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...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:AIChE journal Ročník 62; číslo 6; s. 2043 - 2070
Hlavní autori: Li, Jie, Xiao, Xin, Floudas, Christodoulos A.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Blackwell Publishing Ltd 01.06.2016
American Institute of Chemical Engineers
Predmet:
Blenders
Blending
Blends
Constants
Delivery scheduling
Gasoline
global optimization
MINLP
mixed-integer nonlinear programming
multi-period
Nonlinear programming
Optimization
Petroleum engineering
refinery operations
Scheduling
ISSN:0001-1541, 1547-5905
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí: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
Bibliografia:ArticleID:AIC15168
ark:/67375/WNG-9WNT14H3-Z
istex:497D85AD2E6AC340B2C0518C0A9D0487D7832BF0
National Natural Science Foundation of China - No. 21206174
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0001-1541
1547-5905
DOI:10.1002/aic.15168