A VAE-GAN generative model combined with sliding-window temporal features and dual decision fusion detects known power events and assigns unseen disturbances to a new class using PMU data.
Data- driven event detection of power systems based on unequal-interval reduction of PMU data and local outlier factor,
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Generative Modeling and Decision Fusion for Unknown Event Detection and Classification Using Synchrophasor Data
A VAE-GAN generative model combined with sliding-window temporal features and dual decision fusion detects known power events and assigns unseen disturbances to a new class using PMU data.