Marcus Fuchs
RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Aachen, Germany
Rita Streblow
RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Aachen, Germany
Dirk Müller
RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Aachen, Germany
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http://dx.doi.org/10.3384/ecp15118737Ingår i: Proceedings of the 11th International Modelica Conference, Versailles, France, September 21-23, 2015
Linköping Electronic Conference Proceedings 118:79, s. 737-745
Publicerad: 2015-09-18
ISBN: 978-91-7685-955-1
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
Models of large thermo-fluid networks can be useful to better understand the dynamic behavior of complex systems. Yet, numerical outputs and line plots of individual variables may not be sufficient ways of processing the simulation results for the user. Thus, the aim of this paper is to present a visualization approach by means of graph drawing. To demonstrate the approach, we use an example from the Modelica Standard Library and the use case of a district heating system model. We parse the Modelica model code to generate a {\tt System} graph that represents the model structure and its graphical layout. The graph drawing subsequently visualizes the results for every time-step. In the examples, we vary line thickness to visualize mass flow rates between two nodes and line color to show temperatures of the medium. We argue, that this approach can be a useful tool for modeling and analysis.
Francesco Casella, Martin Otter, Katrin Proelss, Christoph Richter, and Hubertus Tummescheit. The Modelica Fluid and Media library for modeling of incompressible and compressible thermo-fluid pipe networks. In Modelica Association, editor, Proceedings of the 5th International Modelica Conference, pages 631–640, 2006.
Kevin Davies. ModelicaRes python package, 2015. URL http://kdavies4.github.io/ModelicaRes/.
Roel De Conick. awesim python package, 2015. URL https://github.com/saroele/awesim.
Arash M. Dizqah, Alireza Maheri, Krishna Busawon, and Peter Fritzson. Standalone DC microgrids as complementarity dynamical systems: Modeling and applications. Control Engineering Practice, 35:102–112, 2015. ISSN 09670661. doi: 10.1016/j.conengprac.2014.10.006.
Tingting Fang and Risto Lahdelma. State estimation of district heating network based on customer measurements. Applied Thermal Engineering, 73(1):1211–1221, 2014. ISSN 13594311. doi: 10.1016/j.applthermaleng.2014.09.003.
Aric A. Hagberg, Daniel A. Schult, and Pieter J. Swart. Exploring network structure, dynamics, and function using NetworkX. In Proceedings of the 7th Python in Science Conference (SciPy2008), pages 11–15, Pasadena, CA USA, August 2008.
Matthias Hellerer, Tobias Bellmann, and Florian Schlegel. The DLR Visualization Library - recent development and applications. In the 10th International Modelica Conference, March 10-12, 2014, Lund, Sweden, Linköping Electronic Conference Proceedings, pages 899–911. Linköping University Electronic Press, 2014. doi: 10.3384/ECP14096899.
Christoph Höger, Alexandra Mehlhase, Christoph Nytsch-Geussen, Karsten Isakovic, and Rick Kubiak. Modelica3D
- platform independent simulation visualization. In Modelica Association, editor, Proceedings of the 9th International Modelica Conference, pages 485–494, 2012. doi: 10.3384/ecp12076485.
John D. Hunter. Matplotlib: A 2D graphics environment. Computing In Science & Engineering, 9(3):90–95, May-Jun 2007.
James Keirstead, Mark Jennings, and Aruna Sivakumar. A review of urban energy system models: Approaches, challenges and opportunities. Renewable
and Sustainable Energy Reviews, 16(6):3847–3866, 2012. doi: 10.1016/j.rser.2012.02.047.
Ralf Köcher. Beitrag zur Berechnung und Auslegung von Fernwärmenetzen. PhD thesis, Technische Universität Berlin, Berlin, 2000. URL http://d-nb.info/960177469/34.
LBL-SRG. BuildingsPy python package, 2015. URL https://github.com/lbl-srg/BuildingsPy.
Jaromir Sivic. Images to video v4.0, 2015. URL http://en.cze.cz/Images-to-video.
