@inproceedings{BarryHerman-CzezuchKimiaieetal.2021,
  author    = {Barry, James and Herman-Czezuch, Anna and Kimiaie, Nicola and Meilinger, Stefanie and Schirrmeister, Christopher and Grabenstein, Johannes and Pfeilsticker, Klaus and Emde, Claudia and G{\"o}dde, Felix and Mayer, Bernhard and Deneke, Hartwig and Witthuhn, Jonas and Scheck, Leonhard and Schroedter-Homscheidt, Marion and Hofbauer, Philipp and Struck, Matthias},
  title     = {Irradiance and cloud optical properties from photovoltaic power data},
  booktitle = {D-A-CH MeteorologieTagung, 21. bis 25. M{\"a}rz 2022 in Leipzig},
  doi       = {10.5194/dach2022-298},
  institution = {Internationales Zentrum f{\"u}r Nachhaltige Entwicklung (IZNE)},
  pages     = {298},
  year      = {2021},
  abstract  = {The rapid increase in solar photovoltaic (PV) installations worldwide has resulted in the electricity grid becoming increasingly dependent on atmospheric conditions, thus requiring more accurate forecasts of incoming solar irradiance. In this context, measured data from PV systems are a valuable source of information about the optical properties of the atmosphere, in particular the cloud optical depth (COD). This work reports first results from an inversion algorithm developed to infer global, direct and diffuse irradiance as well as atmospheric optical properties from PV power measurements, with the goal of assimilating this information into numerical weather prediction (NWP) models.},
  language  = {en}
}