Process Optimization of the Methanol Synthesis Using Different Local Optimization Algorithms

Abstract

Prozessoptimierung wird oft mit wenig flexibler Optimierungsfunktionalität in Prozesssimulatoren oder nach zeitintensiver Modellierung und Implementierung in algebraischen Modellierungssprachen durchgeführt. Der in dieser Arbeit angewandte hybride Ansatz nutzt Vorteile beider Methoden: MATLAB wird als Optimierungsplattform mit dem Prozesssimulator UniSim Design gekoppelt. Der Ansatz wird am Beispiel der industriellen Methanolsynthese evaluiert. Für die Optimierung werden gradientenbasierte und ableitungsfreie Algorithmen angewendet und so bestehende Arbeiten auf dem Gebiet sinnvoll ergänzt.

Multi‐criteria Optimization of an Industrial World‐Scale Process

“…The recycle tolerances were reduced to 10 −6 to avoid dominated points as result. This measure has also been encouraged in , where the application of different starting points in objective space is recommended, too. The flash tolerance was set to 10 −8 .…”

“…The cited paper also provides a wide overview of publications on combinations between flow sheet simulators and external optimization solvers. In a recent report, Sundberg et al compared the performance of three different optimization solvers during the optimization of a flow sheet for methanol synthesis implemented in UniSim . For additional applications of this method to process optimization, see , , .…”

A Framework for Multi-Objective Optimization of Plate-Fin Heat Exchangers Using a Detailed Three-Dimensional Simulation Model

“…Because of the generalized approach presented in this work, possible correlations between objectives and design variables are considered to be unknown. They are only accessible through a numerical solution of the PFHE simulation model, which is thus treated as a blackbox [40]. Derivative-free evolutionary algorithms are suitable for the global optimization of such tasks [41].…”

Process Modeling, Simulation and Optimization: From Single Solutions to a Multitude of Solutions to Support Decision Making

“…Kurnatowski et al show an example using MCO with the commercial flowsheet simulator ChemCAD via an Excel‐VBA interface for the optimization of an industrial process. Sundberg et al give a literature overview on optimization interfaces and used methods and show an application of such an implementation based on a coupling of Matlab with UNISIM for the optimization of a Methanol process. Janus et al show results utilizing a memetic algorithm, which combines an evolutionary algorithm with a local optimization method, for the optimization of an ethanol dehydration process modeled in ASPEN plus.…”