@misc{4db301fde2734500a4ed7cfdc4914b19,
title = "Uncertainty Analysis for Photovoltaic Degradation Rates (Poster)",
abstract = "Dependable and predictable energy production is the key to the long-term success of the PV industry. PV systems show over the lifetime of their exposure a gradual decline that depends on many different factors such as module technology, module type, mounting configuration, climate etc. When degradation rates are determined from continuous data the statistical uncertainty is easily calculated from the regression coefficients. However, total uncertainty that includes measurement uncertainty and instrumentation drift is far more difficult to determine. A Monte Carlo simulation approach was chosen to investigate a comprehensive uncertainty analysis. The most important effect for degradation rates is to avoid instrumentation that changes over time in the field. For instance, a drifting irradiance sensor, which can be achieved through regular calibration, can lead to a substantially erroneous degradation rates. However, the accuracy of the irradiance sensor has negligible impact on degradation rate uncertainty emphasizing that precision (relative accuracy) is more important than absolute accuracy.",
keywords = "degradation rates, irradiance, photovoltaic, PV",
author = "Dirk Jordan and Sarah Kurtz and Cliff Hansen",
year = "2014",
language = "American English",
series = "Presented at the Photovoltaic Module Reliability Workshop (PVMRW), 25-26 February 2014, Golden, Colorado",
type = "Other",
}