An MINLP formulation for the optimization of multicomponent distillation configurations
Abstract
Designing configurations for multicomponent distillation, a ubiquitous process in chemical and petrochemical industries, is often challenging. This is because, as the number of components increases, the number of admissible distillation configurations grows rapidly and these configurations vary substantially in their energy needs. Consequently, if a method could identify a few energyefficient choices from this large set of alternatives, it would be extremely attractive to process designers. This paper develops here such a method by solving a Mixed Integer Nonlinear Program (MINLP) that is formulated to pick, among the regularcolumn configurations of Shah and Agrawal (2010b), those configurations that have a low vaporduty requirement. To compute the minimum vaporduty requirement for each column within the configuration, we use techniques that rely on the Underwood’s method. The combined difficulty arising from the nonlinearity of Underwood equations and the combinatorial explosion of the choiceset of alternatives poses unmistakable challenges for the branchandbound algorithm, the current method of choice to globally solve MINLPs. To address this difficulty, we exploit the structure of Underwood equations and derive valid cuts that expedite the convergence of branchandbound by enabling global solvers, such as BARON, infer tighter bounds on Underwood roots. This provides a quick way to identifymore »
 Authors:

 Purdue Univ., West Lafayette, IN (United States). Davidson School of Chemical Engineering
 Purdue Univ., West Lafayette, IN (United States). Krannert School of Management
 Publication Date:
 Research Org.:
 Purdue Univ., West Lafayette, IN (United States)
 Sponsoring Org.:
 USDOE Office of Energy Efficiency and Renewable Energy (EERE), Advanced Manufacturing Office (EE5A)
 OSTI Identifier:
 1511496
 Grant/Contract Number:
 EE0005768
 Resource Type:
 Journal Article: Accepted Manuscript
 Journal Name:
 Computers and Chemical Engineering
 Additional Journal Information:
 Journal Volume: 125; Journal ID: ISSN 00981354
 Publisher:
 Elsevier
 Country of Publication:
 United States
 Language:
 English
 Subject:
 42 ENGINEERING; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; multicomponent distillation; mixed integer nonlinear program; fractional program; global optimization
Citation Formats
Tumbalam Gooty, Radhakrishna, Agrawal, Rakesh, and Tawarmalani, Mohit. An MINLP formulation for the optimization of multicomponent distillation configurations. United States: N. p., 2019.
Web. doi:10.1016/j.compchemeng.2019.02.013.
Tumbalam Gooty, Radhakrishna, Agrawal, Rakesh, & Tawarmalani, Mohit. An MINLP formulation for the optimization of multicomponent distillation configurations. United States. doi:10.1016/j.compchemeng.2019.02.013.
Tumbalam Gooty, Radhakrishna, Agrawal, Rakesh, and Tawarmalani, Mohit. Thu .
"An MINLP formulation for the optimization of multicomponent distillation configurations". United States. doi:10.1016/j.compchemeng.2019.02.013. https://www.osti.gov/servlets/purl/1511496.
@article{osti_1511496,
title = {An MINLP formulation for the optimization of multicomponent distillation configurations},
author = {Tumbalam Gooty, Radhakrishna and Agrawal, Rakesh and Tawarmalani, Mohit},
abstractNote = {Designing configurations for multicomponent distillation, a ubiquitous process in chemical and petrochemical industries, is often challenging. This is because, as the number of components increases, the number of admissible distillation configurations grows rapidly and these configurations vary substantially in their energy needs. Consequently, if a method could identify a few energyefficient choices from this large set of alternatives, it would be extremely attractive to process designers. This paper develops here such a method by solving a Mixed Integer Nonlinear Program (MINLP) that is formulated to pick, among the regularcolumn configurations of Shah and Agrawal (2010b), those configurations that have a low vaporduty requirement. To compute the minimum vaporduty requirement for each column within the configuration, we use techniques that rely on the Underwood’s method. The combined difficulty arising from the nonlinearity of Underwood equations and the combinatorial explosion of the choiceset of alternatives poses unmistakable challenges for the branchandbound algorithm, the current method of choice to globally solve MINLPs. To address this difficulty, we exploit the structure of Underwood equations and derive valid cuts that expedite the convergence of branchandbound by enabling global solvers, such as BARON, infer tighter bounds on Underwood roots. This provides a quick way to identify a few lucrative alternative configurations for separation of a given nonazeotropic mixture. We illustrate the practicality of our approach on a casestudy concerning heavycrude distillation and on various other examples from the literature.},
doi = {10.1016/j.compchemeng.2019.02.013},
journal = {Computers and Chemical Engineering},
issn = {00981354},
number = ,
volume = 125,
place = {United States},
year = {2019},
month = {3}
}
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