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Communication Dans Un Congrès Année : 2020

A Deep Physical Model for Solar Irradiance Forecasting with Fisheye Images

Résumé

We present a new deep learning approach for short-term solar irradiance forecasting based on fisheye images. Our architecture, based on recent works on video prediction with partial differential equations, extracts spatio-temporal features modelling cloud motion to accurately anticipate future solar irradiance. Our method obtains state-of-the-art results on video prediction and 5min-ahead irradiance forecasting against strong recent baselines, highlighting the benefits of incorporating physical knowledge in deep models for real-world physical process forecasting.
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Dates et versions

hal-02947332 , version 1 (23-09-2020)

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Vincent Le Guen, Nicolas Thome. A Deep Physical Model for Solar Irradiance Forecasting with Fisheye Images. CVPR OmniCV worshop 2020, Jun 2020, Seattle, United States. ⟨10.1109/CVPRW50498.2020.00323⟩. ⟨hal-02947332⟩
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