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Power System Security Analysis using Reinforcement Learning

Power systems are ultimately operated by human grid operators who make decisions largely based on decades of intuition. With 90% integration of renewables and unprecedented changes energy demand patterns this intuition is broken. A reinforcement learning tool able to learn this operators intuition, able to learn from experience and able to generate data in real time may be the perfect setting for developing a solution for the arising challenges concerning power system security.


José María Sunyer Nestares

Ofertado en

  • Grado en Ingeniería en Tecnologías Industriales (electricidad) - (GITI-E)