Conference article

Industrial application of optimization with Modelica and Optimica using intelligent Python scripting

Karin Dietl
Siemens AG, Energy Sector, Erlangen, Germany

Stephanie Gallardo Yances
Siemens AG, Energy Sector, Erlangen, Germany

Anna Anna
Lund University, Department of Automatic Control, Lund, Sweden

Johan Åkesson
Modelon AB, Lund, Sweden

Kilian Link
Siemens AG, Energy Sector, Erlangen, Germany

Stéphane Velut
Modelon AB, Lund, Sweden

Download articlehttp://dx.doi.org/10.3384/ecp14096777

Published in: Proceedings of the 10th International Modelica Conference; March 10-12; 2014; Lund; Sweden

Linköping Electronic Conference Proceedings 96:81, p. 777-786

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Published: 2014-03-10

ISBN: 978-91-7519-380-9

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

Abstract

This paper shows how different kinds of optimi-zation related task such as offline optimization or optimal control are solved using a combina-tion of Modelica; Optimica; JModelica.org and Python. The application examples presented in this paper are all real industrial applications in the field of Combined Cycle Power Plants. Therefore different workflows have to be com-bined to solve the underlying task. This paper shows that these workflows can be conveniently connected using Python.

Keywords

Dynamic optimization; Nonlinear Model Predictive Control; Extended Kalman Filter

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