Abstract

In contrast to deterministic forecasts, probabilistic forecasts give additional information about the inherent uncertainty embodied in weather predictions. In the realm of solar forecasting, prediction intervals are especially important to assess risks in grid operations and to optimize the energy storages needed to ensure the supply–demand balance. Even if the development of probabilistic solar forecasts is relatively recent, the main available methods come from other fields of meteorology, particularly from the wind domain. This chapter reviews some of the methods used to generate probabilistic solar forecasts. A special emphasis is put on short term (from several hours to several days) and very short term (from several minutes to several hours) forecasts. As the verification of the quality of the probabilistic forecasts is of major interest, graphical tools like reliability diagram and rank histogram are depicted. These diagnostic tools are relevant for assessing the good calibration of the probabilistic forecasts. In addition, a quantitative score, the CRPS, is also proposed. The CRPS takes into account the different sources of uncertainties and as a proper score, the CRPS is useful to rank competing forecasting methods.

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