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

0

0.2

0.4

0.6

0.8

1

1.2

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2001

2003

2005

2007

Co

mp

lete

%

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

3

3.5

4

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

info@greenpowerlabs.com

1 Research Drive

Dartmouth Nova Scotia Canada B2Y 4M9

1-902-466-6475