Sergio A. Dorado-Rojas
Department of Electrical, Systems and Computer Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
Manuel Navarro Catalán
Department of Electrical, Systems and Computer Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
Marcelo de Castro Fernandes
Department of Electrical, Systems and Computer Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
Luigi Vanfretti
Department of Electrical, Systems and Computer Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
Ladda ner artikelhttps://doi.org/10.3384/ecp2016928Ingår i: Proceedings of the American Modelica Conference 2020, Boulder, Colorado, USA, March 23-25, 2020
Linköping Electronic Conference Proceedings 169:3, s. 28-34
Publicerad: 2020-11-03
ISBN: 978-91-7929-900-2
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
In this paper, a benchmark between solvers and Modelica
tools for time-domain simulations of a power system
model is presented. A Python-based approach is employed
to automate Modelica simulations and compute
performance metrics. This routine is employed to compare
the performance of a commercial (Dymola) against
an open-source (OpenModelica) simulation tool with different
solver settings. Python scripts are developed to execute
a dynamic simulation of a common model for power
system studies with 49 states and 420 variables in three
different scenarios. This degree of automation makes it
easier to change solver settings and tools during execution.
The performance of each of the tools is assessed through
metrics such as execution time and CPU utilization. The
quantitative comparison results provide a clear reference
to the performance of the tools and solvers for the execution
of time-domain simulations with a significant degree
of complexity. The commercial tool offers better performance
for variable-step solver, but the performance of the
open-source software shows significantly faster results for
fixed-step solvers.
Modelica, Python-Dymola Interface, Python-OpenModelica Interface, CPU performance.
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