Global optimization of multicomponent distillation configurations: Global minimization of total cost for multicomponent mixture separations

• Published in: Computers & chemical engineering Vol. 126; no. C; pp. 249 - 262
• Main Authors: Jiang, Zheyu, Mathew, Tony Joseph, Zhang, Haibo, Huff, Joshua, Nallasivam, Ulaganathan, Tawarmalani, Mohit, Agrawal, Rakesh
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 12.07.2019; Elsevier
• Subjects: Cost optimization; Distillation configuration; ENGINEERING; Global optimization; Multicomponent distillation; Process intensification; Global optimization; Process intensification; Cost optimization; Multicomponent distillation; Distillation configuration
• ISSN: 0098-1354; 1873-4375
• DOI: 10.1016/j.compchemeng.2019.04.009

•A global optimization algorithm for total cost of distillation configurations.•Implement more accurate cost models and allow more flexible input from user.•The first of its kind that guarantees global optimality.•Discuss process intensification ideas to further upgrade identified configurations. We introduce a global optimization framework for determining the minimum cost required to distill any ideal or near-ideal multicomponent mixture into its individual constituents using a sequence of columns. This new framework extends the Global Minimization Algorithm (GMA) previously introduced by Nallasivam et al. (2016); and we refer to the new framework as the Global Minimization Algorithm for Cost (GMAC). GMAC guarantees global optimality by formulating a nonlinear program (NLP) for each and every distillation configuration in the search space and solving it using global optimization solvers. The case study presented in this work not only demonstrates the need for developing such an algorithm, but also shows the flexibility and effectiveness of GMAC, which enables process engineers to design and retrofit energy efficient and cost-effective distillation configurations.