A review of machine learning approaches to power system security and stability

OA Alimi, K Ouahada, AM Abu-Mahfouz - IEEE Access, 2020 - ieeexplore.ieee.org
Increasing use of renewable energy sources, liberalized energy markets and most
importantly, the integrations of various monitoring, measuring and communication …

A systematic review of real-time detection and classification of power quality disturbances

JE Caicedo, D Agudelo-Martínez… - … and Control of …, 2023 - ieeexplore.ieee.org
This paper offers a systematic literature review of real-time detection and classification of
Power Quality Disturbances (PQDs). A particular focus is given to voltage sags and notches …

A novel deep learning method for the classification of power quality disturbances using deep convolutional neural network

S Wang, H Chen - Applied energy, 2019 - Elsevier
With the integration of multiple energy systems, there are more and more deterioration risks
of power quality in different energy production, transformation, delivery and consumption …

A new optimal feature selection algorithm for classification of power quality disturbances using discrete wavelet transform and probabilistic neural network

S Khokhar, AAM Zin, AP Memon, AS Mokhtar - Measurement, 2017 - Elsevier
Abstract Automatic classification of Power Quality Disturbances (PQDs) is a challenging
concern for both the utility and industry. In this paper, a novel technique of automatic …

Research challenges in real-time classification of power quality disturbances applicable to microgrids: A systematic review

R Igual, C Medrano - Renewable and Sustainable Energy Reviews, 2020 - Elsevier
Microgrids with distributed renewable energy sources are especially sensitive to power
quality disturbances. To mitigate the effects of distortions, they must first be detected and …

Recognition of power quality disturbances using S-transform based ruled decision tree and fuzzy C-means clustering classifiers

OP Mahela, AG Shaik - Applied Soft Computing, 2017 - Elsevier
A method based on Stockwell's transform and Fuzzy C-means (FCM) clustering initialized by
decision tree has been proposed in this paper for detection and classification of power …

An efficient algorithm for atomic decomposition of power quality disturbance signals using convolutional neural network

Y Han, Y Feng, P Yang, L Xu, AS Zalhaf - Electric Power Systems Research, 2022 - Elsevier
The atomic decomposition (AD) algorithm for Power Quality Disturbance (PQD) signals can
obtain sparser and physically clearer results than the conventional fixed basis …

Adversarial attacks and defense for CNN based power quality recognition in smart grid

J Tian, B Wang, J Li, Z Wang - IEEE Transactions on Network …, 2021 - ieeexplore.ieee.org
Vulnerability of various machine learning methods to adversarial examples has been
recently explored in the literature. Power systems which use these vulnerable methods face …

Power quality disturbance classification based on compressed sensing and deep convolution neural networks

J Wang, Z Xu, Y Che - IEEE access, 2019 - ieeexplore.ieee.org
By analyzing the recovery and reconstruction process of various power quality single
disturbances and composite disturbance signals, we proposed a set of acquisition methods …

Integral mathematical model of power quality disturbances

R Igual, C Medrano, FJ Arcega… - 2018 18th International …, 2018 - ieeexplore.ieee.org
Power quality (PQ) disturbances lead to severe problems in industries and electrical grids.
To mitigate PQ problems, the accurate detection and classification of the possible …