58. “Global Optimization of an Aggregated GDP Model for Distillation Sequences”.

LORENA BERGAMINI,; PIO A. AGUIRRE

Lyon Francia

Congreso; 18th European Symposium on Computer Aided Process Engineering (ESCAPE-18);; 2008

IFP Institute Francais de Petrole

An aggregated model for multicomponent distillation columns is first presented. The model allows predicting internal temperatures and flows for conventional columns operating at minimum reflux. The aggregated model is then embedded in a superstructure that corresponds to a sequence of distillation columns performing the separation of a multicomponent feed into pure components, and a Generalized Disjunctive model is generated. A new version of the Logic-Based Outer-Approximation for Global Optimization algorithm was used to overcome the difficulties for finding the global optimal solution due to nonconvexities of the feasible region. Lower bounding linear problems are set up, where the nonlinearities of the original model are replaced by piecewise underestimators. The algorithm solves iteratively global and local bounding MILP problems and reduced NLP problems. Convergence is achieved when the global bounding problem is infeasible, showing that there are no better solutions. The performance of the algorithm is illustrated with the separation of a four-component mixture. Keywords: distillation sequence - aggregated model - global optimization