Event-Type Identification in Power Grids Using a Spectral Correlation Function-Aided Convolutional Neural Network

Event-Type Identification in Power Grids Using a Spectral Correlation Function-Aided Convolutional Neural Network

Rapid and accurate identification of events in power grids is critical to ensuring system reliability and security. This study introduces a novel event-type identification method, utilizing a Spectral Correlation Function (SCF)-aided Convolutional Neural Network (CNN). The proposed method employs a...

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Bibliographic Details
Main Authors: Ozgur Alaca, Ali Riza Ekti, Jhi-Young Joo, Nils Stenvig
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Access Journal of Power and Energy
Subjects:
Data augmentation
event and fault classification
grid event signature library (GESL)
low amplitude arcing
machine learning
spectral correlation function (SCF)
Online Access:https://ieeexplore.ieee.org/document/10789217/
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https://ieeexplore.ieee.org/document/10789217/

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