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Probabilistic Solar Forecasts Evaluation Part 2: Quantile Forecasts

Abstract : Two types of probabilistic forecasts are used in the field of solar energy forecasting. The first one takes the form of Ensemble forecasts commonly provided by meteorological utilities such as ECMWF. The second one is based on statistical methods that generate quantiles forecasts. The first type of forecasts is treated in the first part of this article. In this second part, we focus on the assessment of the quality of quantile forecasts characterized by two main attributes namely reliability and resolution. More precisely, we propose a verification framework based on diagnostic tools and quantitative scoring rules that are specifically designed for the evaluation of quantile forecasts. The probabilistic models are evaluated on two selected sites that experience very different climatic conditions. It is shown that the decomposition into reliability and resolution of a scoring rule, the Continuous Ranked Probability Score (CRPS), may help to obtain a detailed picture of the performance of the models and consequently may help in selecting the best probabilistic method.
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Contributor : Mathieu David <>
Submitted on : Monday, September 13, 2021 - 10:04:00 AM
Last modification on : Monday, September 20, 2021 - 8:14:01 AM


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Philippe Lauret, Faly Ramahatana-Andriamasomanana, Josselin Le Gal La Salle, Mathieu David. Probabilistic Solar Forecasts Evaluation Part 2: Quantile Forecasts. ISES Solar World Congress 2019/IEA SHC International Conference on Solar Heating and Cooling for Buildings and Industry 2019, Nov 2019, Santiago, France. pp.1-7, ⟨10.18086/swc.2019.43.04⟩. ⟨hal-02899292⟩



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