[HTML][HTML] Power quality monitoring in electric grid integrating offshore wind energy: A review
The rising integration of offshore wind energy into the electric grid provides remarkable
opportunities in terms of environmental sustainability and cost efficiency. However, it poses …
opportunities in terms of environmental sustainability and cost efficiency. However, it poses …
A comprehensive review of deep-learning applications to power quality analysis
Power quality (PQ) monitoring and detection has emerged as an essential requirement due
to the proliferation of sensitive power electronic interfacing devices, electric vehicle charging …
to the proliferation of sensitive power electronic interfacing devices, electric vehicle charging …
[HTML][HTML] The use of deep learning and 2-D wavelet scalograms for power quality disturbances classification
RS Salles, PF Ribeiro - Electric Power Systems Research, 2023 - Elsevier
This work investigates the use of advanced signal processing and deep Learning for pattern
recognition and classification of signals with power quality disturbances. For this purpose …
recognition and classification of signals with power quality disturbances. For this purpose …
A synchronized lissajous-based method to detect and classify events in synchro-waveform measurements in power distribution networks
M Izadi, H Mohsenian-Rad - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
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 …
CNN/Bi‐LSTM‐based deep learning algorithm for classification of power quality disturbances by using spectrogram images
This paper, using an inverse signal approach, presents a novel deep learning algorithm
based on a convolutional neural network (CNN) and bidirectional long short‐term memory …
based on a convolutional neural network (CNN) and bidirectional long short‐term memory …
A new deep learning method for the classification of power quality disturbances in hybrid power system
With the advancement of technology, the demand for high quality and sustainable electrical
energy has been increased due to the widespread use of electrical devices in our daily lives …
energy has been increased due to the widespread use of electrical devices in our daily lives …
A hybrid approach based on principal component analysis for power quality event classification using support vector machines
A Saxena, AM Alshamrani, AF Alrasheedi… - Mathematics, 2022 - mdpi.com
Power quality has emerged as a sincere denominator in the planning and operation of a
power system. Various events affect the quality of power at the distribution end of the system …
power system. Various events affect the quality of power at the distribution end of the system …
An end-to-end deep learning method for voltage sag classification
Power quality disturbances (PQD) have a negative impact on power quality-sensitive
equipment, often resulting in great financial losses. To prevent these losses, besides …
equipment, often resulting in great financial losses. To prevent these losses, besides …
Classification of power quality disturbances in solar PV integrated power system based on a hybrid deep learning approach
Nowadays, due to the increase in the demand for electrical energy and the development of
technology, the electrical devices have a more complex structure. This situation has …
technology, the electrical devices have a more complex structure. This situation has …
Power quality disturbances classification based on Gramian angular summation field method and convolutional neural networks
This paper presents a novel hybrid approach combining Gramian Angular Summation Field
(GASF) method with a convolutional neural network (CNN) to classify power quality …
(GASF) method with a convolutional neural network (CNN) to classify power quality …