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.
Figure 7 illustrates the distribution of individual PMU data segments in the 2D feature space defined by the reconstruction error and discriminator error
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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.