Steady-state Optimization of Modelica Models and Functional Mockup Units with Pyomo

This paper describes two ways on how to interface Functional Mockup Units (FMUs) and Modelica models through the Pyomo’s foreign function interface with Pyomo. Pyomo is a Python-based, open-source optimization modeling language with a diverse set of optimization capabilities. Modelica has arguably much better modeling capabilities than Pyomo, but Pyomo integrates excellent optimization solvers, such as Ipopt (Wächter et al. 2006), and provides a good optimization infrastructure. The Interface has been developed in the context of a NAWI, (National Alliance Water Innovation) Hub project in collaboration with the University of Connecticut and Sandia National Labs. The optimization has been set up and tested within Modelon’s Modelica platform Modelon Impact. An unpublished, detailed multi-effect desalination plant developed by Prof. Matt Stuber in the context of (Stuber et al., 2015) has been used to demonstrate the capabilities, as well as simple test models, and design models from Modelon’s commercial Libraries.

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Publication Details

Journal
Linköping electronic conference proceedings
Published
2025-01-16
DOI
https://doi.org/10.3384/ecp207109
Primary Topic
Modeling and Simulation Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Steady-state Optimization of Modelica Models and Functional Mockup Units with Pyomo

Matthew D. Stuber, Robin Andersson, Jesse Gohl, Hubertus Tummescheit
Linköping electronic conference proceedings
Modeling and Simulation Systems
article

Steady-state Optimization of Modelica Models and Functional Mockup Units with Pyomo

Matthew D. Stuber, Robin Andersson, Jesse Gohl, Hubertus Tummescheit
article en

Abstract

This paper describes two ways on how to interface Functional Mockup Units (FMUs) and Modelica models through the Pyomo’s foreign function interface with Pyomo. Pyomo is a Python-based, open-source optimization modeling language with a diverse set of optimization capabilities. Modelica has arguably much better modeling capabilities than Pyomo, but Pyomo integrates excellent optimization solvers, such as Ipopt (Wächter et al. 2006), and provides a good optimization infrastructure. The Interface has been developed in the context of a NAWI, (National Alliance Water Innovation) Hub project in collaboration with the University of Connecticut and Sandia National Labs. The optimization has been set up and tested within Modelon’s Modelica platform Modelon Impact. An unpublished, detailed multi-effect desalination plant developed by Prof. Matt Stuber in the context of (Stuber et al., 2015) has been used to demonstrate the capabilities, as well as simple test models, and design models from Modelon’s commercial Libraries.

Linköping electronic conference proceedingsVol. 207
University of Connecticut (US)
U.S. Department of Energy, University of Connecticut, Office of Energy Efficiency and Renewable Energy, Office of Energy Efficiency
Openalex Percentile: Top 98%
Modeling and Simulation Systems
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