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Yield predictions for photovoltaic power plants: empirical validation, recent advances and remaining uncertainties
Author(s) -
Müller Björn,
Hardt Laura,
Armbruster Alfons,
Kiefer Klaus,
Reise Christian
Publication year - 2016
Publication title -
progress in photovoltaics: research and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.286
H-Index - 131
eISSN - 1099-159X
pISSN - 1062-7995
DOI - 10.1002/pip.2616
Subject(s) - irradiance , photovoltaic system , solar resource , yield (engineering) , solar irradiance , environmental science , solar energy , meteorology , atmospheric sciences , satellite , empirical modelling , computer science , simulation , engineering , geography , materials science , physics , optics , electrical engineering , aerospace engineering , metallurgy
Yield predictions are performed to predict the solar resource, the performance and the energy production over the expected lifetime of a photovoltaic (PV) system. In this study, we compare yield predictions and monitored data for 26 PV power plants located in southern Germany and Spain. The monitoring data include in‐plane irradiance for comparison with the estimated solar resource and energy yield for comparison with predicted performance. The results show that because of increased irradiance in recent years (‘global brightening’) the yield predictions systematically underestimate the energy yield of PV systems by about 5%. Because common irradiance databases and averaging times were used for the yield predictions analysed in this paper, it is concluded that yield predictions for areas where the global brightening effect occurred in general underestimated the energy yield by the same magnitude. Using recent satellite‐derived irradiance time series avoids this underestimation. The observed performance ratio of the analysed systems decreases by 0.5%/year in average with a relatively high spread between individual systems. This decrease is a main factor for the combined uncertainty of yield predictions. It is attributed to non‐reversible degradation of PV cells or modules and to reversible effects, like soiling. Based on the results of the validation, the combined uncertainty of state of the art yield predictions using recent solar irradiance data is estimated to about 8%. Copyright © 2015 John Wiley & Sons, Ltd.