(408c) Design and Synthesis of Complex Distillation Networks with Hybrid Genetic Algorithm | AIChE

(408c) Design and Synthesis of Complex Distillation Networks with Hybrid Genetic Algorithm



We propose a novel computer-aided design for complex heat-integrated column networks to identify optimal energy efficient configurations. Since various complex column configurations including Petlyuk, Kaibel, divided wall columns, side-stripper and rectifiers have better energy efficiency than simple separation networks, we target to design complex column networks to separate multicomponent mixtures. However, complex column network synthesis is a challenging problem because the rigorous mass, equilibrium, summation and heat (MESH) equations lead to non-smooth fragmented search spaces. Therefore global optimization methods involving both structural and parametric degrees of freedom is still a challenge for existing math programming algorithms.

Moreover, combinatorial complexity grows rapidly with the number of components to be separated. Our design and synthesis approaches focus on solving these two main challenges. First new computer-aided design methodology deploys an inverse design methods based on temperature collocation which substantially reduces the problem dimension. Therefore it reduces the combinatorial complexity solving highly multi-dimensional mixture. Second, we developed hybrid genetic algorithm, in which stochastic GA elements can be combined with a local deterministic search. At first stage, GA iterates until individuals begin to coalesce and confines the region with niche technique. The gradient-based local optimizer follows to find a solution in this specified region. This hybrid scheme enables to find out all global and local solutions and thus improves accuracy of the solutions as well as the computation speed for finding solutions.

Our novel methods allow the global search for feasible, effective and optimal energy efficient designs of the complex distillation column network in a fully automatic fashion. To be verified as a design and synthesis solution in practice, we used the rigorous commercial flowsheet simulator AspenPlus and both results are prettily matched each other. Furthermore, the automatic and rigorous flowsheet synthesis is apt to systematically address industrial-size process design problems such as the synthesis of energy-efficient separation networks, layout of biorefineries with novel feedstocks or sustainable process for reduction of greenhouse gases emissions.