A feasible path-based approach for Dividing Wall Column design procedure. (June 2021) - Di Pretoro, Alessandro; Ciranna, Flavia; Fedeli, Matteo; Joulia, Xavier; Montastruc, Ludovic; Manenti, Flavio
Highlights: A feasible path-based procedure allows to bypass the simulation failures due to the non-ideal thermodynamics or complex optimization algorithms. The proposed procedure use a shortcut design provided by ProSimPlus® process simulator to initialize the design algorithm coupled with rigorous process simulations. Although "non-optimal", the DWC design obtained via the feasible path-based procedure fulfills the expectations both from an economic and an environmental point of view with respect to the equivalent distillation train. Abstract: Process integration has become the best practice over the last years in separation units design. In particular, distillation trains can be reduced in a single column shell by means of internal separating wall under the name of Dividing Wall Column. This configuration allows on average for a 30% total costs reduction and is more and more popular for multicomponent mixtures purification. However, the DWC design optimization results much more complex than the one related to a series of standard distillation columns due to the higher number of column sections and side cuts. Moreover, in case of process simulation assisted design, the model convergence is very sensitive with respect to the initial guess, resulting in discontinuities in the sequence of optimization steps. In this paper an innovative design procedure based on feasible paths is presented for an ABEW mixture separation case study. Starting from a converged design based on shortcut methods, the number of trays can be increased and or removed from the proper column section selected with the help of composition profiles analysis. This procedure results to be particularly effective for non-ideal mixtures separations, such as the ABEW one, likely to undergo simulation convergence failures. This design algorithm provides an optimized solution really close to the optimal one in a relatively short time and without the need to solve the related MINLP problem.