Conceptual design and optimization of chemical processes under uncertainty by two-stage programming

• A tool for the optimization of flow sheets under uncertainty was developed.
• A two-stage stochastic programming approach is used to model the problems.
• A hybrid algorithm coupled with IPOPT for solving the scenario problems is used.
• Two chemical processes are modelled and optimized.
• Considering recourse during the design phase can reduce the impact of uncertainty.

This contribution presents a method and a tool for modelling and optimizing process superstructures in the early phase of process design where the models of the processing units and other data are inaccurate. To adequately deal with this uncertainty, we employ a two-stage formulation where the operational parameters can be adapted to the realization of the uncertainty while the design parameters are the first-stage decisions. The uncertainty is represented by a set of discrete scenarios and the optimization problem is solved by stage decomposition. The approach is implemented in the computer tool FSOpt (Flow sheet Superstructure Optimization) FSOpt provides a flexible environment for the modelling of the unit operations and the generation of superstructures and algorithms for the translation of the superstructure into non-linear programming models.The approach is applied to two case studies, the hydroformylation of dodec-1-ene and the separation of an azeotropic mixture of water and formic acid.