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The impact of angular dependent loss measurement on PV module energy yield prediction

: Ebert, M.; Stascheit, H.; Hädrich, I.; Eitner, U.

Volltext urn:nbn:de:0011-n-3112769 (135 KByte PDF)
MD5 Fingerprint: daa78cb8de5793f51d5377a9d7b89997
Erstellt am: 5.11.2014

Bokhoven, T.P. ; European Commission:
29th European Photovoltaic Solar Energy Conference and Exhibition, EU PVSEC 2014 : Proceedings of the international conference held in Amsterdam, The Netherlands, 22 - 26 September 2014, DVD
München: WIP, 2014
ISBN: 3-936338-34-5
European Photovoltaic Solar Energy Conference and Exhibition (EU PVSEC) <29, 2014, Amsterdam>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer ISE ()
Photovoltaische Module; Systeme und Zuverlässigkeit; Photovoltaische Module und Kraftwerke; Modulentwicklung; Antireflection-Coating; Fassade; modelling; performance; methods

Different methods to characterize the Incidence Angle Modifier (IAM) of PV modules have been presented in the past [1-4]. From the authors perspective it is questionable if the detailed characterisation of the angular behaviour of PV modules has any significant benefits to yield modelling activities undertaken to forecast the power energy yield of a PV system. The purpose of this work is to evaluate the influence of IAM data from different measurement techniques as input on a yearly yield model. Several sample modules with different top cover such as standard Low iron glass, anti-reflection (AR) coated glass or structured ETFE foils have been characterized on three different test setups, two outdoor and one in the sun simulator. The measured IAM values are fitted to a double exponential model and used in a simple yield model to evaluate the influence of the different measuring methods to the yearly yield for modules with different orientations and different geographical locations. The results show that the different module covers have a significant impact on the IAM, however on yearly yield basis the cosine loss at high angle of incidence (AOI) dominates, reducing the impact of IAM differences. Secondly we show that the AIM characterization is subject of statistical measurement errors caused by the test setup or the module itself. To increase comparability of IAM data we recommend determining a uniform measurement method with precise definition of the test setup.