Kaibel column: Modeling, optimization, and conceptual design of multi-product dividing wall columns

• Published in: Computers & chemical engineering 2019-06, Vol.125, p.31-39
• Main Authors: Soraya Rawlings, E., Chen, Qi, Grossmann, Ignacio E., Caballero, Jose A.
• Format: Article
• Language: English
• Subjects: Dividing wall columns; General disjunctive programming; Kaibel column; Mixed integer nonlinear programming optimization; Nonlinear programming optimization
• ISSN: 0098-1354; 1873-4375
• DOI: 10.1016/j.compchemeng.2019.03.006

•The optimization and conceptual design of a Kaibel column is achieved by implementing an NLP, an MINLP, and a GDP formulation into a proposed rigorous tray-by-tray Kaibel column model.•The results obtained with the proposed rigorous tray-by-tray model are very similar to the results obtained using a commercial software.•The MINLP formulation is effective to determine the optimal location of side streams on the internal trays of the Kaibel column.•The GDP formulation is effective to determine the minimum number of trays in a Kaibel column.•A reduction on the remixing effects is observed when using the optimal design parameters obtained with the MINLP and GDP formulations. In this work, we present the modeling, optimization, and conceptual design of a dividing wall column for the separation of four products, commonly referred to in the literature as a Kaibel column, by implementing three different formulations: an NLP, an MINLP, and a GDP formulation. For its solution, we propose a rigorous tray-by-tray model and compared it to results from a commercial software, followed by its reformulation to include a mixed-integer nonlinear programming and a general disjunctive programming formulation to respond to the conceptual design problem attached to these complex configurations. Considering the proposed rigorous model and the two formulations, the Kaibel column is solved, obtaining four high-purity products and new optimal tray locations for the feed and two side product streams, when the mixed-integer nonlinear programming formulation is applied. The use of these optimally located side streams showed reductions in the energy consumption when compared to cases were non-optimal fixed tray locations are used. When the general disjunctive programming problem was solved, the minimum number of trays needed in the main column and dividing wall are obtained, showing a great reduction of the remixing effects in the Kaibel column, and with that, a more energy efficient configuration. The models were coded in Pyomo using the solver IPOPT for the solution of the nonlinear programming problem, the solver Bonmin for the solution of the mixed-integer nonlinear programming problem, and GDPopt for the solution of the general disjunctive programming optimization problem.