Rigorous NLP distillation models for simultaneous optimization to reduce utility and capital costs

Yeoh, Keat Ping; Hui, Chi Wai

doi:10.1016/j.clet.2021.100066

Cited by 6 publications

(3 citation statements)

References 25 publications

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“…For optimization, the PTC model guarantees robustness, and a bypass efficiency method is used to optimize the number of plates efficiently. Based on the concept of bypass efficiency, Yeoh et al [22] proposed two NLP models with a strict plate-to-plate MESH calculation. The models can be used to simultaneously optimize the N, N F , and operating parameters such as the R and P.…”

Section: Previous Research On Distillation Column Designmentioning

confidence: 99%

Intelligent Optimization Design of Distillation Columns Using Surrogate Models Based on GA-BP

Zhang

et al. 2023

Processes

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The design of distillation columns significantly impacts the economy, energy consumption, and environment of chemical processes. However, optimizing the design of distillation columns is a very challenging problem. In order to develop an intelligent technique to obtain the best design solution, improve design efficiency, and minimize reliance on experience in the design process, a design methodology based on the GA-BP model is proposed in this paper. Firstly, a distillation column surrogate model is established using the back propagation neural network technique based on the training data from the rigorous simulation, which covers all possible changes in feed conditions, operating conditions, and design parameters. The essence of this step is to turn the distillation design process from model-driven to data-driven. Secondly, the model takes the minimum TAC as the objective function and performs the optimization search using a Genetic Algorithm to obtain the design solution with the minimum TAC, in which a life-cycle assessment (LCA) model is incorporated to evaluate the obtained optimized design solution from both economic and environmental aspects. Finally, the feasibility of the proposed method is verified with a propylene distillation column as an example. The results show that the method has advantages in convergence speed without sacrificing accuracy and can obtain an improved design solution with reduced cost and environmental impact. Compared with the original design using rigorous simulation, the TAC is reduced by 6.1% and carbon emission by 27.13 kgCO2/t.

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Section: Previous Research On Distillation Column Designmentioning

confidence: 99%

Intelligent Optimization Design of Distillation Columns Using Surrogate Models Based on GA-BP

Zhang

et al. 2023

Processes

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show abstract

“…The graphical McCabe-Thiele and Ponchon-Savarit methods are well known in the literature [10][11][12][13]. Therefore, a detailed thermodynamic description of these methods is not hereby provided.…”

Section: Model Developmentmentioning

confidence: 99%

“…McCabe-Tile Method This methods hinges upon the fact that, as an approximation, the operating lines on − diagram can be considered straight for each section of the fractionator [6,11,12,16]. The parameters available are the concentration of in the top product (in the condenser) -, the concentration of in the bottom product (in the reboiler) -, and the concentration of in the feed stream -.…”

Section: Construction Of the Operating Lines Of Thementioning

confidence: 99%

Computation Programming of McCabe-Thiele and Ponchon-Savarit Methods for SHORT-CUT Distillation Design

Chilev¹,

Dicko²,

Langlois³

et al. 2021

IJSTS

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Boundary function method for stage number optimization for multi-stage distillation process design

Jia

Cao

Qian

et al. 2023

Chemical Engineering Science

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Rigorous NLP distillation models for simultaneous optimization to reduce utility and capital costs

Cited by 6 publications

References 25 publications

Intelligent Optimization Design of Distillation Columns Using Surrogate Models Based on GA-BP

Intelligent Optimization Design of Distillation Columns Using Surrogate Models Based on GA-BP

Computation Programming of McCabe-Thiele and Ponchon-Savarit Methods for SHORT-CUT Distillation Design

Boundary function method for stage number optimization for multi-stage distillation process design

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