In this session there will be a complete review of technologies and techniques to assess the solar resource of a site and its suitability for a CSP project.
- Understanding the solar resource for csp plants
- Solar radiation measurement and estimation
- Solar radiation databases
- Statistical characterisation of the solar resource. Typical meteorological years
- Solar resource assessment for csp plants
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Concentrated Solar Power Course - Session 5 - Solar Resource Assessment
1. By Manuel A. Silva Pérez
silva@esi.us.es
May 5, 2010
Concentrated Solar Thermal Power
Technnology Training
Session 5 – SOLAR RESOURCE
ASSESSMENT FOR CSP PLANTS
http://www.leonardo-energy.org/csp-training-course-5-lessons
2. SOLAR RESOURCE
ASSESSMENT FOR CSP PLANTS
Manuel A. Silva Pérez
Group of Thermodynamics and Renewable Energy
ETSI – University of Seville
http://www.leonardo-energy.org/csp-training-course-
lesson-5-assessing-solar-resource-csp-plants
3. CONTENTS
Understanding the solar resource for CSP plants
Solar radiation measurement and estimation
Solar radiation databases
Statistical characterization of the solar resource.
Typical meteorological years
Solar resource assessment for CSP plants
http://www.leonardo-energy.org/csp-training-course-
lesson-5-assessing-solar-resource-csp-plants
4. UNDERSTANDING THE SOLAR RESOURCE
FOR CSP PLANTS
The Sun as an energy source
Mass: 1,99 x 1030 kg
Diameter: 1,392 x 109 m
Area: 6,087 x 1018 m2
Volume: 1,412 x 1027 m3
Average density: 1,41 x 103 kg/m3
Angular diameter: 31’ 59,3’’
Average distance to earth: 1,496 x 1011 m = 1 AU
Equivalent Temperature: 5777 K
Power: 3,86 x 1026 W
Irradiance: 6,35 x 107 W/m2
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lesson-5-assessing-solar-resource-csp-plants
5. 0,0 0,5 1,0 1,5 2,0 2,5 3,0
0
500
1000
1500
2000
2500
0,0 0,5 1,0 1,5 2,0 2,5 3,0
0
500
1000
1500
2000
2500
nI0
(W·m-2 ·m-1)
(m)
Blackbody @ 5777 K
Extraterrestrial solar spectrum
Visible
http://rredc.nrel.gov/solar/standards/am0/wehrli1985.new.html
UV IR
THE SUN AS A BLACKBODY
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lesson-5-assessing-solar-resource-csp-plants
7. INTERACTION BETWEEN SOLAR RADIATION
AND THE EARTH’S ATMOSPHERE
0
500
1000
1500
2000
0,3 1,3 2,3 3,3
Longitud de onda (micras)
W/m
2
·m
Extraterrestre
5777 K
In
Idh
IT
http://rredc.nrel.gov/solar/standards/am0/wehrli1985.new.html
http://www.leonardo-energy.org/csp-training-course-
lesson-5-assessing-solar-resource-csp-plants
8. (Cloudless sky)
Absorption
%
8
100%
Air molecules
1
1 to 5
0.1 a 10
5
Dust, aerosols
Moisture
0.5 to 10
2 to 10
Diffuse
%
Reflection
to space %
Beam
83% to 56%
11% to 23% 5% a 15%
INTERACTION BETWEEN SOLAR RADIATION
AND THE EARTH’S ATMOSPHERE
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lesson-5-assessing-solar-resource-csp-plants
9. SOLAR RADIATION CHARACTERISTICS
CYCLES
Daily
Day – night
Modulation of solar radiation
during the day
Seasonal
Modulation of solar radiation
during the year
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lesson-5-assessing-solar-resource-csp-plants
10. SOLAR RADIATION CHARACTERISTICS
LOW DENSITY
Maximum value < 1367 W/m2
Large areas required for solar energy applications
Concentration increases energy power density.
Only the direct (beam) component can be concentrated
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lesson-5-assessing-solar-resource-csp-plants
11. SOLAR RADIATION CHARACTERISTICS
GEOGRAPHY
Cloudless sky: Solar radiation depends mainly on
latitude.
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lesson-5-assessing-solar-resource-csp-plants
12. SOLAR RADIATION CAHRACTERISITICS
RANDOM COMPONENT
Solar radiation is modulated by meteorological
conditions – CLOUDS
Local climatic characteristics have to be taken into
account!
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lesson-5-assessing-solar-resource-csp-plants
14. 0 4 8 12 16 20 24
Hora Solar
0
200
400
600
800
1000
0 4 8 12 16 20 24
Hora Solar
W/m
2
0
200
400
600
800
1000
0 4 8 12 16 20 24
Hora Solar
W/m
2
0
200
400
600
800
1000
0 4 8 12 16 20 24
Hora Solar
W/m
2
Global irradiance
Diffuse irradiance
Beam irradiance
Solar radiation measurement
Sunshine duration
Campbell – Stokes heliograph
Pyranometer
Shaded Pyranometer
Pyrheliometer
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lesson-5-assessing-solar-resource-csp-plants
15. Measurement of Solar Radiation
Broad-band global solar irradiance: Pyranometer
Diffuse radiation is measured with a pyranometer and a shading device (disc,
shadow ring, or band) that excludes direct solar radiation
Response decreases approximately as the cosine of the angle of incidence.
Measures energy incident on a flat surface, usually horizontal
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lesson-5-assessing-solar-resource-csp-plants
16. Easy to model
Sensitive to attenuation
It is the main component under
clear sky
Measurement
Precise calibration (absolute –
cavity- radiometer)
Requires continuous tracking
5.7 º
Eppley Labs pyrheliometer (NIP) & tracker
DIRECT NORMAL (BEAM) IRRADIANCE MEASUREMENT
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lesson-5-assessing-solar-resource-csp-plants
17. QUALITY CONTROL OF SOLAR RADIATION DATA
Different procedures, all based on data filtering by:
Comparison with physical constraints, other
measurements, models.
Visual inspection by experienced staff
An example follows (see also
http://rredc.nrel.gov/solar/pubs/qc_tnd/ for a
different, more exhaustive procedure)
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lesson-5-assessing-solar-resource-csp-plants
18. QUALITY CONTROL OF SOLAR RADIATION DATA
Physically Possible Limits
Extremely Rare Limits
Comparisons vs other measurements
Comparisons vs model
Visual inspection
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lesson-5-assessing-solar-resource-csp-plants
19. FILTER 5: VISUAL INSPECTION
0
200
400
600
800
1000
1200
1400
-8 -6 -4 -2 0 2 4 6 8
hora solar
irradianciasW/m2
IDmedida
ig
id
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lesson-5-assessing-solar-resource-csp-plants
21. CLASSICAL ESTIMATION OF
SOLAR RADIATION
Models depend on the variable to estimate and on
the available data and their characteristics:
Estimation of daily or monthly global horizontal or
direct normal irradiation from sunshine duration
Estimation of hourly values from daily values of
global horizontal irradiation
Estimation of global irradiation on tilted surfaces
Estimation of the beam component from global
horizontal irradiation
Etc.
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lesson-5-assessing-solar-resource-csp-plants
22. ESTIMATION OF DAILY OR MONTHLY GLOBAL
HORIZONTAL IRRADIATION FROM SUNSHINE
DURATION
Angstrom – type formulas
H/H0 = a + b (s/s0)
Where
H is the monthly average daily global irradiation on a
horizontal surface
H0 is the monthly average daily extraterrestrial
irradiation on a horizontal surface
s is the monthly average daily number of hours of bright
sunshine,
s0 is the monthly average daily maximum number of
hours f possible sunshine
a and b are regression constants
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lesson-5-assessing-solar-resource-csp-plants
23. ESTIMATION OF DIRECT NORMAL IRRADIATION
FROM SUNSHINE DURATION
0
100
200
300
400
500
600
700
800
900
1000
-8 -6 -4 -2 0 2 4 6 8
hora solar / h
Ebn/W·m-2
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lesson-5-assessing-solar-resource-csp-plants
24. Daily or hourly global horizontal
irradiation values
0.0
0.2
0.4
0.6
0.8
1.0
0 0.2 0.4 0.6 0.8 1
Kt
Kd
Daily or hourly Diffuse
values
Hb,0 = Hg,0 - Hg,0
Decomposition models (estimation of beam and diffuse
components from global horizontal)
KT = Kd =
Hg,0
Ho
Hd,0
Hg,0
26. SOLAR RADIATION ESTIMATION FROM
SATELLITE IMAGES
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lesson-5-assessing-solar-resource-csp-plants
27. SOLAR RADIATION ESTIMATION FROM
SATELLITE IMAGES
Energy balance
tase0 EEII
aseg EII
A
I
0
1
1
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lesson-5-assessing-solar-resource-csp-plants
28. THE SATELLITE
METEOROLOGICAL SATELLITES
In meteorology studies frequent and high density
observations on the Earth's surface are required.
Conventional systems do not provide a global
cover.
An important tool to analyse the distribution of the
climatic system are the METEOROLOGICAL
SATELLITES. These can be:
Polar
Geostationary: In Europe, the system o geostationary
meteorological satellites is METEOSAT
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lesson-5-assessing-solar-resource-csp-plants
29. METHODOLOGY
ADVANTAGES
The geostationary satellites show simultaneously
wide areas.
The information of these satellites is always
referred to the same window.
It is possible to analyse past climate using satellite
images of previous years.
The utilisation of the same detector to evaluate the
radiation in different places.
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lesson-5-assessing-solar-resource-csp-plants
30. METHODOLOGY
DISADVANTAGES
The range of the brilliance values of cloud cover
(90-255) and of the soils (30-100) overlap.
The digital conversion results in imprecision for low
values of brilliance.
The image information is related to an instant, while
the radiation data is estimated in a hourly or daily
period.
The spectral response of the detector is not in the
same range of that of conventional pyranometers.
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lesson-5-assessing-solar-resource-csp-plants
31. METHODOLOGY
PHYSICAL AND STATISTICAL MODELS
The purpose of all models is the estimation of the
solar global irradiation on every pixel of the image.
The existing models are classified in: physical and
statistical depending of the nature of the apporach
to evaluate the interaction between the solar
radiation and the atmosphere.
Both types of models show similar error ranges.
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lesson-5-assessing-solar-resource-csp-plants
32. METHODOLOGY
PHYSICAL AND STATISTICAL MODELS
STATISTICAL MODELS
Based on relationships (usually statistical regressions) between
pyranometric data and the digital count of the satellite.
This relation is used to calculate the global radiation from the digital
count of the satellite.
Simple and easy to apply.
They do not need meteorological measurements.
The main limitations are:
The needed of ground data.
The lack of universality.
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lesson-5-assessing-solar-resource-csp-plants
33. METHODOLOGY
PHYSICAL AND STATISTICAL MODELS
PHYSICAL MODELS
Based on the physics of the atmosphere. They consider:
The absorption and scatter coefficients of the atmospheric
components.
The albedo of the clouds and their absorption coefficients.
The ground albedo.
Physical models do not need ground data and are universal models.
Need atmospheric measurements.
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lesson-5-assessing-solar-resource-csp-plants
34. DATA BASES AND TOOLS
EUROPE
HELIOCLIM1 Y HELIOCLIM.
http://www.helioclim.net/index.html
http://www.soda-is.com/eng/index.html
ESRA (European Solar Radiation Atlas).
http://www.helioclim.net/esra/
PVGIS (Photovoltaic Gis)
http://re.jrc.cec.eu.int/pvgis/pv/
SOLEMI (Solar Energy Mining)
http://www.solemi.de/home.html
USA
National Solar Radiation Database
http://rredc.nrel.gov/solar/old_data/nsrdb/1991-2005/tmy3
NASA
http://eosweb.larc.nasa.gov/sse/
WORLD
METEONORM.
http://www.meteotest.ch/en/mn_home?w=ber
WRDC (World Radiation Data Centre)
http://wrdc-mgo.nrel.gov/
36. THE NATIONAL SOLAR RADIATION DATABASE.
TMY3
The TMY3s are data sets of hourly values of solar radiation
and meteorological elements for a 1-year period. Their
intended use is for computer simulations of solar energy
conversion systems and building systems to facilitate
performance comparisons of different system types,
configurations, and locations in the United States and its
territories. Because they represent typical rather than extreme
conditions, they are not suited for designing systems to meet
the worst-case conditions occurring at a location.
rredc.nrel.gov/solar/old_data/nsrdb/1991-2005/tmy3.
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lesson-5-assessing-solar-resource-csp-plants
37. STATISTICAL CHARACTERIZATION OF THE
SOLAR RESOURCE
The statistical characterization of solar radiation
requires long series of MEASURED data
Sunshine hours – good availability
Global horizontal (GH) – good availability
Direct Normal (DNI) – poor availability
The statistical distribution of solar radiation
depends on the aggregation periods
Monthly and yearly values of global irradiation have
normal distribution
The distribution of yearly values of DNI is not normal
(Weibul?)
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lesson-5-assessing-solar-resource-csp-plants
38. SOLAR RESOURCE ASSESSMENT
FOR CSP PLANTS
1. Estimate the solar resource from readily available
information (expertise required!)
1 Surface measurements
1 On site
2 Nearby
2 Satellite estimates
3 Sunshine hours
4 Qualitative information
2. Set up a measurement station
1. Datalogger
2. Pyrheliometer
3. Pyranometer (global and diffuse)
4. Meteo (wind, temperature, RH)
3. Maintain the station (frequent cleaning!)
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lesson-5-assessing-solar-resource-csp-plants
39. SOLAR RESOURCE ASSESSMENT
FOR CSP PLANTS
5. Perfom quality control of measured data
6. Compare estimates with measurements and
assess solar resource (DNI, Global)
After 1 year of on-site measurements
1 year is not significant:
long term estimates should prevail
Analysis must be made by experts
7. Elaborate design year(s) from measured data
Time series -1 year- of hourly or n-minute values
Typical
P50
Pxx
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40. THANKS FOR YOUR ATTENTION!
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