@inproceedings{c862e676da6742838bf0b60f106f050d,
title = "A Dymola-Python framework for data-driven model creation and co-simulation",
abstract = "The introduction of cyber-physical systems has been a recent development in energy systems. Cyber-physical systems contain digital components for applications such as monitoring or control. In many cases, modeling multiple aspects of such cyber-physical systems poses a challenge to conventional simulation tools. In addition, recent modeling approaches, such as data-driven modeling, are being applied. The combination of such data-driven models, which may consist of a different architecture than traditional models, with traditional models can be implemented through co-simulation methods. In co-simulation, components created from different simulation tools can be combined and coupled through standardized interfaces. This work presents a framework for data-driven model generation and co-simulation. The framework is implemented in Python and Dymola and is based on the Functional Mock-up Interface (FMI) standard. The framework implements the creation of data-driven models in Python, the generation of Functional Mock-up Units (FMUs) through the frameworks uniFMU and pythonFMU, as well the creation of a testbench model in Dymola and the cosimulation of this model. The framework is demonstrated on the application of a solar collector from a single family house heating system.",
keywords = "Cyber-Physical Systems, Modelling & Simulation, Data-driven Modelling, Co-Simulation",
author = "Sandra Wilfling and Basak Falay and Qamar Alfalouji and Gerald Schweiger",
year = "2022",
doi = "10.3384/ecp193165",
language = "English",
series = "Link{\"o}ping Electronic Conference Proceedings ",
number = "193",
pages = "165--170",
booktitle = "Proceedings of Asian Modelica Conference 2022, Tokyo, Japan, November 24-25, 2022",
note = "Asian Modelica Conference 2022 ; Conference date: 24-12-2021 Through 25-12-2021",
}