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Photovoltaic-battery systems as irradiance sensors: first results of a prototype study

  • In view of the rapid growth of solar power installations worldwide, accurate forecasts of photovoltaic (PV) power generation are becoming increasingly indispensable for the overall stability of the electricity grid. In the context of household energy storage systems, PV power forecasts contribute towards intelligent energy management and control of PV-battery systems, in particular so that self-sufficiency and battery lifetime are maximised. Typical battery control algorithms require day-ahead forecasts of PV power generation, and in most cases a combination of statistical methods and numerical weather prediction (NWP) models are employed. The latter are however often inaccurate, both due to deficiencies in model physics as well as an insufficient description of irradiance variability.

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Metadaten
Document Type:Conference Object
Language:English
Author:James Barry, Anna Herman-Czezuch, Daniel Fischer, Stefanie Meilinger, Rone Yousif, Felix Gödde, Alexander Bergenthal
Parent Title (English):EMS Annual Meeting Abstracts
Volume:18
Article Number:392
URN:urn:nbn:de:hbz:1044-opus-58175
DOI:https://doi.org/10.5194/ems2021-392
Publisher:Copernicus GmbH
Date of first publication:2021/06/18
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:2021/08/27
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International