Long-Term Impact of Light- and Elevated Temperature-Induced Degradation on Photovoltaic Arrays

Abstract: Low levelized cost of electricity (LCOE) has been identified as critical for widespread adoption of photovoltaics (PV) without subsidies. Maintaining decades-long high-energy production is often an under-recognized opportunity in meeting cost goals because component lifetimes are not fully quantified at the time of manufacture. Whereas certain standardized tests minimize risk of early failure, there is little guidance to quantitatively predict degradation (or lack thereof) over decades, based on accelerated tests. In this article, we move toward bridging the understanding between indoor accelerated tests and outdoor performance data, with the goal of predicting energy yield with enough accuracy to inform financial decisions. Light- and elevated temperature-induced degradation (LETID) in p-type Si modules is analyzed in terms of impact on long-term module performance and thus LCOE. A method to predict the progression of LETID, using fixed kinetic constants and a numerical solution to the basic reaction rate equations, is detailed. Predictions are compared against both published data and that new to this study. These data include both indoor accelerated tests and fielded modules. We use the results in financial models to derive LCOE of modules in different climates with varying amounts of LETID, including uncertainty. Cost models based on the predictions indicate that LETID has a significant and climate-dependent impact on LCOE. We show that—even given the uncertainties identified in the study—these financial calculations can provide useful guidance to quantify risk based on accelerated test results. The analysis serves as an example of developing a predictive approach to PV reliability using physics of failure. Graphical abstract: [Figure not available: see fulltext.] Impact statement: In recent years, deployment of photovoltaics (i.e., solar panels, or “PVs”) has grown at an astounding rate: Global electricity generation from PVs has increased by a factor of nearly 30 in the past 10 years. This rapid expansion has been driven by both remarkable cost decreases and societal demand for decarbonization. Product durability and consumer confidence are key elements of maintaining a robust industry and low costs. It is thus necessary to augment current empirical methods of assessing PV reliability with more predictive and quantitative assessments. This article applies basic findings of solar-cell defect physics in a way that can help industry stakeholders estimate the financial impacts of PV panel reliability. Light and elevated temperature-induced degradation is analyzed in terms of impact on long-term module performance and levelized cost of electricity. The predictions generated in this work are compared against experimental data, both from indoor accelerated tests and from fielded modules. The approach of comparing a physical model to indoor and outdoor data sets, setting limits on uncertainty, then translating energy yield predictions to financial impacts, is generally applicable to any PV degradation mechanism.