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arXiv · 1909.10870

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

Bradley Eck·Francesco Fusco·Robert Gormally·Mark Purcell·Seshu Tirupathi
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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 time-series 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.

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Bradley Eck, Francesco Fusco, Robert Gormally, Mark Purcell, Seshu Tirupathi. 2019-09-18. AI Modelling and Time-series Forecasting Systems for Trading Energy Flexibility in Distribution Grids. https://doi.org/10.1145/3307772.3330158

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