Modern control techniques for power distribution systems and microgrids rely on predictive frameworks exploiting the forecast of stochastic resources at time scales ranging from several minutes to seconds. This research subject focuses on the development of machine-learning-based techniques for the ultra short term forecasting of both renewable energy resources as well as heterogeneous loads with small level of aggregation.
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Intraday solar irradiance forecasting using public cameras