Integration of modular process simulators under the Generalized Disjunctive Programming framework for the structural flowsheet optimization

• A new modeling framework that exploits the synergistic combination of commercial process simulators and GDP models.
• Our methodology allows to include easily logical relationships among alternatives.
• The proposed tool uses a logic based Outer Approximation algorithm.
• The methodology is applied to the synthesis of a methanol plant where different alternatives.

The optimization of chemical processes where the flowsheet topology is not kept fixed is a challenging discrete-continuous optimization problem. Usually, this task has been performed through equation based models. This approach presents several problems, as tedious and complicated component properties estimation or the handling of huge problems (with thousands of equations and variables). We propose a GDP approach as an alternative to the MINLP models coupled with a flowsheet program. The novelty of this approach relies on using a commercial modular process simulator where the superstructure is drawn directly on the graphical use interface of the simulator. This methodology takes advantage of modular process simulators (specially tailored numerical methods, reliability, and robustness) and the flexibility of the GDP formulation for the modeling and solution. The optimization tool proposed is successfully applied to the synthesis of a methanol plant where different alternatives are available for the streams, equipment and process conditions.