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Dynamic Process Intensification via Data-Driven Dynamic Optimization: Concept and Application to Ternary Distillation

delete2021-07-06
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OA
AI
L
Lingqing Yan
T
Tewodros Deneke
K
Keijo Heljanko
I
Iiro Harjunkoski
T
Thomas F. Edgar
M
Michael Bâldea *
DOI:10.1021/acs.iecr.1c01415delete
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摘要

摘要

En 中文
Process intensification is a design philosophy aimed at making chemical processes safer and more efficient. Its implementation often results in significant modifications to the design and structure of a process, with several conventional unit operations occurring in the same physical device. Traditionally, process intensification has focused on steady-state operation. In our previous works, we introduced dynamic process intensification (DPI) as a new intensification paradigm based on operational changes for conventional or intensified units. DPI is predicated on switching operation between two auxiliary steady states selected via a steady-state optimization calculation, which ensures that the system generates, on average and over time, the same products as in nominal steady-state operation, but with favorable economics. This paper extends the DPI concept and introduces a novel dynamic optimization-based DPI (Do-DPI) strategy that involves imposing a true cyclic operation rather than switching between two discrete states. We discuss its implementation using surrogate dynamic models learned via system identification. An extensive case study concerning a ternary distillation column separating a canonical hydrocarbon mixture shows that Do-DPI can reduce energy use by more than 4% relative to steady-state operation, with no significant deviations in product quality and production rate.
Keyword:
SYSTEMS
ENERGY
SCALE
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期刊

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Industrial and Engineering Chemistry Research
IF:
3.9
论文数:
4.0W
被引数:
9.6W

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university of helsinki
学者数:
4.1W
论文数: 3.6W
被引数: 51
U
university of texas austin
学者数:
2.4W
论文数: 2.0W
被引数: 54
U
university of texas system
学者数:
18.5W
论文数: 15.6W
被引数: 210
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