Predictive warning system prototype for the prevention of failures in electrical grids

Recent events around the world such as the nationwide blackout of Chile in February 2025, that affected 90% of the population for over 12 hours or the Iberian blackout in April 2025 where Spain and Portugal experienced a total loss of the electrical service for almost 24 hours can disrupt essential services, cause significant financial losses, threaten public safety, and erode confidence in the resilience of national infrastructure. At the same time, electric power systems are undergoing a profound transformation. The rapid integration of renewable and distributed energy resources, coupled with the growing electrification of transportation and heating, is making grid operation increasingly complex and dynamic. Therefore, research that focuses on the prevention of catastrophic events and the maintenance of grid stability is both timely and essential.

This project is conducted in the collaboration between Prof. Arrieta Paternina (National Autonomous University of Mexico UNAM) and Prof. Korba in the framework of an IEEE working group. Data-driven and machine-learning algorithms for a preventive monitoring system for electrical power grids will be developed and tested in real time.