Earth observation based cloud, aerosol, and irradiance information for applications in solar energy generation

The number of renewable energy systems has increased with the implementation of the feed-in tariff in Germany. Nowadays, more than 1.5 million photovoltaic systems are connected to the grid and over 85 % are installed at the low voltage level. The distribution system operators (DSO) have now to adapt their grid operation for high load as well as high feed-in times. An annual energy feed-in or demand value is not sufficient for planning and operating low voltage grids with volatile feed-in power characteristics exceeding the maximum power consumption by 5 to 10 times. Based on the historical development, there are normally no measurement devices in the low voltage grid, except the once yearly evaluated meters in the households and power drag-indicators in transformer stations. These power drag-indicators usually are also checked only once per year and do not solve the need for monitoring the grid state. One option for closing parts of this information gap is the use of data on irradiance conditions taken from remote sensing technologies. With data from the Meteosat Second Generation meteorological satellite (MSG) updated each 15 min (or even 5 minutes in the rapid scan mode), the near real-time estimation of the state of a low voltage grid is performed. Power generation by PV can be described with the knowledge of irradiance and temperature. This covers the feed-in side of the grid state. However, the demand – not accessible be remote sensing – is describable only by statistical approaches. Having used MSG data for nowcasting, we also introduce MSG based surface irradiance as provided by the Copernicus Atmosphere Monitoring Service (CAMS) for solar resource assessments. The radiation service consists of an all-sky radiation time series service taking satellite-based cloud parameters into account and a clear-sky radiation time series service for cloud-free skies. We also discuss variability of irradiances as seen from space and the extended solar power plant site assessment based on knowledge on clouds and aerosols.