An Automated and Interpretable Machine Learning Scheme for Power System Transient Stability Assessment

An Automated and Interpretable Machine Learning Scheme for Power System Transient Stability Assessment

Many repeated manual feature adjustments and much heuristic parameter tuning are required during the debugging of machine learning (ML)-based transient stability assessment (TSA) of power systems. Furthermore, the results produced by ML-based TSA are often not explainable. This paper handles both th...

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Bibliographic Details
Main Authors: Fang Liu, Xiaodi Wang, Ting Li, Mingzeng Huang, Tao Hu, Yunfeng Wen, Yunche Su
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Energies
Subjects:
transient stability
automated machine learning
interpretability
Bayesian optimization
SHAP
CatBoost
Online Access:https://www.mdpi.com/1996-1073/16/4/1956

Internet

https://www.mdpi.com/1996-1073/16/4/1956

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