Data Filtering Impact on PV Degradation Rates and Uncertainty (Poster)

Conference · Thu Mar 01 04:00:00 EST 2012

OSTI ID:1046312

Jordan, Dirk C.; Kurtz, Sarah R.

To sustain the commercial success of photovoltaics (PV) it becomes vital to know how power output decreases with time. In order to predict power delivery, degradation rates must be determined accurately. Data filtering, any data treatment assessment of long-term field behavior, is discussed as part of a more comprehensive uncertainty analysis and can be one of the greatest sources of uncertaintyin long-term performance studies. Several distinct filtering methods such as outlier removal and inclusion of only sunny days on several different metrics such as PVUSA, performance ratio, DC power to plane-of-array irradiance ratio, uncorrected, and temperature-corrected were examined. PVUSA showed the highest sensitivity while temperature-corrected power over irradiance ratio was found to bethe least sensitive to data filtering conditions. Using this ratio it is demonstrated that quantification of degradation rates with a statistical accuracy of +/- 0.2%/year within 4 years of field data is possible on two crystalline silicon and two thin-film systems.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 1046312
• Report Number(s): NREL/PO-5200-54579
• Country of Publication: United States
• Language: English

Related Subjects

14 SOLAR ENERGY
24 POWER TRANSMISSION AND DISTRIBUTION
ACCURACY
DATA
METRICS
PERFORMANCE
PHOTOVOLTAIC POWER PLANTS
POWER GENERATION
SENSITIVITY
data filtering
degradation rates
outdoor performance
photovoltaic
uncertainty