Enhancing Power Grid Reliability With Machine Learning and Auxiliary Classifier Generative Adversarial Networks: A Study on Fault Detection Using the Georgia Electric System Load Dataset
Power networks are vital to society, yet service outages and faults can have devastating consequences. This study introduces a novel integration of machine learning and data augmentation techniques for fault detection and classification, addressing gaps in data diversity and imbalance. Unlike tradit...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10818412/ |
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