Solar resource monitoring and
forecasting using satellite data
Green Power Labs Inc.
And
Applied Geomatics Research Group
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
NASA Satellite-based solar climatology
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.
NASA Surface meteorology and Solar
Energy dataset
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.
Long term Satellite climatology
and landscape
Motivation for using satellite data
•Interest to satellite
data is triggered by
lack of observations
•Environment Canada
operated only 2
stations
•Halifax Citadel and
Kentville
•No new data since
2002
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Citadel
Kentville
UP: Solar data collection intensity by
Environment Canada In the Province of
Nova Scotia 1970 till present.
LEFT: GOES satellite coverage.
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)
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 models that use the visible satellite channel as main input for cloud index determination.
•Avoid satellite data calibration•A small number of high accuracy ground stations are needed for satellite model ground truth and real time calibration
R. Perez: “80,000 radiometers
covering US at 10 km grid would
not achieve an accuracy better
than 13% for points located
between stations”
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
Northern portion
of GOES East
image (above the
equator) and …
Maritime Canada
study area
The process
Dynamic range
Darkest
Brightest
observedHour of day
Clear sky model
Hour of day
Ghi
High resolution data
1x1 km, 30 min
Julian Day 85 (March 26) 2007 at 15:15 UTC
New BrunswickPrince Edward
Island
GOES image being analyzed
25 day window around Day 85
Minimum pixel brightness
25 day window around Day 85
Maximum pixel brightness
Calculated for 15:15 UTC on Day 85 (25 day window)
Global Insolation for the analyzed image
Calculated for all daylight hours of Day 85 (25 day window)
Solar radiation for the studied day 85
2750
750
Wh/m2
Calculated for all daylight hours in March 2007 (25 day window)
Daily Solar Radiation averaged for a month
3100
2200
Wh/m2
Each of these results represent the
combination of approximately 744
GOES images
(~24 images/day x 31 days/month)
Resulting Satellite-based radiation Maps
High-resolution satellite-
based solar resource
maps for Nova Scotia
(Canada)
Shows spatial pattern
and temporal variability
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.
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.
Groundtruthing
R2 = 0.81
Comparison of modelled and observed
irradiance.
Observations taken at meteorological stations in the Annapolis Valley, Canada
R2 = 0.94
RMSE <15%
Linke Turbidity
LT=6 LT=3
0
0.5
1
1.5
2
2.5
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3.5
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4.5
5
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
Lin
ke t
urb
idit
y
Halifax
Kejimkujik
Sable Island
Howland
Optical thickness of the
atmosphere due to the absorption
by the water vapor and the
absorption by the aerosol particles.
It summarizes the attenuation of
the direct beam solar radiation.
Important for CSP
Insolation
Normal processing
Snow processing
Insolation
Effect of snow masking algorithm
January 2007
Snow
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
Methodology is applicable to any areas with
satellite coverage
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
ArcGIS plugins
This toolset functions as a plugin for ArcGIS 9.2
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
of heating and cooling
cycles based on micro
climate data
Point and area monitoring
Effective energy management strategies require forecasting of energy output from solar technologies.
Energy traders
Utilities
Power Producers
Building Owners
The Next Steps:
Forecasting Solar Resource
Thank you!
Contact Information:
www.greenpowerlabs.com
1 Research Drive
Dartmouth Nova Scotia Canada B2Y 4M9
1-902-466-6475