| dc.description.abstract | The solar photovoltaic (PV) market has grown very rapidly throughout the past 15 years and is quickly
becoming an international, non-subsidized market with increased demand for performance certainty.
An increasing number of studies analyze long term monitoring data to determine degradation rates,
or "rates of change" (RoCs). Analyses of long term monitoring data give insight in the performance
of PV power plants over time, but are found to be sensitive to uncertainties, especially those related
to irradiance measurements using silicon reference cells. In this thesis, the results of a degradation
analysis based on long term monitoring data of 80 crystalline silicon PV systems and the results of
six case studies are presented. The case study analysis focused on individual systems and sensors, and
used sensor calibration logs and SolarGIS irradiance data as a reference for measured irradiance. It was
found, that the reference cell soiling, drifting and switching from brand or type have a profound impact
on the resulting RoCs, leading to both positive RoCs of up to +1% per year, and strong negative RoCs
up to -4% per year. The case study analysis shows, however, that the RoCs are much lower if reference
cells are adjusted for soiling, drifting and sensor replacements or if satellite irradiance data is used.
This indicates, that the impact of biased irradiance data should not be underestimated. It was also
found, that the distribution of RoCs is strongly influenced by the age and size of the selected systems,
underlining the importance of system selection. The case study analysis indicates, that crystalline
silicon PV systems operating for 8+ years are expected to show a "rate of change" of -0.5% per year
or less. | |
