Very short term forecasting of the Global Horizontal Irradiance using a spatio-temporal autoregressive model
2014
The integration of massive solar energy supply in the existing grids requires an accurate forecast of the
solar resourcesto manage the energetic balance. In this context, we propose a new approach to forecast the Global Horizontal Irradiance at ground level from satellite images and ground based measurements. The training of spatio-temporal multidimensional
autoregressive modelswith HelioClim-3 data along with 15-min averaged GHI times series is tested with respect to a ground based station from the BSRN network. Forecast horizons from 15 min to 1 h provided very promising results validated on a one year ground-based pyranometric data set. The performances have been compared to another similar method from the literature by means of relative metrics. The proposed approach paves the way of the use of satellite-based surface
solar irradiance(SSI) estimation as an SSI map
nowcastingmethod that enables to capture spatio-temporal correlation for the improvement of a local SSI forecast.
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