©3E | | www.3E.eu

EVALUATION OF SATELLITE

IRRADIATION DATA AT 200 SITES IN

WESTERN EUROPE

22 October 2015 Karel De Brabandere | Karel.DeBrabandere@3E.eu

3E in a nutshell

2

• Founded in 1999

• 120 experts, 18

nationalities

• Projects in over 30

countries, 5

continents

• Offices in (a.o.)

• Brussels

• Toulouse

• Cape Town

• London

Need for accurate irradiation data

3

Long term yield assessment

Long term average

Yearly variation

Performance evaluation

Yearly reference yield

Monthly reference yield

Fault detection

Daily reference yield

Hourly reference yield

Need for accurate irradiation data

4

On-site Irradiance sensors can have excellent accuracy

But in reality:

• Sensor type

• Dome / Flat

• Si / Thermopile

• Soiling

• Shading

• Orientation

• Degradation

• Availability

• … Regular validation of sensors is a necessity!

Satellite irradiation data

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Meteosat-8/9/10 (MSG) satellite imagery

• SEVIRI instrument

• Coverage: Europe, Africa

• Temporal resolution: 15 min

• Nadir spatial resolution: 3 x 3 km²

• Start: January 2004

Satellite irradiation data

6

Services evaluated

• macc-rad (SoDa)

• HelioClim-3 v3, v4, v5 (SoDa)

• cpp (KNMI)

• gsip (NOAA)

‘Empirical’ models

• Image Cloud mask Irradiance

• macc-rad and HelioClim-3

‘Physical’ models

• Image Cloud properties Irradiance

• cpp and gsip

Are the (rather new) physical models better than the empirical models?

Satellite irradiation data

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Data evaluated

• Global horizontal irradiation

• Hourly / Daily / Monthly aggregated

• 2011 - 2015

Evaluation at 203 sites in Western Europe

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Pyranometer data from national meteo stations

France: 160 MétéoFrance stations

Belgium: 12 RMI (KMI / IRM) stations

• Daily aggregated global horizontal irradiation

• 2012 - 2013

Netherlands: 31 KNMI stations

• Hourly global horizontal irradiation

• 2011 - 2015

Evaluation metrics

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• Root Mean Square Error

(RMSE)

• Standard Deviation of Error

(SDE)

• Bias

RMSE [%]

𝑅𝑀𝑆𝐸2 = 𝑆𝐷𝐸2 + 𝐵𝑖𝑎𝑠2

Daily data

Monthly data

Individual site 𝐸 𝑥 = 𝑥2

𝑁

Evaluation: 2012

10

Macc-rad: high bias

Hc3: improvement

with every version

Cpp: Best in class

Evaluation: 2013

11

Macc-rad: high bias

Hc3: improvement

with every version

Cpp: Best in class

Very similar results for

2013

Evaluation: Netherlands 2011

12

Why focus on

Netherlands?

• Consistent high

quality of meteo

• Almost no horizon

shading

• Almost no snow

• Hourly

• Long history up till

yesterday

• Free & verifiable

Hourly Data

Evaluation: Netherlands 2012

13

Why focus on

Netherlands?

• Consistent high

quality

• No horizon

shading

• Almost no snow

• Hourly

• Long history

• Free & verifiable

Evaluation: Netherlands 2013

14

Why focus on

Netherlands?

• Consistent high

quality

• No horizon

shading

• Almost no snow

• Hourly

• Long history

• Free & verifiable

Evaluation: Netherlands 2014

15

Why focus on

Netherlands?

• Consistent high

quality

• No horizon

shading

• Almost no snow

• Hourly

• Long history

• Free & verifiable

Evaluation: Netherlands 2014 April – 2015 Feb

16

NOAA gsip

• Data from March

2014 onwards

Evaluation on 11

months!

Hourly, daily:

rather poor accuracy

Monthly:

good accuracy

Potential for improvement?

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Average Bias

• MACC-RAD ~10%

• HC3v3 ~2.5%

• Other 0 - 2%

• Mostly positive

Bias correction!

Average bias of standard deviation

• Minor systematic deviations

MOS correction Average Bias ≠ RMS Bias !!!

Potential for improvement?

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Daily Bias pattern

(Bias grouped by

‘hour of day’)

• Systematic

patterns for all

databases

• Huge impact on

Plane-of-Array

irradiation!

More advanced

MOS correction

Potential for improvement?

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Basic MOS correction

of:

• Bias

• Bias of SD

𝑌 = 𝑏 ∙ 𝑋𝑝

Only 2 parameters

• Factor 𝑏

• Exponent 𝑝

Potential for improvement?

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Macc-rad:

• Huge reduction of

Bias

• Smaller reductions

in SDE

Small, but significant

improvements for

HC3v3 and cpp

• monthly RMSE

cpp: 4% 3%

Conclusions

3E Profile: Full Scope Consultancy & Software Services in Sustainable Energy 21

Fault detection (hourly, daily)

sensor, satellite if no sensor present

Follow-up on plant performance (monthly, yearly)

good satellite or validated sensor

Expected yield (design)

very good sensor or good satellite

Sensor validation

good satellite

Data web service in development for processed cpp data: www.3E.eu/datacentre

Acknowledgements

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SoDa macc-rad, HelioClim3: http://www.soda-pro.com/

KNMI msg-cpp: http://msgcpp.knmi.nl/

NOAA gsip: http://www.class.ncdc.noaa.gov/

KNMI hourly data: http://knmi.nl/nederland-nu/klimatologie/uurgegevens

RMI: http://www.meteo.be/

Météo-France: http://www.meteofrance.com/

3E provides:

• cpp data for performance analysis

• Sensor validation

• Data web service at www.3E.eu/datacentre (soon)

www.3E.eu

Thank you

23

Brussels

Toulouse

Gent

Louvain-La-Neuve

Beijing

Istanbul

Cape Town

London

Milano

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