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Seasonal and short-term weather-related changes in the solar spectrum can induce shifts in the performance of photovoltaic (PV) systems that affect both annual energy predictions and system characterization. The spectral shift factor, which is a metric indicative of how much the performance of a PV system will vary from nameplate due to deviations from the ASTM G173 spectrum (air mass of 1.5), is predicted using TMY3 data and the simple model of the atmospheric radiative transfer for sunshine (SMARTS) model and is correlated with cadmium telluride (CdTe) PV system performance in four different climates. The predicted spectral shift factors for CdTe systems show improved performance in the late summer and early fall and diminished performance in the winter. These intraannual variations can be as large as ± 3%, but annual spectral shift factors are typically within ± 1% of nameplate. The spectral shift factor of CdTe systems was found to be most sensitive to the precipitable water content of the atmosphere. Consequently, a parameterization of CdTe spectral shift factor as an exponential function of precipitable water is derived using the outputs of the SMARTS model in 11 locations. This parameterization is shown to predict observed monthly and daily fluctuations in CdTe PV performance. Future efforts will incorporate this methodology into energy predictions that will reduce uncertainty.
Date of Publication: Jan. 2013