As the energy sector transitions toward increased renewable integration and bidirectional grid operation, the complexity and frequency of disturbance events rise, necessitating advanced situational awareness. Robust expert systems are needed that leverage a multilayered wide area monitoring, protection, and control (WAMPAC) architecture, integrating device-level detection, data aggregation, and an adaptive event classification and validation framework facilitated by dynamic incremental learning (DIL). These expert systems address challenges such as concept drift, catastrophic forgetting, and the need for human-in-the-loop oversight, enabling rapid and accurate identification of both known and novel disturbance events that can be expected in the future.
