Latent Space Modeling for Event Detection in Power Grid Data

This project explores how latent representations learned from raw grid waveforms can reveal underlying structure and enable early detection of abnormal events. By modeling high-frequency voltage and current signals, we aim to distinguish critical disturbances from normal behavior with minimal delay.