Compendium of photovoltaic degradation rates

Abstract Published data on photovoltaic (PV) degradation measurements were aggregated and re‐examined. The subject has seen an increased interest in recent years resulting in more than 11 000 degradation rates in almost 200 studies from 40 different countries. As studies have grown in number and size, we found an impact from sampling bias attributable to size and accuracy. Because of the correlational nature of this study we examined the data in several ways to minimize this bias. We found median degradation for x‐Si technologies in the 0.5–0.6%/year range with the mean in the 0.8–0.9%/year range. Hetero‐interface technology (HIT) and microcrystalline silicon (µc‐Si) technologies, although not as plentiful, exhibit degradation around 1%/year and resemble thin‐film products more closely than x‐Si. Several studies showing low degradation for copper indium gallium selenide (CIGS) have emerged. Higher degradation for cadmium telluride (CdTe) has been reported, but these findings could reflect a convolution of less accurate studies and longer stabilization periods for some products. Significant deviations for beginning‐of‐life measurements with respect to nameplate rating have been documented over the last 35 years. Therefore, degradation rates that use nameplate rating as reference may be significantly impacted. Studies that used nameplate rating as reference but used solar simulators showed less variation than similar studies using outdoor measurements, even when accounting for different climates. This could be associated with confounding effects of measurement uncertainty and soiling that take place outdoors. Hotter climates and mounting configurations that lead to sustained higher temperatures may lead to higher degradation in some, but not all, products. Wear‐out non‐linearities for the worst performing modules have been documented in a few select studies that took multiple measurements of an ensemble of modules during the lifetime of the system. However, the majority of these modules exhibit a fairly linear decline. Modeling these non‐linearities, whether they occur at the beginning‐of‐life or end‐of‐life in the PV life cycle, has an important impact on the levelized cost of energy. Copyright © 2016 John Wiley & Sons, Ltd.