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We demonstrate progress on the deployment of two sets of technologies tosupport distribution grid operators integrating high shares of renewable energysources, based on a market for trading local energy flexibilities. Anartificial-intelligence (AI) grid modelling tool, based on probabilisticgraphs, predicts congestions and estimates the amount and location of energyflexibility required to avoid such events. A scalable time-series forecastingsystem delivers large numbers of short-term predictions of distributed energydemand and generation. We discuss the deployment of the technologies at threetrial demonstration sites across Europe, in the context of a research projectcarried out in a consortium with energy utilities, technology providers andresearch institutions.

AI Modelling and Time-series Forecasting Systems for Trading Energy Flexibility in Distribution Grids