Abstract
A novel approach for a blending between nowcasting and numerical weather prediction (NWP) for the surface incoming shortwave radiation (SIS) for a forecast horizon of 1–5 h is presented in this study. The blending is performed with a software tool called ANAKLIM++ (Adjustment of Assimilation Software for the Reanalysis of Climate Data) which was originally designed for the efficient assimilation of two-dimensional data sets using a variational approach. A nowcasting for SIS was already presented and validated in earlier publications as seamless solar radiation forecast (SESORA). For our blending, two NWP models, namely the ICON (Icosahedral Non-hydrostatic model) from the German weather Service (DWD) and the IFS (Integrated Forecasting System) from the European Centre for Medium-Range Weather Forecasts (ECMWF), were used. The weights for the input data for ANAKLIM++ vary for every single forecast time and pixel, depending on the error growth of the nowcasting. The results look promising, since the root mean square error (RMSE) and mean absolute error (MAE) of the blending are smaller than the error measures of the nowcasting or NWP models, respectively.
Highlights
The contribution of photovoltaic (PV) power to the electricity mix increased significantly over the last decades in accordance with the overall importance of renewable energies [1,2]
The results look promising, since the root mean square error (RMSE) and mean absolute error (MAE) of the blending are smaller than the error measures of the nowcasting or numerical weather prediction (NWP) models, respectively
The nowcasting of solar radiation is based on the optical flow of the effective cloud albedo derived from the visible channel of Meteosat Second Generation (MSG) [51,52]
Summary
The contribution of photovoltaic (PV) power to the electricity mix increased significantly over the last decades in accordance with the overall importance of renewable energies [1,2]. And temporally high resolved solar radiation forecasts are strongly required due to the rapid installation of solar power worldwide and the integration of fluctuating PV power into the grid [3]. It is essential for management and operation strategies that solar radiation forecasts deliver reliable predictions of the expected PV power for the 0–12 h [1,4,5,6,7]. Because weather and power forecasts always contain a part of uncertainty there will be balancing costs for transmission system operators (TSO) related to forecast errors. With regard to the rising share of renewable energies as a source of electricity, the need for more accurate forecasts is growing rapidly
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