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 ... Read more

In this paper, a real-time state estimation platform for distribution grids monitored by Phasor Measurement Units (PMUs) is developed, tested, and validated using Real Time Digital Simulator (RTDS). The developed platform serves as a proof-of-concept for potential implementation in an existing 50 kV ring network of the Dutch distribution utility Stedin medium voltage distribution grid located in the southwest (Zeeland area) of the Netherlands. To catch up with the fast sampling rates of PMUs, the platform incorporates computationally efficient techniques for state estimation and detection, discrimination and identification of anomalies like bad data and sudden load changes. Forecasting Aided State Estimation has been utilized to enable measurement innovations needed for fast anomaly detection, discrimination, and identification, whilst the Extended Kalman Filter (EKF) algorithm is selected to provide fast state forecasting and filtering. The platform has been tested under various normal and abnormal operating conditions considering different statistical properties of measurement noise as well as different bad data and sudden load change scenarios. To demonstrate advantages and disadvantages for embedding EKF into the platform, EKF is compared with Unscented Kalman Filter (UKF) in terms of estimation accuracy, computational efficiency, and compatibility with the module for anomaly detection, discrimination, and identification. The results of extensive simulations provide good hints about the feasibility of PMU-based real-time state estimation for the Stedin distribution grid. ... Read more