A Data-Driven Convolutional Neural Network Approach for Power Quality Disturbance Signal Classification (DeepPQDS-FKTNet)

A Data-Driven Convolutional Neural Network Approach for Power Quality Disturbance Signal Classification (DeepPQDS-FKTNet)

Power quality disturbance (PQD) signal classification is crucial for the real-time monitoring of modern power grids, assuring safe and reliable operation and user safety. Traditional power quality disturbance signal classification approaches are sensitive to noise, feature selection, etc. This study...

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Bibliographic Details
Main Authors: Fahman Saeed, Sultan Aldera, Mohammad Alkhatib, Abdullrahman A. Al-Shamma’a, Hassan M. Hussein Farh
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Mathematics
Subjects:
power quality disturbances (PQDs)
energy
AutoML
DeepPQDS-FKTNet
deep learning
classification
Online Access:https://www.mdpi.com/2227-7390/11/23/4726

Internet

https://www.mdpi.com/2227-7390/11/23/4726

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