Machine learning applications in power system fault diagnosis: Research advancements and perspectives
Newer generation sources and loads are posing new challenges to the conventional power
system protection schemes. Adaptive and intelligent protection methodology, based on …
system protection schemes. Adaptive and intelligent protection methodology, based on …
Fault detection, classification and location for transmission lines and distribution systems: a review on the methods
A comprehensive review on the methods used for fault detection, classification and location
in transmission lines and distribution systems is presented in this study. Though the three …
in transmission lines and distribution systems is presented in this study. Though the three …
Deep learning through LSTM classification and regression for transmission line fault detection, diagnosis and location in large-scale multi-machine power systems
Fault detection, diagnosis, identification and location are crucial to improve the sensitivity
and reliability of system protection. This maintains power systems continuous proper …
and reliability of system protection. This maintains power systems continuous proper …
A critical review of detection and classification of power quality events
Requirement of green supply with higher quality has been consumers' demand around the
globe. The electrical power system is expected to deliver undistorted sinusoidal rated …
globe. The electrical power system is expected to deliver undistorted sinusoidal rated …
Detection and classification of transmission line faults based on unsupervised feature learning and convolutional sparse autoencoder
We present in this paper a novel method for fault detection and classification in power
transmission lines based on convolutional sparse autoencoder. Contrary to conventional …
transmission lines based on convolutional sparse autoencoder. Contrary to conventional …
Hybrid CNN-LSTM approaches for identification of type and locations of transmission line faults
A Moradzadeh, H Teimourzadeh… - International Journal of …, 2022 - Elsevier
Timely and accurate detection of transmission line faults is one of the most important issues
in the reliability of the power systems. In this paper, in order to assess the effects of …
in the reliability of the power systems. In this paper, in order to assess the effects of …
Fault detection and classification based on co-training of semisupervised machine learning
TS Abdelgayed, WG Morsi… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
This paper presents a semisupervised machine learning approach based on co-training of
two classifiers for fault classification in both the transmission and the distribution systems …
two classifiers for fault classification in both the transmission and the distribution systems …
Fault detection for photovoltaic systems based on multi-resolution signal decomposition and fuzzy inference systems
Z Yi, AH Etemadi - IEEE transactions on smart grid, 2016 - ieeexplore.ieee.org
This paper presents a detection scheme for DC side short-circuit faults of photovoltaic (PV)
arrays that consist of multiple PV panels connected in a series/parallel configuration. Such …
arrays that consist of multiple PV panels connected in a series/parallel configuration. Such …
Quantum computing based hybrid deep learning for fault diagnosis in electrical power systems
A Ajagekar, F You - Applied Energy, 2021 - Elsevier
Quantum computing (QC) and deep learning have shown promise of supporting
transformative advances and have recently gained popularity in a wide range of areas. This …
transformative advances and have recently gained popularity in a wide range of areas. This …
Mathematical morphology-based feature-extraction technique for detection and classification of faults on power transmission line
The permanency of highly-reliable power supply is a core trait of an electric power
transmission network. A transmission line is the main part of this network through which …
transmission network. A transmission line is the main part of this network through which …