Copyright © 2014 Clean Power Research, L.L.C
v040714
Satellite Irradiance Models and
Datasets
Adam Kankiewicz
Solar Resour...
Agenda
 The Evolution of Solar Irradiance Modeling and
Datasets
 Satellite-based Irradiance Modeling
 TMY Data Consider...
Agenda
 The Evolution of Solar Irradiance Modeling and
Datasets
 Satellite-based Irradiance Modeling
 TMY Data Consider...
“It’s main objective is to
provide data for computerized
calculations regarding energy
conservation, energy
consumption in...
 Year long file of hourly (“8760”) weather data pulled
from a bank of longer historical data coverage
 Meant to typify a...
 Typical GHI Year (TGY)
 Same concept as TMY but with weighting based solely
on GHI
What is TGY?
Individual year
TGY
Mon...
The Evolution of Irradiance Modeling
ModelMethodologyDataset
METSTAT
Typical GHI
Year
(TGY)
TMY2
Satellite-based
SUNY
Sate...
Modeling Surface Irradiance Data
METSTAT
(Meteorological
Statistical)
Satellite-based
Primary difference is how clouds
are...
Agenda
 The Evolution of Solar Irradiance Modeling and
Datasets
 Satellite-based Irradiance Modeling
 TMY Data Consider...
Radiative Transfer Model
(quasi-physical)
+
Cloud Modulation
(largely empirical)
Satellite Model Components
© Perez & Hoff
Radiative Transfer Model
AOD
Precipitable water
Ozone
Altitude
0.1
0.2
0.3
0.4
W
O3
H
Model Sensitivities
Radiative Transfer Model
(quasi-physical)
+
Cloud Modulation
(largely empirical)
What GOES into a Satellite Model?
Copyright © 2014 Clean Power Research, L.L.C
v040714
Cloud Modulation
© Perez & Hoff
Copyright © 2014 Clean Power Research, L.L.C
v040714
Cloudindex
© Perez & Hoff
Cloud Modulation
DARK (clear) WHITE (cloudy)
© Perez & Hoff
DNI Extrapolation with DIRINDEX
DARK (clear) WHITE (cloudy)
© Perez & Hoff
Specular Reflectivity Must Be Accounted for
Presence of
snow detected
on the ground
© Perez & Hoff
Snow Must Be Accounted for
DARK (clear) WHITE (cloudy)
Visible Channel
IR Channel Combination
© Perez & Hoff
Fort Peck, MT
Visible + IR: Better Snow Discrimination
Visible Model
© Perez & Hoff
Satellite(W/m2)
Ground (W/m2)
Visible ...
Visible + IR: Better Snow Discrimination
February 2011
Visible Model Visible + IR Model
© Perez & Hoff
Satellite Model Error Characteristics
2010-2012 Observations
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
GHI
Visible Model Vis...
Agenda
 The Evolution of Solar Irradiance Modeling and
Datasets
 Satellite-based Irradiance Modeling
 TMY Data Consider...
TMY3 Data Locations (All Classes)
Not All TMY3 Locations Are Created Equal
% of
Sites
Uncertainty # of Years Sampled
(Generally)
Class I 16% Lowest 24 years...
TMY3 Data Locations (Class Differences)
Minneapolis/St. Paul Example
TMY3_Minneapolis-St. Paul Int.
Airport (Class I)
TMY3...
TMY3 Data Locations (Class Differences)
Minneapolis/St. Paul Example
* Annual output of a 5 kW system
MonthlyAveGHI(W/m2)
...
TMY3 Data Locations (Class I)
TMY3 (Class I) and Satellite-based Data
Hanford, CA
Error as a Function of Distance
Ground(W/m2)
Satellite (W/m2)
Agenda
 The Evolution of Solar Irradiance Modeling and
Datasets
 Satellite-based Irradiance Modeling
 TMY Data Consider...
Which Dataset Should I Use?
Use Cases
TMY/
TGY
Ground Satellite
Initial Estimates 
Siting & Financing of
Utility Scale PV...
© Clean Power Research
More than One Flavor of Satellite Data
 Spatial Resolution
 Temporal Resolution
 Length of Cover...
Copyright © 2014 Clean Power Research, L.L.C
v040714
Thank you
Skip Dise
SolarAnywhere Prod. Manager
johndise@cleanpower.c...
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2014 PV Performance Modeling Workshop: Satellite Irradiance Models and Datasets: Adam Kankiewicz, Clean Power Research

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2014 PV Performance Modeling Workshop: Satellite Irradiance Models and Datasets: Adam Kankiewicz, Clean Power Research

  1. 1. Copyright © 2014 Clean Power Research, L.L.C v040714 Satellite Irradiance Models and Datasets Adam Kankiewicz Solar Resource Specialist 2014 PV Sandia Performance Modeling Workshop May 5, 2014
  2. 2. Agenda  The Evolution of Solar Irradiance Modeling and Datasets  Satellite-based Irradiance Modeling  TMY Data Considerations  Which Data Should I Use?
  3. 3. Agenda  The Evolution of Solar Irradiance Modeling and Datasets  Satellite-based Irradiance Modeling  TMY Data Considerations  Which Data Should I Use?
  4. 4. “It’s main objective is to provide data for computerized calculations regarding energy conservation, energy consumption in buildings and indoor climate.” The Origins of TMY
  5. 5.  Year long file of hourly (“8760”) weather data pulled from a bank of longer historical data coverage  Meant to typify average weather conditions at a location (P50)  TMY data are consistent at the monthly level  Current NREL NSRDB TMY2 and TMY3 weighting scheme: GHI: 25% DNI: 25% Met data (T, Td, WS): 50% What is TMY?
  6. 6.  Typical GHI Year (TGY)  Same concept as TMY but with weighting based solely on GHI What is TGY? Individual year TGY MonthlyAveGHI(W/m2)
  7. 7. The Evolution of Irradiance Modeling ModelMethodologyDataset METSTAT Typical GHI Year (TGY) TMY2 Satellite-based SUNY Satellite TMY3 TGY Typical Meteorogical Year (TMY) 1970’s 2014 Updated Satellite
  8. 8. Modeling Surface Irradiance Data METSTAT (Meteorological Statistical) Satellite-based Primary difference is how clouds are observed and handled! Weather data plus ground-based cloud observations Weather data plus satellite-based cloud observations
  9. 9. Agenda  The Evolution of Solar Irradiance Modeling and Datasets  Satellite-based Irradiance Modeling  TMY Data Considerations  Which Data Should I Use?
  10. 10. Radiative Transfer Model (quasi-physical) + Cloud Modulation (largely empirical) Satellite Model Components
  11. 11. © Perez & Hoff Radiative Transfer Model
  12. 12. AOD Precipitable water Ozone Altitude 0.1 0.2 0.3 0.4 W O3 H Model Sensitivities
  13. 13. Radiative Transfer Model (quasi-physical) + Cloud Modulation (largely empirical) What GOES into a Satellite Model?
  14. 14. Copyright © 2014 Clean Power Research, L.L.C v040714 Cloud Modulation © Perez & Hoff
  15. 15. Copyright © 2014 Clean Power Research, L.L.C v040714 Cloudindex © Perez & Hoff Cloud Modulation DARK (clear) WHITE (cloudy)
  16. 16. © Perez & Hoff DNI Extrapolation with DIRINDEX DARK (clear) WHITE (cloudy)
  17. 17. © Perez & Hoff Specular Reflectivity Must Be Accounted for
  18. 18. Presence of snow detected on the ground © Perez & Hoff Snow Must Be Accounted for DARK (clear) WHITE (cloudy)
  19. 19. Visible Channel IR Channel Combination © Perez & Hoff
  20. 20. Fort Peck, MT Visible + IR: Better Snow Discrimination Visible Model © Perez & Hoff Satellite(W/m2) Ground (W/m2) Visible + IR Model Satellite(W/m2) Ground (W/m2)
  21. 21. Visible + IR: Better Snow Discrimination February 2011 Visible Model Visible + IR Model © Perez & Hoff
  22. 22. Satellite Model Error Characteristics 2010-2012 Observations 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% GHI Visible Model Visible + IR © Perez & Hoff RelativeAnnualMAE(%)
  23. 23. Agenda  The Evolution of Solar Irradiance Modeling and Datasets  Satellite-based Irradiance Modeling  TMY Data Considerations  Which Data Should I Use?
  24. 24. TMY3 Data Locations (All Classes)
  25. 25. Not All TMY3 Locations Are Created Equal % of Sites Uncertainty # of Years Sampled (Generally) Class I 16% Lowest 24 years Class II 43% Higher 12 years Class III 41% Highest 12 years + missing data Only 40 sites have measured solar data (<2%) Pre-1998 = METSTAT modeled 1998-2005 years = Satellite modeled
  26. 26. TMY3 Data Locations (Class Differences) Minneapolis/St. Paul Example TMY3_Minneapolis-St. Paul Int. Airport (Class I) TMY3_St. Paul downtown Airport (Class II) TMY3_Minneapolis/Crystal (Class II) Annual Ave GHI (W/m2)
  27. 27. TMY3 Data Locations (Class Differences) Minneapolis/St. Paul Example * Annual output of a 5 kW system MonthlyAveGHI(W/m2) TMY3 Minneapolis/Crystal Class II 5,545 kWh* -15% TMY3 St. Paul Downtown Airport Class II 5,907 kWh* -9% TMY3 Minneapolis/St. Paul Airport Class I 6,491 kWh* Base SolarAnywhere Satellite
  28. 28. TMY3 Data Locations (Class I)
  29. 29. TMY3 (Class I) and Satellite-based Data
  30. 30. Hanford, CA Error as a Function of Distance Ground(W/m2) Satellite (W/m2)
  31. 31. Agenda  The Evolution of Solar Irradiance Modeling and Datasets  Satellite-based Irradiance Modeling  TMY Data Considerations  Which Data Should I Use?
  32. 32. Which Dataset Should I Use? Use Cases TMY/ TGY Ground Satellite Initial Estimates  Siting & Financing of Utility Scale PV Systems   Production Guarantees for DG Lease Funds  Real-time Monitoring  
  33. 33. © Clean Power Research More than One Flavor of Satellite Data  Spatial Resolution  Temporal Resolution  Length of Coverage  Time-frame  Tuned/Not-Tuned  Ancillary Weather Data Clear Sky 0 4:00 12:00 20:00 Ground Satellite 60 min. Data Satellite 30 min. data Satellite 1 min. Data
  34. 34. Copyright © 2014 Clean Power Research, L.L.C v040714 Thank you Skip Dise SolarAnywhere Prod. Manager johndise@cleanpower.com Please feel free to contact us for any details or clarification related to presentation Adam Kankiewicz SolarAnywhere Research Spec. adamk@cleanpower.com Mark McKahan-Jones Senior Account Executive mmj@cleanpower.com

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