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Artificial Intelligence in energy forecasting

As renewable generation grows and markets become more volatile, accurate forecasting is becoming increasingly important for all commercially successful energy companies.

AI forecasting tools are now competing with traditional ‘fundamentals’ methods to forecast variables including demand, renewable generation output and short-term market prices.

Good data and a solid knowledge of the underlying fundamentals is of course required for successful AI forecasting. Yet it is also necessary to have a deep understanding of how to maximise the machine learning techniques’ potential, as well as knowing the new tools’ constraints and limitations.

AFRY has developed a drag-and-drop interface to harness the power of the latest deep learning techniques. In this webinar, Stephen Woodhouse and Dr. Jan Wierzba introduce the tool and demonstrate some live case studies.

The slide pack and recording are available below.

Slide pack Pdf, 1.1 MB.

If you have any questions, please get in touch with Stephen Woodhouse and Jan Wierzba.

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