Fault Detection and Classification in Ring Power System With DG Penetration Using Hybrid CNN-LSTM
A modern electric power system integrated with advanced technologies such as sensors and smart meters is referred to as a “smart grids”, aimed at enhancing electrical power delivery efficiency and reliability. However, fault location and prediction can become challenging when d...
Main Authors: | Ahmed Sami Alhanaf, Murtaza Farsadi, Hasan Huseyin Balik |
---|---|
格式: | 文件 |
语言: | English |
出版: |
IEEE
2024-01-01
|
丛编: | IEEE Access |
主题: | |
在线阅读: | https://ieeexplore.ieee.org/document/10508728/ |
相似书籍
-
Intelligent Fault Detection and Classification Schemes for Smart Grids Based on Deep Neural Networks
由: Ahmed Sami Alhanaf, et al.
出版: (2023-11-01) -
Bearing fault diagnosis with parallel CNN and LSTM
由: Guanghua Fu, et al.
出版: (2024-01-01) -
Research on Wind Turbine Fault Detection Based on CNN-LSTM
由: Lin Qi, et al.
出版: (2024-09-01) -
Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods
由: Yaseen Ahmed Mohammed Alsumaidaee, et al.
出版: (2023-03-01) -
Research on fault diagnosis of solar photovoltaic module based on CNN-LSTM
由: Cheng Qize, et al.
出版: (2020-04-01)