Deep Statistical Solvers and Power Systems Applications

Explore a 44-minute seminar from GERAD Research Center on deep statistical solvers and their applications in power systems. Delve into the challenges faced by power systems due to the integration of intermittent renewable energies and disruptive market mechanisms. Learn how RTE, the French Transmission System Operator, is leveraging Deep Learning methods to address increasing complexity. Discover the potential of Graph Neural Networks (GNNs) in handling topological changes in power grids and their ability to imitate power grid simulators. Examine an innovative approach that trains GNNs to optimize power systems through direct minimization of physical laws rather than imitation. Gain insights into cutting-edge research that combines deep learning techniques with power system optimization to tackle the evolving challenges in the energy sector.