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SIMULATION AND CHARACTERIZATION OF SPATIAL VARIATION OF SHUNTS IN INDUSTRIAL
SOLAR CELLS BY PSPICE AND DARK LOCK-IN INFRARED THERMOGRAPHY
P. Somasundaran, A. Sinha, R. Gupta
Department of Energy Science and Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
Email: somasundaran_kerala@iitb.ac.in, Tel: +91-22-25767837, Fax: +91-22-2576-4890
ABSTRACT: Shunting is one of the major problems in solar cell which degrades cell performance and
efficiency.This work aims to investigate the degradation in cell performance caused by the presence of shunts at
various locations of industrial mono-crystalline and multi-crystalline silicon solar cells. Location, nature and area of
these shunts existing in silicon solar cells have been examined by Lock-in Thermography (LIT). Spatial dependence
of shunts has been studied by considering the shunted region of same area at various locations of the cell such as
shunt under bus bar, shunt on edge and shunt between bus bars. In each case, degradation in fill factor, efficiency and
the total shunt resistance of cell has been estimated by distributed diode model approach based on single diode model
of solar cell considering the shunted region of same area and severity.
Keywords: Shunts, Silicon Solar Cell, Simulation, PSPICE, Lock-in Thermography, Distributed Diode Model
1 INTRODUCTION
Silicon solar cells often suffer from shunts which are
internal short circuits causing degradation in cell
performance and efficiency. Shunts can broadly be
classified in two categories based on the origin: process
induced shunts and material related shunts. Process
induced shunts are formed during the production due to
problems associated with fabrication machines. These
types of shunts can be minimized by better process
control, monitoring tool, and handling. Some typical
process related shunts formation happens due to cracks in
wafer, scratches, improper metallization contact,
Aluminium particles, etc. Whereas, material related
shunts are strongly recombinative crystal defects,
macroscopic Si3N4 inclusions, SiC particles and SiC
filament-type precipitates [1]. These can be minimized by
using better quality of material which will increase cost
of cell.
The shunts offer alternative conductive parallel paths
for the current to sink and thus reduces the cell output
current. Shunts also cause reduction of the open circuit
voltage. Hence the degradation in fill factor and
efficiency are caused by the shunts. The numerical value
of the degradation in efficiency and fill factor due the
presence of shunts depends not only on the severity or
magnitude of the shunt but also on the nature, location
and extent or area of the shunts.
The shunt can be of two different nature: ohmic
shunts and non-ohmic or diode like shunts. The ohmic or
linear shunts follow a linear I-V relationship, i.e. they
obey Ohm’s law. The diode like shunts are due to
recombination centres in the cell with ideality factor of
even upto 5 and above.
This work aims to investigate the degradation in
efficiency and fill factor caused by the shunts at various
locations of industrial silicon solar cells, and thus to
quantify the degradation in overall performance due to
the presence of shunts at different locations of the cell
and to study their effect on the cell performance by
PSpice simulations.
2 APPROACH
The presented simulation approach is simple and can
be applied to any type of industrial solar cell to
Figure.1: Flow chart showing the methodology used for
modelling and simulation
understand and quantify the effect of shunts on solar cell
performance. The spatial dependence of shunts in
industrial solar cells of large area has been investigated
by a distributed diode model approach based on the
electrical equivalent circuit of the solar cell and DLIT
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technique. The spatial dependence of the shunts at
various locations of the cell has also been quantified here
in terms of efficiency using a novel approach.
The presented approach is useful and relevant to
industry to classify the shunts in different categories
based on the level of severity in order to tackle the
shunting problem during production. Using the approach,
shunts causing the greatest reduction in output power
may be removed or isolated using laser technique [2], but
leaving out those shunts which cause relatively low loss
in efficiency of the cell. Even if they can not be removed,
correcting steps in production can be taken up based on
severirty of shunts. Since the LIT technique can detect
strong shunts in a few seconds of measurement time, the
simulation approach presented here can be implemented
in industry.
The basic outline of the methodology for modeling
and simulation is described in the flow chart shown in
Fig. 1.
To understand the effect of shunts on the solar cell
having dimensions of 125 mm x 125 mm, schematic of
which is shown in Fig. 2(a) with position of three shunts,
the cell was divided into 375 x 375 equal elementary
areas, as shown in Fig. 2(b).
(b)
Figure.2: (a) Schematic of the cell showing three
different shunts positions.(b) Meshing over the cell to
divide it into small equal elementary areas.
Each elementary area was modeled by solar cell
equivalent circuit consisting of a diode, a shunt resistance
and a current source in parallel as shown in Fig. 3.
Figure.3: Distributed diode model approach of solar cell
Resistances have been connected laterally between
each neighboring elementary areas corresponding to
sheet and bulk resistance of the cell. Electrical equivalent
circuit of the solar cell, consisting of distributed diodes in
parallel with current source and shunt resistance, with a
series resistance has been exploited to study the effect of
shunting on the cell performance. A similar type of
approach has been applied [3] to investigate pointed
shunts in laboratory made small solar cells .
Simulations have been performed using the
distributed diode model of solar cell by a circuit
simulation software PSpice [4] to investigate the effects
of shunts on the cells performance [5, 6, 7]. From
experimental dark I-V of the cell, two parameters, reverse
saturation current (I0) and the ideality factor (n) are
determined by plotting ln(I) - V graph. The forward dark
I-V characteristic of a diode can be written in following
form:
(1)
where I, I0, q, V, n, k, and T are diode forward current,
reverse saturation current, electronic charge, forward
voltage, diode ideality factor, Boltzmann’s constant and
temperature respectively. The parameters I0 and n were
thus calculated from the intercept and slope of the curve
by using equation (1). Diodes were characterized with
these respective I0 and n.
For obtaining the simulated I-V characteristics,
varying voltage was applied across the p and n side. In
case of illuminated I-V curve, current source
corresponding to the short circuit current of elementary
diode was applied.
3 EXPERIMENTAL SET UP AND PROCEDURE
Based on the excitation sources to the cell, there are
mainly two different types of lock-in thermography
methods: Dark-LIT (DLIT) and Illuminated-LIT (ILIT).
In DLIT, the cell is periodically excited by external
power supply whereas in case of ILIT cell is periodically
excited by light source. Each of these methods has its
own advantages and limitations [8]. In this work, DLIT
was preferred because it it has an advantage to classify
the ohmic and non-ohmic shunts apart from its simplicity
in realization compared to ILIT. In DLIT, only dark
current will flow through the cell. At shunt sites, an
increased current causes heating of the solar cell which
can be detected by lock-in thermography technique. To
determine whether the shunt is ohmic or non-ohmic,
DLIT images are to be taken under both forward and
(a)
(a)
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reverse bias. If the DLIT signals at shunts position have
same strength in both images, the shunts are ohmic. If the
signals differ significantly, those shunts are non-ohmic.
In reverse bias conditions, no current flows through the
sample except the leakage current which is negligible
therefore it will be easy to detect ohmic shunts in reverse
bias.
The schematic diagram of lock-in thermography
setup is shown in Fig. 4 which was used to perform DLIT
on industrial Si solar cells. The system is equipped with
an Indium Antimonide (InSb) detector with focal plane
array; Stirling cooled camera head with a pixel resolution
of 320 x 256 pixels. The detector is sensitive in 3-5 µm
wavelength and works at maximum frame rate of 162 Hz
in full window. One programmable DC power supply
acts as an excitation source for DLIT tests. Controller
synchronizes the power supply excitation with the frames
of camera to implement lock-in algorithm over the
captured images.
Figure.4: Block diagram of the experimental set-up
4 EXPERIMENTAL RESULTS
DLIT measuremnts were performed on many
industrial Si cells in order to know the locations and
nature of shunts. Most of the shunts were ohmic in
nature. Both extended and point shunts have been found
in the DLIT images. Present work is mainly focused on
extended shunts. Therefore three cells (named as A, B
and C) having extended shunts have been choosen for the
study. A and B are monocrystalline and C is multi-
crystalline.These cells have ohmic shunts at different
locations. These locations were
1) Shunt between bus bars in cell A, 2) Shunt on the
bus bar in cell B and 3) Shunt on the edge of the cell in
cell C. These three cases of shunt are discussed briefly in
the paper.
4.1 Shunt between bus bars
The DLIT images of the mono-crystalline solar cell is
shown in Fig.5, reveals that an extended shunt is located
in between the busbars (more towards the left busbar) of
the cell. Also, the images shows that strength of lock-in
signal in forward and reverse bias is the same, which
inidicates that the shunt is ohmic in nature. Therefore the
shunt was modelled by a simple resistance, in the
distributed diode model of the cell. The shunted area in
both reverse and forward bias was the same.
Figure.5: DLIT Image of the cell A in a) Forward bias,
b)Reverse bias having shunt between busbars
4.2 Shunt on the bus bar
The DLIT images of a mono-crystalline soalr cell B
having an extended shunt on the busbar is shown in
Fig.6. The shunt is ohmic in nature since the strength of
lock-in signal in forward and reverse bias is the same.
Figure.6: DLIT image of the cell B in a) Forward bias,
b) Reverse bias having shunt on the busbar
4.3 Shunt on the edge
Fig.7 shows the DLIT images of the multi-crystalline
cell C having an extended ohmic shunt on the edge.
Figure.7:.DLIT Image of the cell C in a)Forward bias,b)
Reverse bias showing the shunt on the edge.
5 SIMULATION RESULTS AND DISCUSSION
Based on the simulation approach, dark I-V curves
were plotted for the cell under study, one in absence of
shunt and others in presence of shunt at locations such as,
under the bus bar, between the bus bars and on the edge,
after obtaining all the parameters required for plotting.
Solar Cell
with holder
a
Shunt
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The shunt resistance of the cell was estimated while
varying the resistance of the shunted area. Variation of
shunt resistance of cell (Cell Rsh) with the resistance of
the shunt (Shunt Rsh) for different positions of shunt has
been plotted as shown in Fig. 8. Percentage degradation
in cell Rsh in comparison with the shunt resistance of the
non-shunted cell for all the three cases of shunts are
shown in Fig.9. Percentage degradation in cell Rsh for
shunt under the bus bar with respect to the edge shunt and
the shunt between bus bars is plotted in Fig. 10.
The value of resistance at shunt location was varied
over a wide range of magnitude to understand the nature
of degradation caused by shunt of varying magnitude or
severity .
Figure.8:Variation of shunt resistance of cell with
resistance of shunt for different positions of
shunt , X axis values are in logarithmic scale.
Figure.9: Variation of % Degradation of shunt resistance
of the shunted cell with respect to the shunt
resistance of the non-shunted cell for different
positions of shunt .
The effect of spatial variation of the shunted area on
the fill factor of the cell was studied. The variation in the
fill factor for different spatial locations of shunt in the
cell has been found out and is shown in Fig. 11. It depicts
the effect of shunts on fill factor for the edge shunt; shunt
between busbars and shunt under the bus bar, with the
shunted area being the same in each case.
Percentage degradation in fill factor for the shunt
under bus bar, shunt between bus bars and shunt on the
edge with respect to the fill factor of the non-shunted cell
is shown in Fig. 12.
The variation in the efficiency for different spatial
locations in the cell has been found out and is shown in
Fig. 13. It depicts the effect of shunts on overall
efficiency of the solar cell for the edge shunt,shunt
between bus bars and the shunt under bus bar, with the
shunted area being same in each case.
Figure.10: Variation of % degradation of the cell Rsh
for shunt under the bus bar with respect to edge
shunt and shunt between bus bars.
Figure.11: Variation of Fill factor for edge shunt, shunt
between bus bars and shunt under bus bar with the
magnitude of resistance of shunt.
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Figure.12: Variation of % degradation in Fill factor for
the shunted cell due to shunt under bus bar,
edge shunt and shunt between bus bars.
Variation of percentage degradation in efficiency for
the shunt under bus bar, the shunt between bus bars and
shunt on the edge with respect to the efficiency of the
non-shunted cell are shown in Fig 14.
Figure.13: Variation of Efficiency for edge shunt, shunt
between bus bars and shunt under bus bar with the
magnitude of resistance.
B
Figure.14: Variation of % degradation in efficiency
for shunt under bus bar , edge shunt and shunt between
bus bars with respect to the non-shunted cell.
6 CONCLUSIONS
The numerical value of degradation in efficiency and
fill factor due to the presence of extended ohmic shunts
of varying magnitude at three significant locations in the
industrial silicon solar cell has been studied based on a
simple approach making use of DLIT images and PSpice
Simulations using the distributed diode model of the solar
cell.
The proposed approach is useful to study the effect of
different types and severity of shunts located at different
positions and to classify shunts in different categories
based on the level of tolerance and priority to solve the
severity of shunt problem during production.
7 ACKNOWLEDGEMENT
This work has been supported by a joint India-UK
initiative in solar energy through a joint project ‘Stability
and Performance of Photovoltaics (STAPP)’ funded by
Department of Science and Technology (DST) in India
and Research Councils UK (RCUK) Energy Programme
in UK (contract no: EP/H040331/1).
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