Ai in energy forecasting: how to avoid the black-box effect?

11 December 2020




Energy Webinar

11 December

11.30am – 12.30pm (CET)

Through this presentation, Adrien Rosen and Pierre Artoisenet will present how N-SIDE is able to combine the best of business know-how and the right algorithmic choices to help avoid the symptomatic AI “black-box effect”.

AI in Energy forecasting: how to avoid the black-box effect?

Anticipating the future is a key concern for all actors of the energy sector. More specifically, as energy became a data-driven sector, forecasting of time-series has taken a significant importance for a wide range of actors:

  • for a system operator to minimise the operational costs of running the grid

  • for an asset owner to support them in the management of their technical constraints

  • for a portfolio manager to mitigate financial risks

  • for a trader to capture opportunities on speculative markets

With the rising use of Machine Learning and Artificial Intelligence approaches, another trend is emerging: the need for explainability and transparency.

Presented by Adrien Rosen and Pierre Artoisenet.

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