Sample-by-sample Power Quality Disturbance classification based on Sliding Window Recursive Discrete Fourier Transform
Author:
Funder
Fundação de Amparo à Pesquisa do Estado de Minas Gerais
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Universidade Federal de Lavras
Publisher
Elsevier BV
Reference36 articles.
1. The use of deep learning and 2-D wavelet scalograms for power quality disturbances classification;Salles;Electr. Power Syst. Res.,2023
2. A new robust kernel ridge regression classifier for islanding and power quality disturbances in a multi distributed generation based microgrid;Chakravorti;Renew. Energy Focus,2019
3. Detection and classification of multiple power quality disturbances in microgrid network using probabilistic based intelligent classifier;Suganthi;Sustain. Energy Technol. Assess.,2021
4. Real-time system for automatic detection and classification of single and multiple power quality disturbances;Ribeiro;Measurement,2018
5. A novel deep learning method for the classification of power quality disturbances using deep convolutional neural network;Wang;Appl. Energy,2019
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