Renewable Energy: Forecasting and Risk Management by Philippe Drobinski & Mathilde Mougeot & Dominique Picard & Riwal Plougonven & Peter Tankov

Author:Philippe Drobinski & Mathilde Mougeot & Dominique Picard & Riwal Plougonven & Peter Tankov
Language: eng
Format: epub
ISBN: 9783319990521
Publisher: Springer International Publishing

Figure 6.3 exemplifies the variability found in daily load patterns. Despite such variabilities, common features can still be identified, such as lower demands during night time, higher ones during the day, a steady increase during the morning with a first peak in mid afternoon. The amplitude and position of these features are important landmarks of the load curve.

6.3 Methods

As mentioned in Sect. 6.1, the proposed framework combines the output of various models through an experts aggregation strategy.

We now describe the individual models which make up the experts to be aggregated. For clarity of presentation we separate them into exogenous models (using meteorological data) and endogenous models (relying only on past demand patterns). We then present and discuss the expert aggregation strategies applied to obtain the final prediction.

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