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Optimizing scheduling of refinery operations based on piecewise linear models

Gao, X, Jiang, Y, Chen, T and Huang, D (2015) Optimizing scheduling of refinery operations based on piecewise linear models COMPUTERS & CHEMICAL ENGINEERING, 75. pp. 105-119.

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Abstract

Optimizing scheduling is an effective way to improve the profit of refineries; it usually requires accurate models to describe the complex and nonlinear refining processes. However, conventional nonlinear models will result in a complex mixed integer nonlinear programming (MINLP) problem for scheduling. This paper presents a piecewise linear (PWL) modeling approach, which can describe global nonlinearity with locally linear functions, to refinery scheduling. Specifically, a high level canonical PWL representation is adopted to give a simple yet effective partition of the domain of decision variables. Furthermore, a unified partitioning strategy is proposed to model multiple response functions defined on the same domain. Based on the proposed PWL partitioning and modeling strategy, the original MINLP can be replaced by mixed integer linear programming (MILP), which can be readily solved using standard optimization algorithms. The effectiveness of the proposed strategy is demonstrated by a case study originated from a refinery in China.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
AuthorsEmailORCID
Gao, XUNSPECIFIEDUNSPECIFIED
Jiang, YUNSPECIFIEDUNSPECIFIED
Chen, TUNSPECIFIEDUNSPECIFIED
Huang, DUNSPECIFIEDUNSPECIFIED
Date : 6 April 2015
Identification Number : 10.1016/j.compchemeng.2015.01.022
Uncontrolled Keywords : Science & Technology, Technology, Computer Science, Interdisciplinary Applications, Engineering, Chemical, Computer Science, Engineering, Optimization, Piecewise linear programming, Piecewise linear representation, Refinery scheduling, Unified simplicial partition, CONTINUOUS-TIME FORMULATION, HINGING HYPERPLANES, HIERARCHICAL APPROACH, SIMPLICIAL PARTITION, OPTIMIZATION, REPRESENTATION, REGRESSION
Related URLs :
Additional Information : © 2015. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Depositing User : Symplectic Elements
Date Deposited : 09 Sep 2015 12:39
Last Modified : 06 Apr 2016 01:08
URI: http://epubs.surrey.ac.uk/id/eprint/808423

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