High-Precision Identification of Power Quality Disturbances Based on Discrete Orthogonal S-Transforms and Compressed Neural Network Methods

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 discrete orthogonal S-transform (DOST) in the feature extraction stage, compressive sensing (CS) in the feature reduction stage, a...

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Bibliographic Details
Main Authors: Muhammad Abubakar, Arfan Ali Nagra, Muhammad Faheem, Muhammad Mudassar, Muhammad Sohail
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Multiple power quality disturbances identification
compressed sensing
discrete orthogonal S-transform
deep neural network
wind-grid distribution
Online Access:https://ieeexplore.ieee.org/document/10214567/

Internet

https://ieeexplore.ieee.org/document/10214567/

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