Forecasts of solar radiation are needed for the operation of solar power plants, in order to integrate stable electricity into the grid and to optimize the production of solar energy according to demand.
In this project we explore the construction of a system for the forecast of solar radiation based on the use of satellite measurements, numerical weather prediction modelling, and radiative transfer modelling. We combine Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) images and cloud products with forecasts of the non-hydrostatic numerical weather prediction model HARMONIE. Evaluation of the forecasts is performed by means of observations within the framework of the Baseline Surface Radiation Network (BSRN) site in Cabauw.
Short-term (0-6h) forecasts are derived from the advection of SEVIRI cloud physical properties by means of atmospheric motion vectors. Once forecasts of cloud properties are known we calculate broadband and spectral fluxes of direct, diffuse, and global solar irradiance using the SICCS (Surface Insolation under Clear and Cloudy skies derived from SEVIRI imagery) algorithm.
Longer-term forecasts (0-48h) are produced by HARMONIE. Since the initial state of HARMONIE is crucial for a good solar radiation forecast, SEVIRI cloud masks will be assimilated in HARMONIE. The HARMONIE-based solar radiation forecasts will outperform the satellite-based forecasts at longer forecast times. The tipping point will probably lie somewhere in the short-term forecast window, i.e. between 0 and 6h. The determination of this tipping point is one of the aims of this project. Also we will run HARMONIE in with different configurations to investigate which state will result in the best solar radiation forecast.The results are described by Wang et al. (2019).
Reference
Wang, P., R. van Westrhenen. J. F. Meirink, S. van der Veen, and W. Knap. 2019. Surface solar radiation forecasts by advecting cloud physical properties derived from Meteosat Second Generation observations. Solar Energy, 177, 47-58, https://doi.org/10.1016/j.solener.2018.10.073.
