Data-driven Small-signal Modeling for Converter-based Power Systems
- URL: http://arxiv.org/abs/2108.13046v1
- Date: Mon, 30 Aug 2021 08:10:45 GMT
- Title: Data-driven Small-signal Modeling for Converter-based Power Systems
- Authors: Francesca Rossi, Eduardo Prieto-Araujo, Marc Cheah-Mane, Oriol
Gomis-Bellmunt
- Abstract summary: This article details a complete procedure to derive a data-driven small-signal-based model useful to perform converter-based power system related studies.
To compute the model, Decision Tree (DT) regression, both using single DT and ensemble DT, and Spline regression have been employed.
The possible applications of the model are discussed, highlighting the potential of the developed model in further power system small-signal related studies.
- Score: 7.501426386641255
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This article details a complete procedure to derive a data-driven
small-signal-based model useful to perform converter-based power system related
studies. To compute the model, Decision Tree (DT) regression, both using single
DT and ensemble DT, and Spline regression have been employed and their
performances have been compared, in terms of accuracy, training and computing
time. The methodology includes a comprehensive step-by-step procedure to
develop the model: data generation by conventional simulation and mathematical
models, databases (DBs) arrangement, regression training and testing, realizing
prediction for new instances. The methodology has been developed using an
essential network and then tested on a more complex system, to show the
validity and usefulness of the suggested approach. Both power systems test
cases have the essential characteristics of converter-based power systems,
simulating high penetration of converter interfaced generation and the presence
of HVDC links. Moreover, it is proposed how to represent in a visual manner the
results of the small-signal stability analysis for a wide range of system
operating conditions, exploiting DT regressions. Finally, the possible
applications of the model are discussed, highlighting the potential of the
developed model in further power system small-signal related studies.
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