Multi-objective optimization of bioethanol reactive dehydration processes using genetic algorithms

The multi-objective optimization of different ethanol dehydration is presented. The objective functions are defined as maximizing ethanol purity and net profit while minimizing the total CO2 equivalent emissions. A link between MATLAB, Visual Basic and Aspen Plus was proposed to solve the multiobjective design problem. It was found that reactive dehydration systems advantage conventional azeotropic distillation, due to the generation of value-added products and that including an organic Rankine cycle also has the potential to take advantage of the exothermic nature of the involved reactions for the generation of electricity, thus yielding better processes from the economic and environmental aspects.