2004.05.002 10.1016/S0098-1354(01)00643-3 10.1007/s10898-012-9874-7 10.1002/aic.12623 10.1007/s10107-012-0555-6 10.1021/ie970927g 10.1007/s10957-013-0396-3 10.1080/10556788.2014.916287 10.1002/aic.11970 10.1002/aic.14423 10.1016/S0098-1354(00)00571-8 10.1016/j.compchemeng.2006.02.008 10.1002/aic.14444 10.1007/s10898-014-0166-2 10.1287/inte.19.1.85 10.1021/ie011002a 10.1002/aic.11280 10.1021/ie9709289 10.1021/ie901842k 10.1016/j.compchemeng.2015.08.003 10.1016/j.compchemeng.2015.08.005 10.1007/s10479-005-3446-x 10.1016/j.compchemeng.2005.05.010 10.1016/j.compchemeng.2005.11.004 10.1007/BF02591747 10.1016/j.compchemeng.2007.03.019 10.1016/j.compchemeng.2013.12.001 10.1021/ie102321b 10.1021/ie1010004 10.1021/ie0600590 10.1021/ie0600588 10.1021/ie0341597 10.1021/ie8010726 10.1287/inte.25.5.64 |
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| References_xml | – reference: Jia Z, Ierapetritou MG. Mixed-integer linear programming model for gasoline blending and distribution scheduling. Ind Eng Chem Res. 2003;42:825-835. – reference: Li J, Karimi IA, Srinivasan R. Recipe determination and scheduling of gasoline blending operations. AIChE J. 2010;56(2):441-465. – reference: Cao C, Gu X, Zhong X. A data-driven rolling-horizon online scheduling model for diesel produciton of a real-world refinery. AIChE J. 2014;59(4):1160-1174. – reference: Castillo PAC, Mahalec V. Inventory pinch based, multiscale models for integrated planning and scheduling-part II: gasoline blend scheduling. AIChE J. 2014;60:2475-2497. – reference: Misener R, Floudas CA. Global optimization of mixed-integer quadratically-constrained quadratic programs (MIQCQP) through Piecewise-Linear and Edge-Concave relaxations. Math Prog Ser B. 2012;136:155-182. – reference: Castillo PAC, Mahalec V. Inventory pinch based, multiscale models for integrated planning and scheduling-part I: gasoline blending planning. AIChE J. 2014;60:2158-2178. – reference: Shah NK, Li Z, Ierapetritou MG. Petroleum refining operations: key issues, advances, and opportunities. Ind Eng Chem Res. 2011;50(3):1161-1170. – reference: Janak SL, Floudas CA. Improving unit-specific event based continuous-time approaches for batch processes: integrality gap and task splitting. Comp Chem Eng. 2008;32:913-955. – reference: Castillo PAC, Mahalec V. Improved continuous-time model for gasoline blend scheduling. Comp Chem Eng. 2015;84:627-646. – reference: Li J, Floudas CA. Optimal event point determination for short-term scheduling of multipurpose batch plants via unit-specific event-based continuous-time approaches. Ind Eng Chem Res. 2010;49:7446-7469. – reference: Lin X, Floudas CA, Modi S, Juhasz NM. Continuous-time optimization approach for medium-range production scheduling of a multiproduct batch plant. Ind Eng Chem Res. 2002;41:3884-3906. – reference: Li J, Misener R, Floudas CA. Continuous-time modeling and global optimization approach for scheduling of crude oil operations. AIChE J. 2012;58(1):205-226. – reference: Dewitt CW, Lasdon LS, Waren AD, Brenner DA, Melhem SA. OMEGA: an improved gasoline blending system for Texaco. Interfaces. 1989;19:85-101. – reference: Li J, Li W, Karimi IA, Srinivasan R. Improving the robustness and efficiency of crude scheduling algorithms. AIChE J. 2007;53(10):2659-2680. – reference: Castillo PAC, Mahalec V. Inventory pinch gasoline blend scheduling algorithm combing discrete- and continuous-time models. Comp Chem Eng. 2015;84:611-626. – reference: Pinto JM, Joly M, Moro LFL. Planning and scheduling models for refinery operations. Comp Chem Eng. 2000;24:2259-2276. – reference: Harjunkoski I, Maravelias CT, Bongers P, Castro P, Engell S, Grossmann IE, Hooker J, Méndez C, Sand G, Wassick J. 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| SubjectTerms | Blenders Blending Blends Constants Delivery scheduling Gasoline global optimization MINLP mixed-integer nonlinear programming multi-period Nonlinear programming Optimization Petroleum engineering refinery operations Scheduling |
| Title | Integrated gasoline blending and order delivery operations: Part I. short-term scheduling and global optimization for single and multi-period operations |
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