Anomaly Detection in Power Grids via Context-Agnostic Learning

arXiv:2404.07898v1 Announce Type: new
Abstract: An important tool grid operators use to safeguard against failures, whether naturally occurring or malicious, involves detecting anomalies in the power system SCADA data. In this paper, we aim to solve a real-time anomaly detection problem. Given time-series measurement values coming from a fixed set of sensors on the grid, can we identify anomalies in the network topology or measurement data? Existing methods, primarily optimization-based, mostly use only a single snapshot of the measurement values …

abstract aim anomaly anomaly detection arxiv context cs.lg data detection grid measurement operators paper power real-time sensors series set solve stat.ap tool type values via