Application of big data and machine learning in smart grid, and associated security concerns: A review
This paper conducts a comprehensive study on the application of big data and machine
learning in the electrical power grid introduced through the emergence of the next …
learning in the electrical power grid introduced through the emergence of the next …
Power quality disturbance detection and classification using signal processing and soft computing techniques: A comprehensive review
M Mishra - International transactions on electrical energy …, 2019 - Wiley Online Library
Power quality (PQ) studies have gained huge attention from the academics and the industry
over the past three decades. The main objective of this article is to provide a comprehensive …
over the past three decades. The main objective of this article is to provide a comprehensive …
Power system monitoring for electrical disturbances in wide network using machine learning
Due to infrastructure developments, wide disturbances have occurred in the power system.
There is a need for intelligent monitoring systems across wide power networks for the …
There is a need for intelligent monitoring systems across wide power networks for the …
Power quality disturbance monitoring and classification based on improved PCA and convolution neural network for wind-grid distribution systems
The excessive use of power semiconductor devices in a grid utility increases the malfunction
of the control system, produces power quality disturbances (PQDs) and reduces the …
of the control system, produces power quality disturbances (PQDs) and reduces the …
Detection and classification of power quality disturbances using GWO ELM
Many industies have equipments sensitive to bad power quality that affects their production
and product quality. Therefore, it is important to automatically monitor the quality of power …
and product quality. Therefore, it is important to automatically monitor the quality of power …
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 …
High-precision identification of power quality disturbances based on discrete orthogonal S-transforms and compressed neural network methods
Power quality disturbances (PQDs) occur as the use of non-linear load and renewable-
based micro-grids increases. This paper presents a new algorithm that consists of the …
based micro-grids increases. This paper presents a new algorithm that consists of the …
Overview of signal processing and machine learning for smart grid condition monitoring
Nowadays, the main grid is facing several challenges related to the integration of renewable
energy resources, deployment of grid-level energy storage devices, deployment of new …
energy resources, deployment of grid-level energy storage devices, deployment of new …
Transformation of smart grid using machine learning
With the advent of distributed and renewable energy sources, maintaining the stability of
power grid is becoming increasingly difficult. Traditional power grid can be transformed into …
power grid is becoming increasingly difficult. Traditional power grid can be transformed into …
Signal-piloted processing and machine learning based efficient power quality disturbances recognition
S Mian Qaisar - PloS one, 2021 - journals.plos.org
Significant losses can occur for various smart grid stake holders due to the Power Quality
Disturbances (PQDs). Therefore, it is necessary to correctly recognize and timely mitigate …
Disturbances (PQDs). Therefore, it is necessary to correctly recognize and timely mitigate …