Irradiance and cloud optical properties from photovoltaic power data
- 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.
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| Document Type: | Conference Object |
|---|---|
| Language: | English |
| Author: | James Barry, Anna Herman-Czezuch, Nicola Kimiaie, Stefanie Meilinger, Christopher Schirrmeister, Johannes Grabenstein, Klaus Pfeilsticker, Claudia Emde, Felix Gödde, Bernhard Mayer, Hartwig Deneke, Jonas Witthuhn, Leonhard Scheck, Marion Schroedter-Homscheidt, Philipp Hofbauer, Matthias Struck |
| Parent Title (English): | D-A-CH MeteorologieTagung, 21. bis 25. März 2022 in Leipzig |
| Article Number: | 298 |
| URN: | urn:nbn:de:hbz:1044-opus-60638 |
| DOI: | https://doi.org/10.5194/dach2022-298 |
| Publisher: | Copernicus GmbH |
| Publishing Institution: | Hochschule Bonn-Rhein-Sieg |
| Date of first publication: | 2021/12/18 |
| Departments, institutes and facilities: | Internationales Zentrum für Nachhaltige Entwicklung (IZNE) |
| Dewey Decimal Classification (DDC): | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 551 Geologie, Hydrologie, Meteorologie |
| Entry in this database: | 2022/01/12 |
| Licence (German): |  Creative Commons - CC BY - Namensnennung 4.0 International |
