The electricity grid is undergoing fundamental transformation due to increasing penetration of variable energy resources (VER) at bulk power level, distributed energy resources (DER) at the grid edge, and intermittent large loads (such as Data Centers) in between. These changes require enhanced situational awareness and timely actionable information for grid operators for reliable and secure grid operation. Existing tools at the disposal of grid operators require enhancements to meet the challenge.
The recent Iberian-wide Blackout on April 28, 2025 is witness to this deficiency. The outage left 60 million people in Spain and Portugal without power in just 5 seconds following a generator trip at a Granada substation (2,200 MW lost) triggered cascading outages that affected transport (metros, trains, airports), traffic systems, mobile phones, internet infrastructure, ATMs, etc. The root cause of the problem can be traced to grid instability and oscillations resulting from lack of adequate system inertia due to proliferation of Inverter-Based Resources (IBRs), and inadequacy of situational awareness and rapid actionable information for timely action.
This course will address the new processes and tools to address this deficiency. In particular the course will cover how new data-driven network analysis tools and procedures empowered by Artificial Intelligence and Machine Learning (AI/ML) can be used to enhance situational awareness. Attendees will also gain insight into use case development, data driven AI model selection and evaluation, and deployment in an operations environment.
This session will take place on Tuesday, March 31, from 2:00 to 3:30 PM CST.
