A Survey of Open-Source Power System Dynamic Simulators with Grid-Forming Inverter for Machine Learning Applications

Fuente: arXiv
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Bibliographic Details
Main Authors: Su, Tong, Peng, Jiangkai, Selim, Alaa, Zhao, Junbo, Tan, Jin
Format: Preprint
Published: 2024
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author Su, Tong
Peng, Jiangkai
Selim, Alaa
Zhao, Junbo
Tan, Jin
author_facet Su, Tong
Peng, Jiangkai
Selim, Alaa
Zhao, Junbo
Tan, Jin
contents The emergence of grid-forming (GFM) inverter technology and the increasing role of machine learning in power systems highlight the need for evaluating the latest dynamic simulators. Open-source simulators offer distinct advantages in this field, being both free and highly customizable, which makes them well-suited for scientific research and validation of the latest models and methods. This paper provides a comprehensive survey and comparison of the latest open-source simulators that support GFM, with a focus on their capabilities and performance in machine-learning applications.
format Preprint
id arxiv_https___arxiv_org_abs_2412_08065
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Survey of Open-Source Power System Dynamic Simulators with Grid-Forming Inverter for Machine Learning Applications
Su, Tong
Peng, Jiangkai
Selim, Alaa
Zhao, Junbo
Tan, Jin
Systems and Control
The emergence of grid-forming (GFM) inverter technology and the increasing role of machine learning in power systems highlight the need for evaluating the latest dynamic simulators. Open-source simulators offer distinct advantages in this field, being both free and highly customizable, which makes them well-suited for scientific research and validation of the latest models and methods. This paper provides a comprehensive survey and comparison of the latest open-source simulators that support GFM, with a focus on their capabilities and performance in machine-learning applications.
title A Survey of Open-Source Power System Dynamic Simulators with Grid-Forming Inverter for Machine Learning Applications
topic Systems and Control
url https://arxiv.org/abs/2412.08065