AC microgrid protection schemes: A comprehensive review
The power grid infrastructure has evolved from a centralized to a distributed model utilizing
renewable energy sources in the last few years. This trend is likely to continue, given the …
renewable energy sources in the last few years. This trend is likely to continue, given the …
A review of fault diagnosis, prognosis and health management for aircraft electromechanical actuators
Z Yin, N Hu, J Chen, Y Yang… - IET Electric Power …, 2022 - Wiley Online Library
Abstract As More/All Electric Aircraft gradually become a research hotspot,
electromechanical actuators (EMAs), which can directly convert electrical energy into …
electromechanical actuators (EMAs), which can directly convert electrical energy into …
LSTM recurrent neural network classifier for high impedance fault detection in solar PV integrated power system
This paper presents the detection of High Impedance Fault (HIF) in solar Photovoltaic (PV)
integrated power system using recurrent neural network-based Long Short-Term Memory …
integrated power system using recurrent neural network-based Long Short-Term Memory …
A KNN based random subspace ensemble classifier for detection and discrimination of high impedance fault in PV integrated power network
This paper proposes an ensemble Random Subspace (RS) classifier for discrimination of
High Impedance Fault (HIF) in photovoltaic connected power network. The design and …
High Impedance Fault (HIF) in photovoltaic connected power network. The design and …
Fast dynamic phasor estimation algorithm considering DC offset for PMU applications
X Ma, Z Liao, Y Wang, J Zhao - IEEE Transactions on Power …, 2023 - ieeexplore.ieee.org
Because of the volatility and intermittence of the renewable energy units in the novel power
system, the electrical variables usually exhibit dynamic characteristics. Under fault …
system, the electrical variables usually exhibit dynamic characteristics. Under fault …
Feature and subfeature selection for classification using correlation coefficient and fuzzy model
This article presents an analysis of data extraction for classification using correlation
coefficient and fuzzy model. Several traditional methods of data extraction are used for …
coefficient and fuzzy model. Several traditional methods of data extraction are used for …
On the use of artificial intelligence for high impedance fault detection and electrical safety
Accidents caused by faults on overhead power lines have been more frequently reported
under extreme weather conditions and may strongly threaten the safety and stability of the …
under extreme weather conditions and may strongly threaten the safety and stability of the …
Deep learning for high-impedance fault detection: Convolutional autoencoders
High-impedance faults (HIF) are difficult to detect because of their low current amplitude and
highly diverse characteristics. In recent years, machine learning (ML) has been gaining …
highly diverse characteristics. In recent years, machine learning (ML) has been gaining …
A bi-level machine learning method for fault diagnosis of oil-immersed transformers with feature explainability
Power transformer faults are considered rare events, so data samples in normal operations
are much more readily available than in faulty conditions. Traditionally, power transformer …
are much more readily available than in faulty conditions. Traditionally, power transformer …
High-impedance fault diagnosis: a review
A Aljohani, I Habiballah - Energies, 2020 - mdpi.com
High-impedance faults (HIFs) represent one of the biggest challenges in power distribution
networks. An HIF occurs when an electrical conductor unintentionally comes into contact …
networks. An HIF occurs when an electrical conductor unintentionally comes into contact …