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Nondestructive Performance Characterization Techniques for Module Reliability
National Renewable Energy Laboratory (NREL)
1617 Cole Blvd., Golden, CO 80401
This paper describes nondestructive characterization
techniques for module reliability. These techniques
include light and dark current versus voltage and related
analysis such as resistance, diode quality factor, and dark
current. The use of the NREL laser scanner at zero volts
and forward bias is also described as a technique to
uncover cracks, shunts, and open-circuit regions in a
module. Quantum-efficiency measurements of isolated
cells or regions in a module are also possible. The
interpretation of laser-scanning data is enhanced by hot-
spot testing with an infrared camera or thermographic
paper. Specialized nondestructive techniques have also
been developed to determine the shunt resistance of
individual cells in a module by selective shading of cells
under sunlight. Ultraviolet fluorescence and reflectivity
measurements at NREL have proven useful in evaluating
When modules or systems change their performance in
the field it is often desirable to determine why in a
nondestructive manner so that the samples can be
redeployed to monitor further changes. This paper
summarizes the nondestructive analysis capability within
the National Center for Photovoltaics at NREL, with
emphasis on the capabilities of the PV Cell and Module
Performance Characterization team. These capabilities
include current versus[Voltage (I-V), quantum efficiency,
laser scanning, shunt-resistance screening, hot-spot
testing, and reflectivity / fluorescence analysis. This
paper will not discuss reflectance and fluorescence as a
tool do determine the state of degradation of
encapsulants but a summary of the technique can be
found in [1,2]. Visual inspection of the module is
essential to identify delamination, corrosion, cracks,
electromigration and other exposure related defects.
2. Current versus Voltage
The most common procedure to determine
performance changes is to measure the I-V properties
under standard illumination and determine if the
maximum power has changed. Unfortunately, the
maximum power has relatively large random error,
which hampers the ability to resolve changes. At best,
this random error in the maximum power is typically
2%. If the modules are mounted in a system, then it is
time consuming to individually unmount the modules,
bring them inside, and test them. An alternative is to
determine the performance of the system as a function of
time. The method developed at PVUSA bases the
power on a multiple linear regression of power as a
function of air temperature, plane of array irradiance,
and wind speed . This method can be used to determine
the performance of a system over time in monthly chunks or
any other time interval. Figure 1 is an example of the user
interface of a Labview program that allows analysis of any
testbed's data set(s) providing there is a text file that
contains the data, time, plane-of-array irradiance, air
temperature, and wind speed. This particular version
handles data from 7 different systems and individual module
testbeds. The program takes about 2 min to read in the data
and about 10 s to process the 161,000 data points based
upon user selected filtering via sliders in the example.
There is no upper limit to the number of points that the
software can analyze. It has analyzed more than 300,000
points for one system.
Multiple Linear Regression
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Figure 1. User interface for Labview software package to
evaluate the maximum power using a multiple linear
regression to irradiance, air temperature, and wind speed.
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Figure 2. Fill factor
changes with exposure time for 28
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Emery, K. Nondestructive Performance Characterization Techniques for Module Reliability, article, May 1, 2003; Golden, Colorado. (https://digital.library.unt.edu/ark:/67531/metadc1406911/m1/3/: accessed April 25, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.