Module 30 year life: What does it mean and is it predictable-achievable? Page: 1 of 4
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SA402000-O91Z C,
Module 30 Year Life : What does it mean and is it predictable/achievable?
T. J. McMahon, G. J. Jorgensen, and R. L. Hulstrom
National Renewable Energy Laboratory, Golden, CO
D. L. King and M. A. Quintana
Sandia National Laboratories, Albuquerque, NMABSTRACT
We define what we mean by a 30-year module life and
the testing protocol that we believe is involved in achieving
such a prediction. However, we do not believe that a universal
test (or series of tests) will allow for such a prediction to be
made. We can test for a lot of things, but we believe it is
impossible to provide a 30-year certification for any PV
module submitted for test. We explain our belief in this paper.
1. Introduction
The photovoltaic (PV) industry wants a module
technology that will last 30 years in the field and a means by
which to certify that it will, indeed, last 30 years. First, we
must define what we mean by a 30-year life. Second, we will
lay out the accelerated environmental test (AET) protocol
involved in such a prediction. Third, we will discuss the time-
to-failure calculation and the likelihood of such a certification
process. And finally, short of such a certification process, we
discuss an approach for rank ordering and testing of failure
modes. The rank ordering would be similar to the "Life-Cycle
Energy Cost Impact" analysis proposed by R.G. Ross [1].
2. Thirty Year Life
The language used here is critical. It is clearly impossible
to expect every module produced of a given kind to last 30 yr
without failure. The issue is reliability. What constitutes a
failure for one person may not be a failure for others. As a
starting point we paraphrase a textbook definition of
reliability: "a reliable PV module has a high probability that it
will perform its intended purpose adequately for 30 yr, under
the operating conditions encountered." For simplicity we will
say a PV module fails to provide service if its power is down
by more than 30% after 30 years in its use environment. Also,
"a high probability" means that 95% of the modules in the
field will achieve this success. By "use environment" we
mean for any and all use environments in which the PV
module will be applied. Site metrology, handling, and
installation are included in use environment considerations.
3. Accelerated Environmental Testing
A life prediction approach specifically designed for PV
cells and minimodules is outlined elsewhere [2]. Lifetime
prediction tests appropriate for full-sized modules would be
possible only when a final module design is defined, all failure
modes are identified for that module design, and acceleration
parameters for each relevant environmental stress are known.
The AET's chosen must use stress or combinations of stresses
that will accelerate failure modes that are likely to occur in the
real world. Module lifetime in Florida may be very differentO
a
A
ETs
30
25 5
.-
20 10
15Technology "i"
Manufacturer "j"
Process "k"Failure Mode "I"
revealed with
acceleration parameter
for each stress.
Validate with the full
range of field conditions.
Time-To-Failure calculated
under any and all Use
Conditions, for each i, j, k,
and I.
Mixed, composite, and
competing risk models are
used to combine failure
modes as appropriate.Fig. 1. Diagram of Life Prediction Process
than in Arizona. We must decide which performance
parameter(s) should be measured to best monitor the failure
mode being evaluated and then define what constitutes a
failure for that performance parameter.
To use AETs for life prediction testing we divide the
protocol into five steps: (1) Identify and isolate all failure
modes, e.g., in a c-Si module we might look at solder bond
fatigue or in a thin-film module it might be film adhesion or
moisture intrusion.; (2) Design and perform AETs, e.g.
thermal cycling with series resistance as a metric or damp heat
with visual inspection as a metric; (3) Use appropriate
statistical distributions to model specific failure rates; (4)
Choose and apply relevant acceleration models to transform
failure rates; (5) Develop a total module failure rate as a
composite of individual rates to allow service lifetime
prediction for each use condition. Fig. 1 outlines this process.
In step (1), the first through li" failure mode must be
determined for each module submitted for test. The materials
technology and cell design is denoted by the subscript "i". If
multiple manufacturers are using that technology, we need a
second subscript "j" to denote the manufacturer and probable
difference in material processing and/or cell design. If there
are different processes or designs used by the same
manufacturer, then we need a third subscript "k". For each
module, MODiJ,k the l' failure mode must be identified and,
ideally, the underlying failure mechanism (cause) found.
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Mcmahon, T. J.; Jorgensen, G. J.; Hulstrom, R. L.; King, David L. & Quintana, Michael A. Module 30 year life: What does it mean and is it predictable-achievable?, article, April 11, 2000; Albuquerque, New Mexico. (https://digital.library.unt.edu/ark:/67531/metadc709645/m1/1/: accessed April 19, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.