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Irradiance and atmospheric optical properties from photovoltaic power data: model improvements and first results

  • Photovoltaic (PV) power data are a valuable but as yet under-utilised resource that could be used to characterise global irradiance with unprecedented spatio-temporal resolution. The resulting knowledge of atmospheric conditions can then be fed back into weather models and will ultimately serve to improve forecasts of PV power itself. This provides a data-driven alternative to statistical methods that use post-processing to overcome inconsistencies between ground-based irradiance measurements and the corresponding predictions of regional weather models (see for instance Frank et al., 2018). This work reports first results from an algorithm developed to infer global horizontal irradiance as well as atmospheric optical properties such as aerosol or cloud optical depth from PV power measurements.

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Metadaten
Document Type:Conference Object
Language:English
Author:James Barry, Dirk Böttcher, Johannes Grabenstein, Klaus Pfeilsticker, Anna Herman-Czezuch, Nicola Kimiaie, Stefanie Meilinger, Christopher Schirrmeister, Felix Gödde, Bernhard Mayer, Hartwig Deneke, Jonas Witthuhn, Philipp Hofbauer, Matthias Struck
Parent Title (English):EGU General Assembly 2021, Gather Online, 19-30 April 2021
URN:urn:nbn:de:hbz:1044-opus-54013
DOI:https://doi.org/10.5194/egusphere-egu21-7581
Publisher:Copernicus GmbH
Publishing Institution:Hochschule Bonn-Rhein-Sieg
Date of first publication:2021/03/05
Note:
© Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License.
Departments, institutes and facilities:Fachbereich Elektrotechnik, Maschinenbau, Technikjournalismus
Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE)
Internationales Zentrum für Nachhaltige Entwicklung (IZNE)
Projects:MetPVNet - Entwicklung innovativer satellitengestützter Methoden zur verbesserten PV-Ertragsvorhersage auf verschiedenen Zeitskalen für Anwendungen auf Verteilnetzebene (DE/BMWi/0350009A)
Dewey Decimal Classification (DDC):5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 551 Geologie, Hydrologie, Meteorologie
Entry in this database:2021/05/05
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International