Multi-objective optimization of dividing wall columns under model and process parametric uncertainties

点击翻译按钮获取中文摘要

Dividing wall columns have the potential of significant energy savings compared to conventional distillation trains, with high product purities at the same time. This potential can be realized if the column design is optimally adapted to the respective separation task. In preliminary work by the applicants, novel approaches for model-based simulation and optimization have been developed for this purpose. In this project, the aim is to take uncertainties into account in these optimization results and to develop strategies for reacting to such uncertainties in the best possible way. On the one hand, this involves operational uncertainties - such as fluctuating reactant compositions - and on the other hand, uncertainties in physical model parameters, such as for the description of thermodynamic equilibria. The aim of this project is to develop model-based strategies in the choice of degrees of freedom in the design and operation of the columns, so that these uncertainties have as little impact as possible on the energy-saving potential and product purities addressed above. The scientific challenge is to distinguish between the degrees of freedom in design and operational management: The former are fixed once at the beginning and cannot be changed thereafter; the latter are flexibly adjustable during operation within a certain window. This leads to a novel class of multi-objective optimization problems. Based on the preliminary work of the applicants, there is now the possibility to solve these and thus to arrive at insights and methods relevant for the application.