Improved Fault Classification and Localization in Power Transmission Networks using VAE-generated Synthetic Data and Machine Learning Algorithms

Muhammad Amir Khan; Bilal Asad; Toomas Vaimann; Ants Kallaste; Raimondas Pomarnacki; Van Khang Hyunh

doi:10.20944/preprints202309.1009.v1

A peer-reviewed article of this Preprint also exists.

Khan, M.A.; Asad, B.; Vaimann, T.; Kallaste, A.; Pomarnacki, R.; Hyunh, V.K. Improved Fault Classification and Localization in Power Transmission Networks Using VAE-Generated Synthetic Data and Machine Learning Algorithms. Machines 2023, 11, 963. Khan, M.A.; Asad, B.; Vaimann, T.; Kallaste, A.; Pomarnacki, R.; Hyunh, V.K. Improved Fault Classification and Localization in Power Transmission Networks Using VAE-Generated Synthetic Data and Machine Learning Algorithms. Machines 2023, 11, 963.

Abstract

Keywords: Electrical power systems, Support vector machines, Random Forest, Machine learning, Wavelet transform, Transmission lines fault, Electrical power quality, Short circuit, Classification of faults, Localization of faults, Decision trees, Ensemble learning, K-nearest neighbors.

Keywords

Electrical power systems; Support vector machines; random Forest; machine learning; wavelet transform; transmission lines fault; Electrical power quality; short circuit; Classification of faults; localization of faults; decision trees; Ensemble learning; K-nearest neighbors

Subject

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Improved Fault Classification and Localization in Power Transmission Networks using VAE-generated Synthetic Data and Machine Learning Algorithms

Abstract

Keywords

Subject

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