11.30am – 12.30pm (CET)
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.
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