Physics-Informed Machine Learning for Complex Systems - A Focus on Power System Applications

Explore the intersection of physics-informed machine learning and power systems in this 52-minute webinar from GERAD Research Center. Delve into the challenges posed by increasing renewable energy penetration and the resulting vulnerability to disturbances in power systems. Discover how machine learning techniques can be applied to assess vulnerabilities and enhance resilience in these complex systems. Learn about effective reduced models for large electric transmission grids, presented as PDE equations over covered areas. Understand the process of calibrating these models using recorded operational data. Gain insights into the importance of efficient tools for power system analysis in the context of evolving energy landscapes.