Performance Evaluation of Discrete Wavelet Transform and Machine Learning Based Techniques for Classifying Power Quality Disturbances-Reference-Cited by-同舟云学术

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Performance Evaluation of Discrete Wavelet Transform and Machine Learning Based Techniques for Classifying Power Quality Disturbances

Published:2024 Issue: Volume:12 Page:95472-95486
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Sipai Uvesh¹^ORCID,Jadeja Rajendrasinh¹^ORCID,Kothari Nishant¹^ORCID,Trivedi Tapankumar¹^ORCID,Mahadeva Rajesh²^ORCID,Patole Shashikant P.³^ORCID

Affiliation:

1. Department of Electrical Engineering, Marwadi University, Rajkot, Gujarat, India

2. Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India

3. Department of Physics, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10591747.pdf?arnumber=10591747

Reference47 articles.

1. Electrical power systems quality;Dugan,2002

2. Signal Processing of Power Quality Disturbances

3. Power Quality in Microgrids Including Supraharmonics: Issues, Standards, and Mitigations

4. Wavelet transform‐based feature extraction for detection and classification of disturbances in an islanded micro‐grid

5. Characterization of power quality disturbances using hybrid technique of linear Kalman filter and fuzzy-expert system

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