Practical implementation and Operational Experience of Machine Learning Surrogate Model for Real-Time Dynamic Stability Assessment of the Italian Power System

The energy transition is rapidly transforming numerous aspects of the real-time operation of power transmission systems. Ensuring network stability within this evolving scenario requires considerable effort, particularly in accurately predicting potentially critical situations and guaranteeing the effectiveness of preventive and corrective control actions. Currently, dynamic stability assessment relies on massive dynamic simulations, which are computationally highly demanding.