This document discusses using satellite data to generate time series of spectrally resolved solar irradiance data for analyzing the impact of the solar spectrum on photovoltaic module performance. It describes the PVKLIMA project which uses a combination of atmospheric models, satellite imagery, and radiative transfer calculations to estimate spectral irradiance worldwide. Methods for speeding up the calculations and accounting for effects like clouds, aerosols, and module tilt angle are discussed. Future work includes further validation and expanding the method to additional geostationary satellites.

1. Betcke, Hammer, PVPMM Workshop, 22. October 2015, Cologne 11
PVKLIMA
Timeseries of Spectrally Resolved Irradiance Data
from Satellite Measurements
Jethro Betcke, Annette Hammer,
PV Performance Modelling and Monitoring Workshop
22nd
October 2015, Cologne

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Content
• Why focus on spectrally resolved irradiance?
• PVKLIMA project
• Spectrally resolved irradiance from satellite data
• New developments
• Summary and outlook
• References and Funding

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Variations in spectrum
Measurements: TÜV Rheinland
Wavelength (nm) Wavelength (nm)
NormalizedIrradiance
NormalizedIrradiance

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Spectrally weighted irradiance
Normalized spectral
irradiance
E(λ) Spectral irradiance
Global irradiance
SR(λ) Spectral sensitivity of
PV module
n(λ)=E(λ)/G

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Error in Gw
when using AM 1.5 instead of measured spectrum
• → don't neglect spectral effect!
Stuttgart,
south oriented
tilted plane,
one year of data
Spectral measurements:
Bastian Zinßer
IPE Stuttgart

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Seasonal effect
Spectral effect is site specific (→ presentation of Markus Schweiger)

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PVKLIMA - Energy Yield of Thin Film Photovoltaic
Modules under the Influence of different Climate Impacts
• Worldwide meteorological reference dataset to asses
efficiency of modules under realistic working conditions
• Here: Characterizing and rating the impact of the solar
spectrum on the energy yield of thin film PV modules
• (other impacts: temperature, soiling...)

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PVKLIMA - Energy Yield from Thin Film Photovoltaic
Modules under the Influence of different Climate Impacts
• Worldwide meteorological reference dataset to asses
efficiency of modules under realistic working conditions
• Here: Characterizing and rating the impact of the solar
spectrum on the energy yield of thin film PV modules
• Only possible when using satellite data!

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Spectrally resolved iradiance data from
satellite measurements
H2
O, O3
, CO2
absorptionAerosols:
Scattering and
absorption
Clouds:
Scattering and absorption
ground
reflection
www.clipartpanda.com

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Modelling the Spectrum
• Atmospheric composition:
– Global MACC Dataset of European weather service ECMWF
•combination of ground measurements, satellite measurements
and Numerical Weather Models
•Time resolution: 6 hours
• Cloud information:
– Heliosat method and geostationary satellite imagery
• Saving computing time:
– SOLIS: Parametrization of radiative transfer calculations

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Spectral irradiance with SOLIS

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Spectral irradiance with SOLIS

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Kato bands for faster computationNormalizedIrradiance
Wavelength (nm)

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Speed up computation time with SOLIS parametrization
slow
radiation transport
calculation with
libRadtran
atmospheric composition
solar elevation
spectrally resolved
irradiance for two
solar elevations
Fit mit
„Modified Lambert Bar“
Funktion
MLB-Parameter
fit
„Modified Lambert Beer“
function
fast
„Modified Lambert Beer“
function
Solar elevation
Global irradiance:
libRadtran supporting point
MLB Function
libRadtran
Direct irradiance:
libRadtran supporting point
MLB Function
libRadtran
spectrally resolved
irradiance
Two calculations for a given
atmospheric composition
(Solar elevations 30° and 90°)
As often as wanted Example: Irradiance at 530 nm
SZA=90°-Sonnenhöhe (°)
Based on
Mueller et al 2002,
EUMETSAT Conf.
x
+
Einstrahlung(mW/m2
)

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How often do we need to calculate?
• spectral clear sky irradiance solely depends on solar
elevation, if atmospheric state does not significantly change.
→ two radiative transport calculations are sufficient
• For which period can we suppose invariant atmospheric
conditions?
• Preliminary study: approximately 10 days.

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Spectral irradiance with SOLIS

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Heliosat method
Bild: EUMETSAT
reflectivity ρ
of given image
one month of
images VIS
cloud index n:
measure of clouds
clear sky index k*:
transmission through
clouds
ground albedo
ρground
n=
ρ−ρground
ρcloud−ρground
0≤n≤1
k =
G
Gclearsky
= 1−n
*
for each pixel:
search for
cloud free
scene
Meteosat Second Generation:
spatial resolution: up to 1x1 km
temporal resolution: 15 minutes

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Spectral irradiance with SOLIS

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Quality of method
PCA_SPEC: simple empirical method, clear sky index and solar elevation are only input

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PVKLIMA results and
future stepsFrequency of
calculation
(preliminary study
done)
Parametrization
of Aerosol optical
thickness
(publication in
preparation)
broken clouds
Develop
tilt conversion for
spectral irradiance
(in progress)
Application on
Meteosat East
GOES
validation starts now

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PVKLIMA results and
future stepsFrequency of
calculation
(preliminary study
done)
Parametrization
of Aerosol optical
thickness
(publication in
preparation)
broken clouds
Develop
tilt conversion for
spectral irradiance
(in progress)
Application to
Meteosat East
GOES
validation starts now

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Tilt conversion
• Angle-resolved spectral irradiance can be
determined with radiative transport calculations
(computational intensive)
• -> simple model of hemisphere,
similar to Perez or Klucher model
and parametrization per Kato band.
• Spectral data for validation:
–Measurement of tilted spectral irradiance
at the five PVKLIMA/TÜV Rheinland sites
–Simultaneous measurements of
horizontal and tilted spectral irradiance
at University of Oldenburg
(RAMSES spectrometer, spring 2015)
Source: Perez et al., Solar Energy 39, 1987

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Summary and Outlook
• Spectral impact on PV-yield can be analyzed with site
specific timeseries of spectral irradiance
• for areas this information can be obtained with a combination
of models, MACC and satellite data.
• The method is already available, further optimizations will be
developed within PVKLIMA

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References
• LibRadtran:
–Mayer, B., and Kylling, A., 2005. Technical note: The libRadtran software package for radiative transfer
calculations-description and examples of use. Atmospheric Chemistry and Physics 5, 1855–1877.
• SOLIS:
–Mueller, R.W., Dagestad, K.F., Ineichen, P., Schroedter-Homscheidt, M., Cros, S., Dumortier, D., Kuhlemann,
R., Olseth, J.A., Piernavieja, G., Reise, C., Wald, L., Heinemann, D., 2004. Rethinking satellite-based solar
irradiance modelling: The SOLIS clear-sky module. Remote Sensing of Environment 91, 160 – 174.
doi:http://dx.doi.org/10.1016/j.rse.2004.02.009
• Tilt conversion of diffuse irradiance:
–Klucher, T.M., 1979. Evaluation of models to predict insolation on tilted surfaces. Solar Energy 23, 111–114.
–Perez, R., Seals, R., Ineichen, P., Stewart, R., Menicucci, D., 1987. A new simplified version of the Perez diffuse
irradiance model for tilted surfaces. Solar energy 39, 221–231.
• Spectral irradiance from satellite data:
–Betcke, J., Behrendt, T., Kühnert, J., Hammer, A., Lorenz, E., Heinemann, D., 2010. Spectrally resolved solar
irradiance derived from meteosat cloud information - Comparison of two methods, in: Proceedings of the 2010
EUMETSAT Meteorological Satellite Conference. Cordoba, Spain.
–Mueller, R., Behrendt, T., Hammer, A., Kemper, A., 2012. A New Algorithm for the Satellite-Based Retrieval of
Solar Surface Irradiance in Spectral Bands. Remote Sensing 4, 622–647. doi:10.3390/rs4030622
Behrendt, T., Kuehnert, J., Hammer, A., Lorenz, E., Betcke, J., Heinemann, D., 2013. Solar spectral irradiance
derived from satellite data: A tool to improve thin film PV performance estimations? Solar Energy 98, 100–110.
doi:10.1016/j.solener.2013.05.011

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Acknowledgements
• The project PVKLIMA is funded by the German Federal
Ministry for the Environment, Nature Conservation, Building
and Nuclear Safety (BMU) following an order by the German
Federal Parliament (BMU FKZ 0325517B). The content of
the presentation is the sole responsibility of the authors