@techreport{MeilingerHermanCzezuchKimiaieetal.2021,
  type      = {Working Paper},
  author    = {Stefanie Meilinger and Anna Herman-Czezuch and Nicola Kimiaie and Christopher Schirrmeister and Rone Yousif and Stefan Geiss and Leonhard Scheck and Martin Weissmann and Felix G{\"o}dde and Bernhard Mayer and Tobias Zinner and James Barry and Klaus Pfeilsticker and Markus Kraiczy and Kevin Winter and Abdullah Altayara and Christian Reise and Mariella Rivera and Hartwig Deneke and Jonas Witthuhn and Jethro Betcke and Marion Schroedter-Homscheidt and Philipp Hofbauer and Bernhard Rindt},
  title     = {Development of innovative satellite-based methods for improved PV yield prediction on different time scales for distribution grid level applications (MetPVNet)},
  isbn      = {978-3-96043-094-0},
  issn      = {2511-0861},
  doi       = {10.18418/978-3-96043-094-0},
  url       = {https://nbn-resolving.org/urn:nbn:de:hbz:1044-opus-60399},
  institution = {Institut f{\"u}r Technik, Ressourcenschonung und Energieeffizienz (TREE)},
  series = {IZNE Working Paper Series},
  pages     = {18},
  year      = {2021},
  abstract  = {In the research project \"MetPVNet\", both, the forecast-based operation management in distribution grids and as well as the forecasts of the feed-in of PV-power from decentralized plants could be improved on the basis of satellite data and numerical weather forecasts. Based on a detailed network analyses for a real medium-voltage grid area, it was shown that both – the integration of forecast data based on satellite and weather data and the improvement of subsequent day forecasts based on numerical weather models – have a significant added value for forecast-based congestion management or redispatch and reactive power management in the distribution grid. Furthermore, forecast improvements for the forecast model of the German Weather Service were achieved by assimilating visible satellite imagery, and cloud and radiation products from satellites were improved, thus improving the database for short-term forecasting as well as for assimilation. In addition, several methods have been developed that will enable forecast improvement in the future, especially for weather situations with high cloud induced variability and high forecast errors. This article summarizes the most important project results.},
  language  = {en}
}