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\begin{document}

\title{Daylight photoluminescence imaging of photovoltaic systems using
inverter-based switching}



\author[1]{t trupke}%
\author[1]{Juergen W. Weber}%
\author[1]{Oliver Kunz}%
\author[2]{C. Knaack}%
\author[2]{D. Chung}%
\author[3]{A. Barson}%
\author[1]{A. Slade}%
\author[1]{Z. Ouyang}%
\author[1]{H. Gottlieb}%
\affil[1]{University of New South Wales School of Photovoltaic and Renewable Energy Engineering}%
\affil[2]{SMA Solar Technology AG}%
\affil[3]{Gentari / Wirsol}%


\vspace{-1em}



  
  \date{May 21, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Daylight photoluminescence imaging of crystalline silicon photovoltaic
modules is demonstrated for modules embedded in rooftop and
utility-scale systems, using inverters to electrically switch the
operating point of the array. The method enables rapid and high-quality
luminescence image acquisition during the day, unlocking efficient
performance and quality monitoring without the need to connect specific
electrical hardware or to make any modifications to the system wiring.
The principle of the measurement approach is discussed and experimental
results from a 10 kW \textsubscript{DC} residential rooftop system and
from a 149 MW \textsubscript{DC} utility-scale photovoltaic power plant
are presented. Measurements were performed using commercial inverters
without modifications to the inverter hardware or firmware. In the case
of the utility-scale power plant, the daylight photoluminescence image
acquisition of modules connected to a central inverter was obtained from
a remote piloted aircraft. Data analysis includes the conversion of
photoluminescence image data into implied voltage differences.%
\end{abstract}%



\sloppy


\textbf{Daylight photoluminescence imaging of photovoltaic systems using
inverter-based switching}

J.W. Weber, O. Kunz, C. Knaack\textsuperscript{1}, D.
Chung\textsuperscript{1}, A. Barson\textsuperscript{2}

A. Slade, Z. Ouyang, H. Gottlieb, T. Trupke\textsuperscript{*}

The University of New South Wales, Sydney, Australia

\textsuperscript{1} SMA Australia

\textsuperscript{2} Gentari / Wirsol Australia

\textsuperscript{*}E-mail address: t.trupke@unsw.edu.au

\section*{Abstract}

{\label{abstract}}

Daylight photoluminescence imaging of crystalline silicon photovoltaic
modules is demonstrated for modules embedded in rooftop and
utility-scale systems, using inverters to electrically switch the
operating point of the array. The method enables rapid and high-quality
luminescence image acquisition during the day, unlocking efficient
performance and quality monitoring without the need to connect specific
electrical hardware or to make any modifications to the system wiring.
The principle of the measurement approach is discussed and experimental
results from a 10 kW\textsubscript{DC} residential rooftop system and
from a 149 MW\textsubscript{DC} utility-scale photovoltaic power plant
are presented. Measurements were performed using commercial inverters
without modifications to the inverter hardware or firmware. In the case
of the utility-scale power plant, the daylight photoluminescence image
acquisition of modules connected to a central inverter was obtained from
a remote piloted aircraft. Data analysis includes the conversion of
photoluminescence image data into implied voltage differences.

\textbf{Keywords:} Photoluminescence imaging, crystalline silicon,
photovoltaics, solar modules

\section*{Background and Motivation}

{\label{background-and-motivation}}

There is a growing consensus that the exponential growth of the
cumulatively installed photovoltaic (PV) capacity will continue unabated
over coming decades. A large group of experts have forecast that
sustained 25\% compounding annual growth will result in
70-80~TW\textsubscript{DC} of installed PV capacity by 2050, to be
supported by 3-4~TW\textsubscript{DC} of annual module manufacturing and
module installations~. The global annual electricity consumption in 2022
was estimated by the International Energy Agency (IEA) to be 28,777~TWh.
For comparison, in the above scenario the electricity generated from PV
alone will reach an estimated 130,000~TWh per annum, thus exceeding
today's total worldwide annual electricity generation and consumption by
more than four times. Consequently, PV will rapidly become the main
source of global primary energy over coming decades.

PV modules based on single-junction crystalline silicon solar cells
dominate industrial manufacturing and commercial PV deployment today and
will remain the dominant technology for the foreseeable future, possibly
over coming decades~. Power production yield from PV power plants can be
affected by module quality and integrity in multiple ways. These include
manufacturing issues, damage occurring during transport and
installation, degradation during operation under harsh environmental
conditions and catastrophic weather events such as hailstorms, among
others. With industrial silicon modules now rapidly approaching their
theoretical efficiency limit, longevity and module quality are more
important than ever since re-powering of solar systems and early
retirement of PV modules are no longer economically viable options~. For
these reasons, systematic in-field testing and monitoring are of
increasing importance.

Electroluminescence (EL) and photoluminescence (PL) imaging~ emerged
around 2005 as powerful diagnostic tools for device and process
optimisation, process monitoring and quality testing. PL imaging is now
used routinely for PV research and development purposes, whereas EL
imaging has become an integral part of quality testing in high-volume
cell- and module manufacturing. A wealth of information about material
and device defects is contained in luminescence image data, making this
measurement principle an ideal candidate for field inspection of modules
in operating solar systems. Moreover, since specific information about
the presence of defects or degradation that is contained in luminescence
image data cannot be gleaned in any other fashion, we are of the firm
view that luminescence imaging must become an integral, potentially
dominant part of routine field testing, complemented by other inspection
methods such as thermal imaging~, visual inspection and performance data
analysis~.

Monochromatic or narrow-band light sources such as lasers or light
emitting diodes are commonly employed for laboratory PL imaging
applications. Alternatively, and only for outdoor applications during
daytime, the sun itself can be used as the excitation source in
so-called daylight PL imaging (DPL) applications. A significant
technical challenge for DPL imaging, however, is the separation of the
luminescence signal emitted by crystalline silicon solar cells from the
(typically orders of magnitude more intense) reflected sun light.

An elegant technical solution to this problem is based on PL image
acquisition within an ultra-narrow atmospheric spectral absorption band
in which incident sunlight is almost completely blocked by water vapor
absorption and which coincides spectrally with the room temperature
emission from crystalline silicon . Other solutions are based on a
lock-in type approach, whereby the emitted luminescence is modulated by
manipulating the electrical operating point of modules, for example
between open circuit (OC) and the maximum power point (MPP). The PL
image is obtained as the difference between two (or more) images, which
is the approach we also take in this study.

Different methods to achieve the required variation of a module's
electrical operating point have been demonstrated, including the
electrical connection of specialised switching electronics to the module
terminals, non-contact module-level optical modulation and non-contact
string-level optical modulation. A topical review of these methods was
presented in~.

Using the PV inverter as a means of rapidly switching between different
operating points offers an additional solution. Vukovic et al.
demonstrated DPL image acquisition during IV curve sweeps, which some
residential inverters commonly perform in certain intervals to determine
the global MPP~. However, the operating point of a PV string or array
can also be deliberately changed via the PV inverter, which allows the
acquisition of daylight PL images in a more controlled way~. Preliminary
results from a demonstration of controlled variation of the operating
point, achieved with a customised inverter, and performed on a small
test set-up, were recently presented by Koester et al.~.

Here, we demonstrate DPL image acquisition using controlled inverter
switching on operational PV systems and on a much larger scale, whereby
the operating points of all modules connected to an individual inverter
are actively manipulated. The method is demonstrated (i) on a 12
KW\textsubscript{DC} rooftop system located in Sydney, and (ii) on a
2.75 MW\textsubscript{DC} central inverter in a 149
MW\textsubscript{DC}Australian utility-scale solar farm. Both sets of
experiments were conducted using SMA inverters, without modifications to
the hardware or firmware. Actively controlling the inverter requires
knowledge about specific inverter settings and capabilities. Modulation
settings and associated safe operation limits as well as details of the
required communication protocols and access permissions were discussed
with the inverter manufacturer (SMA) prior to all experiments presented
here. This is a requirement for future experiments of this nature.
Photoluminescence image acquisition in the utility-scale solar farm was
achieved from a remote piloted aircraft (RPA), which we consider to be
the most practical and economical solution for rapid DPL inspection of
solar assets.

\section*{Experimental}

{\label{experimental}}

\subsection*{Rooftop system}

{\label{rooftop-system}}

The inverter-based switching method for DPL image acquisition was
demonstrated first on a
12~kW\textsubscript{DC}~/~10~kW\textsubscript{AC} residential rooftop
system at Wylie's Baths in the eastern suburbs of Sydney. The PV system
was commissioned in March 2021 and consists of 35 bifacial
350~W\textsubscript{p} glass-glass modules, each containing 120
half-cell PERC cells with a nominal open circuit voltage of 682~mV per
cell. The modules are arranged in two series-connected strings that are
connected to the DC inputs of a 10~kW SMA Sunnyboy Tripower inverter.
DPL measurements were performed on a sunny day in April 2023 using an
Indium Gallium Arsenide (InGaAs) camera with a resolution of 1280 x 1024
pixels in conjunction with near-infrared camera objectives with focal
lengths ranging from 12.5~mm to 50~mm. A 25~nm bandpass filter with a
centre wavelength of 1,137~nm was mounted in front of the camera lens
for all measurements to exploit a broad atmospheric absorption band that
coincides with the emission spectrum from crystalline silicon at room
temperature. The filter increases the relative proportion of the PL
signal in each individual image, as previously demonstrated and as
discussed in more detail elsewhere .\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

The
camera was mounted on a remote-controlled motorised pan and tilt head
that was attached to an aluminium pole serving as an improvised camera
mount. The pole caused significant camera shaking in the windy
conditions present during testing. An ethernet connection was used for
communication with the inverter to enable periodic switching of the
operating point of all modules in this PV system and setting of the
operating point to any value between MPP and OC conditions.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

A current clamp connected to a digital oscilloscope was used to monitor
the temporal variation of the electrical current into the DC inverter
inputs. Fig. 1 shows the normalised DC current flowing into one of the
inverter inputs during two different switching regimes, reflecting
relative power output from the system. In Fig.1(a) the current trace
reflects a two-step switching process, whereby the operating point of
the system is switched between MPP, at which 100\% of the available
power is extracted and OC, at which the DC current into the inverter and
the extracted power are zero. Note that under OC condition the cells
embedded in the modules emit maximum luminescence intensity, whereas at
MPP about 95\% of the photogenerated carriers are extracted, reducing
the luminescence intensity to close to zero. In Fig.1(b) the operating
point is periodically switched in three distinct steps, including an
interim step at which 40\% of the MPP current
(\emph{I\textsubscript{mpp}} ) is extracted from the module, resulting
in approximately 40\% of the maximum power being extracted. While not
the focus of this paper, the ability to switch between different
operating points enables calculation of image differences that allow
differentiating series resistance variations from recombination defects,
as demonstrated in the context of daylight PL imaging by Bhoopathy et
al. .

The switching of the power output from 100\% to zero takes place in
\textless{} 150~ms, but due to a long dwell time of about 1.5~s the
overall cycle time is about 3~s. This comparatively long cycle time was
chosen intentionally in our proof-of-concept studies reported here as a
conservative setting. We anticipate being able to perform switching at
considerably higher frequencies and with shorter switching times in the
near future, noting though that for residential rooftop applications, as
discussed here, the above switching rate is sufficient to enable rapid
high resolution DPL inspection of all modules of a system within a few
minutes.

Individual camera images were acquired with exposure times between 15~ms
and 20~ms. Image registration was applied to improve DPL image quality,
minimizing DPL image imperfections caused by very significant camera
shake. It is noted that camera shake does not notably affect the quality
of individual camera images, given the above short exposure times.
However, it results in lateral offsets between images, producing
artefacts when difference images are calculated. Image registration
prior to image subtraction eliminates this unwanted effect.

Fig.2 shows two PL images acquired using inverter-based switching on the
residential rooftop system at Wylie's Baths, as described above. From
the fixed camera position the 50mm focal length lens that was used for
these measurements provides close-up DPL images showing half a module to
one full module, depending on the specific module location on the roof
(i.e. distance to the camera). Each DPL image was calculated from 10
image pairs.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image9/image9}

\end{center}
\end{figure}

The DPL image shown in Fig. 2(a) shows a module half with 60 half-cells,
exhibiting significant PL intensity variations between half cells,
indicative of voltage variations and a strong indication of module
degradation. The image also clearly shows a several centimetre-long
microcrack (red circle), various point-like defects and the front bus
bars, demonstrating the excellent image quality that was achieved with
inverter-based DPL imaging.

Fig.2(b) shows a section of another module from the same rooftop system,
containing various examples of a defect that we have named the \emph{Yin
Yang} defect, and which we first reported recently . These defects
appear in pairs of half-cells, whereby the patterns match when one half
cell is de-rotated computationally. Tens of examples of this defect were
observed across different modules within the Wylie's Baths rooftop
system.

We observed the same defect during earlier field work, using the optical
string modulation technique in an Australian utility-scale solar farm,
where tens of thousands of glass-glass half-cell PERC modules exhibited
this defect after only approximately 1.5 years of operation in the
field. Importantly, the modules in that solar farm were from a different
brand compared to the residential system discussed above. Fig.3 shows a
DPL image from that earlier study of a module that exhibits several
examples of the Yin Yang defect. The assembly of half-cell modules in
mass production involves breaking a full cell into halves and rotating
one half-cell by 180 degrees prior to layup in the module. As shown in
Fig.3 (three examples are highlighted in the original image with white
squares), the computational de-rotation of one half-cell in each pair
results in perfect matching of the defect patterns, demonstrating that
the defect was already present in the full cell. DPL images of
non-fielded modules of the same module series did not show these
defects, the presence of the defects is thus a strong sign of module
degradation due to field exposure. We conclude that this defect is
present in the full cell as a latent defect that only becomes activated
by field exposure. Interestingly, we find that the luminescence
intensity from the higher-intensity regions within these defects is
comparable to that of modules from the same series that have not been
exposed to sunlight and which do not show these defects. This suggests
that the bright regions have degraded less strongly due to field
exposure, compared to the surrounding dark regions and that prevention
or mitigation of these defects could result in significant improvements
in system power output. The nature of the underlying degradation
mechanism is currently unclear and subject to ongoing investigations,
which are not the focus of this publication.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image13/image13}

\end{center}
\end{figure}

A significant practical benefit of inverter-based modulation is the
ability to take DPL images of all modules that are connected to the same
inverter, either sequentially and with high spatial resolution (close-up
imaging), as shown in Fig.2, or simultaneously in a single overview
image, with reduced spatial resolution. The larger field of view
required for an overview image can be achieved either by moving the
camera further away from the target or by using a camera objective lens
with a shorter focal length. Fig.4 shows a DPL image of the rooftop
system that was acquired with a 12.5mm focal length lens. The
acquisition of the full roof in a single DPL image could not be achieved
in this study, simply due to limitations with respect to the positioning
of the camera using our improvised camera mount (i.e. the camera could
not be moved further away). The image contains a few artefacts,
including the effect of optical reflections of surrounding trees that
were moving in the wind (green arrow in Fig.4). Note that reflections of
stationary objects do not cause such artefacts, since they cancel out in
the image difference calculation. We also observe an artefact associated
with the shadow cast by the (shaking) mounting pole and the camera (blue
arrow). The latter effect causes the top third of one module to appear
darker. The shading effects by the camera can be avoided by more careful
placement of the camera, in particular, when images are acquired using
an RPA (as demonstrated in the following section). Artefacts associated
with objects such as plants, buildings or other architectural features
are generally not a concern for large utility-scale systems and may be
avoidable in applications on residential PV systems with careful
planning and timing of experiments.

\subsection*{Utility-scale System}

{\label{utility-scale-system}}

Utility-scale inverter-based DPL imaging was demonstrated at a
149~MW\textsubscript{DC} solar farm in Australia in October 2023. The
farm became fully operational in March 2021, utilising 400~W monofacial
half-cell modules on single-axis trackers. The modules feature PERC
solar cells with a nominal open-circuit voltage of 690mV per cell
according to the module specifications. The farm uses 2.75~MW SMA
central inverters (Sunny Central 2750-EV), with approximately 9,000
modules connected to each inverter. For the proof of concept of
large-scale DPL image acquisition using inverter-based modulation
reported here, only one 2.75~MW inverter was switched. As a precaution,
only \textless{}60\% of the inverter's rated DC power was switched at
any time (e.g. between 90\% and 30\% of maximum power) to avoid
potential risks of thermal cycling on the power electronics. DPL image
acquisition was achieved using the same InGaAs camera (1280 x 1024 pixel
resolution) that was used for the data acquired on the rooftop section
discussed above. The camera was mounted on a customised DJI M600
hexacopter RPA, the latter running custom image acquisition software on
an on-board computer. A Gremsy gimbal was used to stabilise the camera,
enabling image acquisition with up to 50~ms exposure time for the
individual image without significant loss of image sharpness due to
camera shake. Images were acquired using a 50~mm focal length objective
lens equipped with the same bandpass filter described above.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image15/image15}

\end{center}
\end{figure}

Fig.5 shows a DPL image of a large section of the solar farm, containing
approximately 1,200 PV modules in one single image. Only modules located
in the bottom half of this image are connected to the inverter that was
switched, i.e. only half of the modules yield a PL image, the other half
appearing dark in the difference image, as expected. Further, the image
includes a grassy area to the right of the PV array, which also appears
dark. The image was calculated from 20 individual near-infrared camera
images. We observe an average PL signal count in the section containing
the switched modules of 290 counts, whereas the count rate in both the
grassy area and the non-switched section is below 10 counts. Four
modules in the image stand out in red. They exhibit considerably lower
PL counts compared to all other modules in that section of the solar
farm. The PL intensity from these modules is approximately 53\% compared
to the surrounding modules.

Quantitative analysis of luminescence intensities from solar cells is
based on the Generalised Planck Equation~, predicting an exponential
relationship between the emitted luminescence intensity and the diode
voltage of the device. In simplified form that relationship can be
written as

\(I_{\text{PL}}=Ce^{\left(\frac{\text{qV}}{\text{kT}}\right)\ }\)(1)

where \emph{I\textsubscript{PL}} is the emitted luminescence
intensity,\emph{k} is Boltzmann's constant, \emph{q} is the elementary
charge,\emph{T} is the sample temperature and \emph{V} is the diode
voltage. The so-called thermal voltage kT/q has a value of about 25.85
mV at room temperature. The calibration constant \emph{C} in Eq.1
depends on various sample specific geometric and optical sample
parameters, on the spectral sensitivity of the detection system and on
various measurement parameters. The accuracy of obtaining implied
voltages from luminescence signals is therefore linked to the ability to
accurately determine the constant \emph{C} . By contrast, it follows
from Eq.1 that the ratio of two luminescence signals,
\emph{I\textsubscript{PL,1}} and\emph{I\textsubscript{PL,2}}
respectively, can be converted into a voltage difference \selectlanguage{greek}\emph{ΔV}\selectlanguage{english} via

\(V=\frac{\text{kT}}{q}\ln\frac{I_{PL,1}}{I_{PL,2}}\). (2)

provided that the calibration constant \emph{C} can be assumed to be the
same for the two luminescence measurements. That is the case if
measurements are conducted with the same measurement system (as is the
case here) and with identical measurement parameters (as is also the
case here) and either on the same sample at different times or under
different bias conditions or on different samples which can be assumed
to have similar optical properties.

Eq. 2 predicts 16.5 mV lower voltage per cell for the four modules that
appear in Fig.5 with 53\% lower PL counts. During our experiments we
noted some variation in optical properties between modules in this solar
farm in the near infrared spectral range that is defined by the bandpass
filter mounted on the camera lens. A detailed quantitative analysis of
DPL results obtained from this solar farm, including the expected minor
impact of these optical variations is currently underway and will be
reported elsewhere, noting however that the focus of this publication is
the demonstration of the inverter-based DPL image acquisition principle.
We would like to emphasise, that the quantitative analysis of DPL image
variations between cells or modules of the same type in terms of voltage
variations according to Eq.2 is well established. For validation
purposes we performed separate experiments on modules at a UNSW outdoor
test system. These measurements confirmed that the accuracy of implied
voltage differences between modules from PL images is on the order of
+/-~2~mV per cell when PL image data is compared to measured terminal
voltages under well controlled experimental conditions.

The DPL image example in Fig.5 demonstrates, for the first time, the
ability to simultaneously acquire PL images of very large numbers of PV
modules, in similar fashion to what is currently common practice with
RPA-based thermal infrared imaging. RPA-based camera deployment enables
not only the acquisition of images of large sections of the farm from a
high vantage point, but also convenient and rapid change of the camera
field of view by variation of the distance to the target. For the
experiments discussed above positioning of the RPA prior to image
acquisition was achieved with manual RPA flight control. For the near
future we envisage automated mapping of solar farms with pre-programmed
flight paths and way points, as is current practice for thermal
inspection. In this scenario we envisage the use of high-level overview
PL imaging data captured from RPAs, as shown in Fig.5, in combination
with either close-up RPA-based imaging or high-fidelity imaging from the
ground. This will enable rapid overview images to be acquired first,
followed by more detailed inspection of specific modules or farm
sections with suspected defects.

\subsection*{Discussion}

{\label{discussion}}

The ability to acquire outdoor DPL images of entire PV systems or of
large sections of solar farms using inverter-based modulation is a very
significant step towards cost effective and commercially viable daylight
luminescence imaging of large utility scale solar systems. The analysis
of relative PL intensities is a particularly powerful quantitative tool
to assess voltage variations between and within modules, and to quantify
module degradation. Of particular importance in this context is the
robustness of PL image data against variations in sample temperature.
Zafirovska et al.~ showed that the temperature coefficient of implied
voltages that are derived from luminescence is about ten times lower
than the temperature coefficient of the terminal voltage. This is
particularly relevant here since measuring temperatures on PV modules in
the field with good accuracy is generally difficult to achieve. While
such accurate temperature measurements are a key requirement for the
analysis of terminal voltage measurements of fielded modules, it is not
required for quantitative PL image analysis due to the low temperature
sensitivity of the PL signal.

The inverter-based manipulation of the operating point of large numbers
of modules that are connected to specific inverters in combination with
RPA-based image acquisition is an elegant solution to inspect large
solar assets, and to find faulty modules or determine module
degradation. No modifications to the system wiring are required, it can
be performed during the day and does not require large and heavy
equipment such as power supplies and generators to be brought on site.
Daylight PL imaging also avoids additional hazards (electrical,
night-work) and administrative difficulties associated with working at
nighttime.

\subsection*{Summary and Conclusions}

{\label{summary-and-conclusions}}

High quality daylight photoluminescence image acquisition of crystalline
silicon solar modules in both rooftop and utility-scale solar farms
using electrical modulation of the operating point of modules connected
to an inverter was demonstrated. Measurements were performed by
manipulating the operating point of modules using existing functionality
of commercial inverters, without specific customisation of either
hardware or firmware, without any modifications to the PV system's
electrical wiring and without utilising additional large power
electronic equipment, such as generators and power supplies.
Importantly, measurements were performed in daylight during regular
working hours, avoiding the administrative and practical complications
and risks associated with nighttime operation.

It was shown that close-up high-resolution and high-quality images of
individual modules enable the detection of microcracks and individual
cell level defects. In contrast, RPA based overview images of large
sections of farms, with up to 1,200 modules contained in a single PL
image, as demonstrated here, allow the detection of coarse cell, module,
and system-level defects. Quantitative analysis enables accurate
assessment of voltage variations within and between modules. The work
presented in this paper is a significant step towards commercially
viable, fast and effective daylight photoluminescence imaging becoming a
routine part of large-scale PV plant inspection.

\section*{Acknowledgment}

{\label{acknowledgment}}

The authors express their sincere gratitude to the management of Wylie's
Baths in Coogee for permitting DPL image acquisition, to Wirtgen Invest,
owner of the Glenrowan West solar farm for their support, in particular
their permission to perform experiments on their premises and Gentari /
Wirsol Australia staff, particularly Purnaansh Gunaicha, Matthew Smith
and Roshan Dharmasena, for outstanding administrative and technical
support during the field work. This work was supported by the Australian
Government through the Australian Renewable Energy Agency {[}ARENA;
Project 2022/TRAC013{]}. The views expressed herein are not necessarily
the views of the Australian Government, and the Australian Government
does not accept responsibility for any information or advice contained
herein.

\section*{Conflict of interest}

{\label{conflict-of-interest}}

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to
influence the work reported in this paper.

\selectlanguage{english}
\FloatBarrier
\end{document}

