Enhancing PowerFactory Dynamic Models with Python for Rapid Prototyping

Enhancing PowerFactory Dynamic Models with Python for Rapid Prototyping

López, Claudio (TU Delft Intelligent Electrical Power Grids)
Cvetkovic, M. (TU Delft Intelligent Electrical Power Grids)
Palensky, P. (TU Delft Intelligent Electrical Power Grids)

2019

DIgSILENT PowerFactory is among the most widely adopted power system analysis tools in research and industry. It provides a comprehensive library of device models and it allows users to define their own. Models for dynamic simulation can be defined in the DIgSILENT Simulation Language (DSL). When the functionality of DSL is insufficient, new DSL functions can be defined in C or C++. However, C and C++ can be challenging for inexperienced programmers. Furthermore, every time the C or C++ code is modified, it needs to be recompiled and PowerFactory needs to be restarted for the changes to take effect, which slows down the workflow, model development, and inhibits rapid prototyping. In this paper we present an open source library that allows users to call Python functions and methods from DSL with minimal effort. Python is a powerful and much easier to use language than C or C++. Additionally, Python programs do not need to be compiled. Furthermore, with this library PowerFactory does not need to be restarted every time the Python code is changed. To illustrate what can be accomplished with our library we present three example use cases related to load modeling, co-simulation, and fault detection based on machine learning. The examples show that it becomes straightforward to enhance DSL with Python and that sophisticated models can be produced with reduced effort using popular open source Python libraries. As a consequence, PowerFactory users gain access to enhanced modeling capabilities and user-friendliness, and a more speedy workflow, which is beneficial for rapid prototyping.

Co-simulation
DSL
dynamic simulation
machine-learning
PowerFactory
Python

http://resolver.tudelft.nl/uuid:b1fe01e0-add6-46db-ad05-7076d04cf279

https://doi.org/10.1109/ISIE.2019.8781432

IEEE, Piscataway, NJ

2021-12-08

978-1-7281-3667-7

2019 IEEE 28th International Symposium on Industrial Electronics (ISIE): Proceedings

28th IEEE International Symposium on Industrial Electronics, ISIE 2019, 2019-06-12 → 2019-06-14, Vancouver, Canada

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

conference paper

© 2019 Claudio López, M. Cvetkovic, P. Palensky