Synthesis and Optimisation of Distillation Processes with MINLP Techniques
The synthesis of optimal distillation processes is of special importance for the chemical industry. This work investigates the use of novel "Mixed-Integer-Nonlinear-Programing" techniques to optimise such processes. These methods allow the rigorous optimisation of operational parameters (e.g. flows) and process structure (e.g. arrangement of columns) simultaneously. The application of MINLP algorithms to several chemical engineering processes is described and insight in the synthesis of complex distillation processes is given. Furthermore, new developments within the GAMS modelling environment are successfully applied to these processes. The results show that the used techniques provide a powerful tool for process synthesis since it is possible to obtain significant savings with respect to energy and investment costs and a deeper understanding of the processes.