Reactive distillation for ETBE production: Setting the focus on the themodynamic model

DURRUTY, GISELA N.; DIAZ, MARIA SOLEDAD; HOCH, PATRICIA MÓNICA

Atlanta

Congreso; AIChe 2014 Annual Meeting; 2014

American Institution of Chemical Engineers

ETBE is a gasoline additive traditionally obtained from exothermic reaction of isobutene and ethanol. The conventional process includes the pretreatment of the butene and isobutene feed flows, reaction, purification, and recovery of non-reacted products, which renders an expensive process with high capital and operating costs (Weber de Menezes et al., 2008). A significant reduction in capital and operating costs can be achieved with reactive distillation (RD). This process combines reaction and distillation in one vessel, where products are continuously withdrawn, this resulting in a great benefit of the overall reaction, due to conversion increase. Reactive distillation also allows to reduce downstream processing and has a higher energy efficiency than conventional processes (Sharifzadeh, 2013). In this work we propose a model for the optimization of the RD unit for ETBE production, with both a rigorous thermodynamic model and hydraulic constraints together with MESH equations (mass, equilibrium, summation and enthalpy). The column consists of a reactive section with two feedflows (one of ethanol and the other of the n-butene and isobutene mix) and a rectifying and a stripping section at the top and bottom, respectively. The reactive section is modeled using the correlations for reaction kinetics from Al-Arfaj & Luyben, 2002. The thermodynamic model proposed here includes models for calculation of activity for the liquid phase (UNIFAC, Fredenslund, Gmehling, & Rasmussen, 1977) and fugacity for the vapor phase (SRK, Soave, 1972) with quadratic mixing rules. To the best of our knowledge, there is no reliable full set of parameters for these thermodynamic models. A parameter estimation problem is then posed, to adjust the parameters from experimental data. Thermodynamic predictions show good agreement with the data. The reactive distillation column model is then posed using the obtained set of parameters. The parameter estimation and the optimization are formulated in an equation oriented environment within GAMS (Brooke et al., 2011). In the parameter estimation problem the objective function is to minimize the sum of squares of the difference between experimental and predicted pressure and in the optimization the objective function is to minimize the total annual cost. Data for column economics are taken from Sharifzadeh, 2013. Results show that reactive distillation is a good alternative to reduce capital and operating costs.