@misc{6536c394d79546b0b609cbc964381992,
title = "Robust PV Degradation Methodology and Application",
abstract = "The degradation rate plays an important role in predicting and assessing the long-term energy generation of PV systems. Many methods have been proposed for extracting the degradation rate from operational data of PV systems, but most of the published approaches are susceptible to bias due to inverter clipping, module soiling, temporary outages, seasonality, and sensor degradation. In this manuscript, we propose a methodology for determining PV degradation leveraging available modeled clear-sky irradiance data rather than site sensor data, and a robust year-over-year (YOY) rate calculation. We show the method to provide reliable degradation rate estimates even in the case of sensor drift, data shifts, and soiling. Compared with alternate methods, we demonstrate that the proposed method delivers the lowest uncertainty in degradation rate estimates for a fleet of 486 PV systems.",
keywords = "degradation, PV reliability, rdtools",
author = "Dirk Jordan and Christopher Deline and Sarah Kurtz and Greg Kimball and Mike Anderson",
year = "2017",
language = "American English",
series = "Presented at the 44th IEEE Photovoltaic Specialist Conference, 25-30 June 2017, Washington, DC",
type = "Other",
}