Optimal operation of parallel distillation systems with multiple product grades: An industrial case study

Yingyan Luo; Qi Zhang; Lingyu Zhu; Xi Chen

doi:10.1016/j.compchemeng.2018.01.009

Optimal operation of parallel distillation systems with multiple product grades: An industrial case study

Yingyan Luo, Qi Zhang, Lingyu Zhu, Xi Chen

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

In the fine chemical industry, customers often demand different grades with different purity specifications. To achieve the best performance, the production tasks should be assigned to different distillation columns at the most suitable operating conditions and time periods. In this paper, an optimal scheduling method is presented through an industrial case study with multiple products and parallel distillation columns. Rigorous nonlinear models are built for each distillation column and validated with plant data, based on which, a reduced-order model is obtained with data of optimal operating points at various conditions. The reduced-order model is then incorporated into a mode-based discrete-time mixed integer linear program (MILP) scheduling model, where transitions between different operating modes are specified based on plant data. The MILP-based scheduling is applied to a real-word industrial case study to demonstrate its computational efficiency and effectiveness in improving economic performance with comparison to two heuristic scheduling methods.

Original language	English (US)
Pages (from-to)	210-224
Number of pages	15
Journal	Computers and Chemical Engineering
Volume	111
DOIs	https://doi.org/10.1016/j.compchemeng.2018.01.009
State	Published - Mar 4 2018
Externally published	Yes

Bibliographical note

Funding Information:
The authors gratefully acknowledge the financial support of NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (No. U1509209 ). Dr. L. Zhu would like also acknowledge the financial support of National Key Research and Development Program (No. 2017YFB0603703 ).

Publisher Copyright:
© 2018 Elsevier Ltd

Keywords

Multiple products
Optimal scheduling
Parallel distillation systems
Reduced-order model

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title = "Optimal operation of parallel distillation systems with multiple product grades: An industrial case study",

abstract = "In the fine chemical industry, customers often demand different grades with different purity specifications. To achieve the best performance, the production tasks should be assigned to different distillation columns at the most suitable operating conditions and time periods. In this paper, an optimal scheduling method is presented through an industrial case study with multiple products and parallel distillation columns. Rigorous nonlinear models are built for each distillation column and validated with plant data, based on which, a reduced-order model is obtained with data of optimal operating points at various conditions. The reduced-order model is then incorporated into a mode-based discrete-time mixed integer linear program (MILP) scheduling model, where transitions between different operating modes are specified based on plant data. The MILP-based scheduling is applied to a real-word industrial case study to demonstrate its computational efficiency and effectiveness in improving economic performance with comparison to two heuristic scheduling methods.",

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note = "Funding Information: The authors gratefully acknowledge the financial support of NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (No. U1509209 ). Dr. L. Zhu would like also acknowledge the financial support of National Key Research and Development Program (No. 2017YFB0603703 ). Publisher Copyright: {\textcopyright} 2018 Elsevier Ltd",

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AU - Zhang, Qi

AU - Zhu, Lingyu

AU - Chen, Xi

N1 - Funding Information: The authors gratefully acknowledge the financial support of NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (No. U1509209 ). Dr. L. Zhu would like also acknowledge the financial support of National Key Research and Development Program (No. 2017YFB0603703 ). Publisher Copyright: © 2018 Elsevier Ltd

PY - 2018/3/4

Y1 - 2018/3/4

N2 - In the fine chemical industry, customers often demand different grades with different purity specifications. To achieve the best performance, the production tasks should be assigned to different distillation columns at the most suitable operating conditions and time periods. In this paper, an optimal scheduling method is presented through an industrial case study with multiple products and parallel distillation columns. Rigorous nonlinear models are built for each distillation column and validated with plant data, based on which, a reduced-order model is obtained with data of optimal operating points at various conditions. The reduced-order model is then incorporated into a mode-based discrete-time mixed integer linear program (MILP) scheduling model, where transitions between different operating modes are specified based on plant data. The MILP-based scheduling is applied to a real-word industrial case study to demonstrate its computational efficiency and effectiveness in improving economic performance with comparison to two heuristic scheduling methods.

AB - In the fine chemical industry, customers often demand different grades with different purity specifications. To achieve the best performance, the production tasks should be assigned to different distillation columns at the most suitable operating conditions and time periods. In this paper, an optimal scheduling method is presented through an industrial case study with multiple products and parallel distillation columns. Rigorous nonlinear models are built for each distillation column and validated with plant data, based on which, a reduced-order model is obtained with data of optimal operating points at various conditions. The reduced-order model is then incorporated into a mode-based discrete-time mixed integer linear program (MILP) scheduling model, where transitions between different operating modes are specified based on plant data. The MILP-based scheduling is applied to a real-word industrial case study to demonstrate its computational efficiency and effectiveness in improving economic performance with comparison to two heuristic scheduling methods.

KW - Multiple products

KW - Optimal scheduling

KW - Parallel distillation systems

KW - Reduced-order model

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Optimal operation of parallel distillation systems with multiple product grades: An industrial case study

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Keywords

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