Konferensartikel

Multi-Objective Optimization of Dynamic Systems combining Genetic Algorithms and Modelica: Application to Adsorption Air-Conditioning Systems

Uwe Bau
Institute of Technical Thermodynamics, RWTH Aachen University, Germany

Daniel Neitzke
Institute of Technical Thermodynamics, RWTH Aachen University, Germany

Franz Lanzerath
Institute of Technical Thermodynamics, RWTH Aachen University, Germany

André Bardow
Institute of Technical Thermodynamics, RWTH Aachen University, Germany

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp15118777

Ingår i: Proceedings of the 11th International Modelica Conference, Versailles, France, September 21-23, 2015

Linköping Electronic Conference Proceedings 118:83, s. 777-784

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Publicerad: 2015-09-18

ISBN: 978-91-7685-955-1

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

The Modelica language enables the fast and convenient development of physical simulation models. These models are often used for simulation studies. The re-use of simulation models for optimizations requires modeladaptions, additional tools or libraries. In this paper, we present a framework to connect Modelica models developed in Dymola to MATLAB’s optimization toolbox. As optimization algorithm, we use a multi-objective genetic algorithm. The optimization procedure is tested for an adsorption air-conditioning design. Compared to a full factorial design, the optimization procedure produces better solutions using less evaluations.

Nyckelord

multi-objective; optimization; Pareto-solution; dynamic systems; full factorial design; genetic; lgorithms; MATLAB; gamultiobj; NSGA-II; adsorption air-conditioning systems

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