Publication
e-Energy 2019
Conference paper

AI modelling and time-series forecasting systems for trading energy flexibility in distribution grids

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Abstract

We demonstrate progress on the deployment of two sets of technologies to support distribution grid operators integrating high shares of renewable energy sources, based on a market for trading local energy flexibilities. An artificial-intelligence (AI) grid modelling tool, based on probabilistic graphs, predicts congestions and estimates the amount and location of energy flexibility required to avoid such events. A scalable timeseries forecasting system delivers large numbers of short-term predictions of distributed energy demand and generation. We discuss the deployment of the technologies at three trial demonstration sites across Europe, in the context of a research project carried out in a consortium with energy utilities, technology providers and research institutions.

Date

15 Jun 2019

Publication

e-Energy 2019

Authors

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