Optimization of an Ethanol Dehydration Process Using Differential Evolution Algorithm

Due to the increasing demand for new fuels that are economically attractive, and as part of the quest for energy alternatives to replace carbon-based fuels, the purification of ethanol plays a key role. Bioethanol is an environmentally-friendly fuel with less greenhouse gases emissions than gasoline, but with similar energy power. Nevertheless the large-scale production of bioethanol fuel requires energy demanding distillation steps to concentrate the diluted streams from the fermentation step and to overcome the azeotropic behavior of the ethanol-water mixture. This work presents the design and optimization of a dehydration process for ethanol, using two separation sequences: a conventional arrangement using distillation and extractive distillation and an alternative arrangement based on liquid-liquid extraction and extractive distillation. Moreover, different solvents were optimized simultaneously in the liquid-liquid extraction column, while ethylene glycol was used as extractive agent in the extractive distillation (ED). Both sequences were optimized using a stochastic global optimization algorithm of differential evolution (DE) coupled to rigorous Aspen Plus simulations. The economic feasibility of utilities for the two configurations was studied by changing the ethanol/water composition in the analyzed feed stream. The results demonstrate significant savings around 20% in total annual cost when the alternative arrangement is used.