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The influence of interannual variation and longterm effects of PV energy yields on financial models

: Müller, B.; Xu-Sigurdsson, B.; Bostock, P.; Farnung, B.


Institute of Electrical and Electronics Engineers -IEEE-:
IEEE 7th World Conference on Photovoltaic Energy Conversion, WCPEC 2018 : A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC, 10-15 June 2018, Waikoloa Village, HI, USA
Piscataway, NJ: IEEE, 2018
ISBN: 978-1-5386-8529-7
ISBN: 978-1-5386-8530-3
World Conference on Photovoltaic Energy Conversion (WCPEC) <7, 2018, Waikoloa/Hawaii>
Photovoltaic Specialists Conference (PVSC) <45, 2018, Waikoloa/Hawaii>
Photovoltaic Science and Engineering Conference (PVSEC) <28, 2018, Waikoloa/Hawaii>
European Photovoltaic Solar Energy Conference and Exhibition (EU PVSEC) <34, 2018, Waikoloa/Hawaii>
Conference Paper
Fraunhofer ISE ()

The uncertainty information provided by state-ofthe-art energy yield predictions for PV systems is not able to reflect deviations from predicted energy yields due to interannual variation of the solar resource and long-term effects such as degradation or long-term irradiance trends. As shown by a comparison of real life measurements on existing PV systems, the Monte Carlo approach used in the paper is able to better reproduce deviations between predictions and measurements. These Monte Carlo uncertainties are then used as input data for a financial model. Based on this, the uncertainty distribution of the internal rate of return for an example PV project is assessed and analyzed.