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Title: Automated Data Collection for Determining Statistical Distributions of Module Power Undergoing Potential-Induced Degradation: Preprint

We propose a method for increasing the frequency of data collection and reducing the time and cost of accelerated lifetime testing of photovoltaic modules undergoing potential-induced degradation (PID). This consists of in-situ measurements of dark current-voltage curves of the modules at elevated stress temperature, their use to determine the maximum power at 25 degrees C standard test conditions (STC), and distribution statistics for determining degradation rates as a function of stress level. The semi-continuous data obtained by this method clearly show degradation curves of the maximum power, including an incubation phase, rates and extent of degradation, precise time to failure, and partial recovery. Stress tests were performed on crystalline silicon modules at 85% relative humidity and 60 degrees C, 72 degrees C, and 85 degrees C. Activation energy for the mean time to failure (1% relative) of 0.85 eV was determined and a mean time to failure of 8,000 h at 25 degrees C and 85% relative humidity is predicted. No clear trend in maximum degradation as a function of stress temperature was observed.
Authors:
;
Publication Date:
OSTI Identifier:
1150195
Report Number(s):
NREL/CP-5J00-62468
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 24th Workshop on Crystalline Silicon Solar Cells & Modules: Materials and Processes, 27-30 July 2014, Breckenridge, Colorado
Research Org:
National Renewable Energy Laboratory (NREL), Golden, CO.
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; 36 MATERIALS SCIENCE ENERGY CONVERSION; SILICON; DURABILITY; MODULE; DEGRADATION; PID; POTENTIAL-INDUCED DEGRADATION; Solar Energy - Photovoltaics