1. Solar resource monitoring and
forecasting using satellite data
Green Power Labs Inc.
And
Applied Geomatics Research Group

2. Presentation contents:
• Satellite data and solar climatology
• Rationale for using geostationary satellites
for monitoring solar radiation
• Example of satellite mapping technology
applied in Atlantic Canada (logic,
sequence of steps, groundtruthing)
• GPLI developed software (SolarSatData)
• Next Steps and Commercial applications

3. NASA Satellite-based solar climatology
NASA Surface meteorology and Solar
Energy dataset
Data period: the monthly average amount of the total solar radiation incident on a
horizontal surface at the surface of the earth for a given month will be averaged for that
month over the 22-year period (1983 - 2005). World Climate Research Program and
International Satellite Cloud Climatology Project.

4. Long term Satellite climatology
and landscape
High resolution map created for an international solar power producer based
on long-term satellite based climatology and landscape analysis. With easy
to use GIS tools, our client was able to quickly and easily locate five prime
sites for a PV plant. The plant is now under construction.

5. Motivation for using satellite data
•Interest to satellite 1.2
data is triggered by
lack of observations 1
•Environment Canada
0.8
operated only 2
Complete%
stations 0.6
•Halifax Citadel and
Kentville 0.4
Citadel
•No new data since Kentville
0.2
2002
0
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2001
2003
2005
2007
UP: Solar data collection intensity by
Environment Canada In the Province of
Nova Scotia 1970 till present.
LEFT: GOES satellite coverage.

6. Geostationary satellites
•Positioned at an exact height above the
Earth
•Rotate around the Earth at the same speed
as the earth rotates around its axis, so
remain stationary above a point on the Earth
•Can view the whole Earth disk below them
•Can scan the same area very frequently
•They are many (e.g. Meteosat, GOES-
EAST, GOES-WEST, GMS, IODC, GOMS)

7. Solar climatology from satellites
•Lack of spatially and
temporally continuous data
•25 km interpolation bottleneck
•Cano et al. (1986) describe a
method for the determination
of the global solar radiation
from meteorological satellite
data.
•Perez et al. (2003) calculate
satellite-derived irradiances for
R. Perez: “80,000 radiometers
models that use the visible
covering US at 10 km grid would
satellite channel as main input
not achieve an accuracy better
for cloud index determination.
than 13% for points located
•Avoid satellite data calibration
between stations”
•A small number of high
accuracy ground stations are
needed for satellite model
ground truth and real time
calibration

8. Project objectives
• Use GOES-East visible spectrum images (1 km
nadir resolution)
• Develop methodology for solar modeling
• Develop mathematical algorithms
• Test results against a number of field stations
• Design software to function within GIS
• Test on a large dataset
• Create maps for Atlantic Canada

9. Northern portion
of GOES East
image (above the
equator) and …
Maritime Canada
study area

10. The process
Clear sky model
Dynamic range
Brightest
Hour of day observed
Darkest
High resolution data
1x1 km, 30 min
Ghi
Hour of day

11. GOES image being analyzed
Prince Edward
New Brunswick
Island
Julian Day 85 (March 26) 2007 at 15:15 UTC

12. Minimum pixel brightness
25 day window around Day 85

13. Maximum pixel brightness
25 day window around Day 85

14. Global Insolation for the analyzed image
Calculated for 15:15 UTC on Day 85 (25 day window)

15. Solar radiation for the studied day 85
Wh/m2
2750
750
Calculated for all daylight hours of Day 85 (25 day window)

16. Daily Solar Radiation averaged for a month
Each of these results represent the
combination of approximately 744
GOES images
(~24 images/day x 31 days/month)
Wh/m2
3100
2200
Calculated for all daylight hours in March 2007 (25 day window)

17. Resulting Satellite-based radiation Maps
High-resolution satellite-
based solar resource
maps for Nova Scotia
(Canada)
Shows spatial pattern
and temporal variability

19. Groundtruthing
Calculated Irradiance values have been compared to solar radiation
measurements collected by the AGRG’s meteorological stations. The
stations are measuring a set of meteorological parameters (i.e., air
temperature, relative humidity, wind speed/direction, barometric pressure,
solar radiation, rainfall, soil temperature, and soil moisture).
14 Station locations are shown on a colorized hillshade of the Annapolis Valley.
Validation results for the Stations circled in red will be shown on following slides.

20. Groundtruthing
The SP LITE sensor
measures the solar energy
received from the entire
hemisphere. It is ideal for
measuring available energy
for use in solar energy
applications, plant growth,
thermal convection and
evapotranspiration.

21. Comparison of modelled and observed
irradiance.
R2 = 0.94
R2 = 0.81
RMSE <15%
Observations taken at meteorological stations in the Annapolis Valley, Canada

22. 5
Linke Turbidity 4.5
4
3.5
Optical thickness of the
Linke turbidity
Halifax
3
atmosphere due to the absorption Kejimkujik
2.5
Sable Island
by the water vapor and the 2 Howland
absorption by the aerosol particles. 1.5
1
It summarizes the attenuation of
0.5
the direct beam solar radiation. 0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Important for CSP Month
Insolation
LT=3
LT=6

23. Effect of snow masking algorithm
Snow
Normal processing
Insolation
Snow processing
January 2007

24. Modeled hourly values of solar radiation
compared to observed at meteorological
stations in the Annapolis Valley for Julian
Day 85, 2007
The meteorological stations shown here are
Stations 10, 30, and 70 – three stations
across the Annapolis Valley transect

25. Methodology is applicable to any areas with
satellite coverage

26. Solar Mapping Toolset for ArcGIS:
Managing and Processing GOES
Satellite Data
GPLI developed a toolset for automated
download , clipping and processing of
GOES images into maps of solar
radiation in ArcGIS 9.2

27. ArcGIS plugins
This toolset functions as a plugin for ArcGIS 9.2

28. The Next Steps:
Solar System Performance Monitoring
• Site specific detailed
information on available
solar resource collected
every 30 minutes
• Close monitoring of
solar technologies to
maintain performance
and maximize energy
output
• Effective management Point and area monitoring
of heating and cooling
cycles based on micro
climate data

29. The Next Steps:
Forecasting Solar Resource
Effective energy
management strategies
require forecasting of
energy output from solar
technologies.
Energy traders
Utilities
Power Producers
Building Owners

30. Thank you!
Contact Information:
www.greenpowerlabs.com
info@greenpowerlabs.com
1 Research Drive
Dartmouth Nova Scotia Canada B2Y 4M9
1-902-466-6475