[HTML][HTML] Systematic review of energy theft practices and autonomous detection through artificial intelligence methods
Energy theft poses a significant challenge for all parties involved in energy distribution, and
its detection is crucial for maintaining stable and financially sustainable energy grids. One …
its detection is crucial for maintaining stable and financially sustainable energy grids. One …
Resilience enhancement of active distribution networks under extreme disaster scenarios: A comprehensive overview of fault location strategies
Fault diagnosis and location play a pivotal role in expediting fault restoration and enhancing
power system resilience. However, integrating distributed generation and diverse load …
power system resilience. However, integrating distributed generation and diverse load …
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 …
Interpretable visual transmission lines inspections using pseudo-prototypical part network
To guarantee the reliability of the electric energy supply, it is necessary that the transmission
lines are operating without interruptions. To improve the identification of faults in the …
lines are operating without interruptions. To improve the identification of faults in the …
High impedance single-phase faults diagnosis in transmission lines via deep reinforcement learning of transfer functions
Accurate and fast fault detection in transmission lines is of high importance to maintain the
reliability of power systems. Most of the existing methods suffer from false detection of high …
reliability of power systems. Most of the existing methods suffer from false detection of high …
End to end machine learning for fault detection and classification in power transmission lines
F Rafique, L Fu, R Mai - Electric Power Systems Research, 2021 - Elsevier
This paper proposes a new machine learning approach for fault detection and classification
tasks in electrical power transmission networks. This method exploits the temporal sequence …
tasks in electrical power transmission networks. This method exploits the temporal sequence …
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 synchronized lissajous-based method to detect and classify events in synchro-waveform measurements in power distribution networks
Waveform measurement units (WMUs) are a new class of smart grid sensors. They capture
synchro-waveforms, ie, time-synchronized high-resolution voltage waveform and current …
synchro-waveforms, ie, time-synchronized high-resolution voltage waveform and current …
A resilient protection scheme for common shunt fault and high impedance fault in distribution lines using wavelet transform
Distribution networks are most prone to high impedance faults (HIFs). These types of faults
occur whenever an energized conductor makes a contact with some surfaces that are poor …
occur whenever an energized conductor makes a contact with some surfaces that are poor …
Resilient operation of electric power distribution grids under progressive wildfires
Wildfires have been growingly recognized as a prominent threat in regions with high
temperatures during the summer. Power distribution systems, especially those passing …
temperatures during the summer. Power distribution systems, especially those passing …