Advances in MINLP to Identify Energy-Efficient Distillation Configurations
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907,; OSTI
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907,
- Krannert School of Management, Purdue University, West Lafayette, Indiana 47907
Separation of mixtures of chemicals, ubiquitous in chemical and petrochemical industries, by distillation is energy intensive. Nearly 3% of the overall energy is used for distillation in the United States. Improving the distillation process is crucial for making chemical industries more sustainable. However, designing distillation sequences is challenging because the choice set is vast, and the equations governing the physical process are highly nonconvex. Traditional design practices rely on heuristics and often result in suboptimal solutions. Tumbalam Gooty et al. present the first approach that reliably identifies the distillation sequence that requires the least energy for a given separation. By embedding convex hulls of substructures and adapting the reformulation-linearization technique to fractions of polynomials, they demonstrated that their approach outperforms the state-of-the-art. Their work will help the chemical industry reduce greenhouse gas emissions associated with distillation.
- Research Organization:
- Purdue Univ., West Lafayette, IN (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- DOE Contract Number:
- EE0005768;
- OSTI ID:
- 1980964
- Journal Information:
- Operations Research, Journal Name: Operations Research; ISSN 0030-364X
- Publisher:
- INFORMS
- Country of Publication:
- United States
- Language:
- English
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