Predictive Anomaly Detection and Self-Healing in Active Distribution Networks Using a Graph Neural Network Digital Twin
Active distribution networks (ADNs) are exposed to two anomaly classes that resist unified detection: physical line outages and cyber false-data-injection (FDI) attacks. The standard defense, weighted- least-squares (WLS) bad-data detection, catches FDI but is structurally blind to topology changes, because a reconfigu...