Transcript
7/28/2019 session 5 solar power
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By Manuel A. Silva Pérezsilva@esi.us.es
May 5, 2010
Concentrated Solar Thermal Power
Technnology Training
Session 5 – SOLAR RESOURCE
ASSESSMENT FOR CSP PLANTS
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SOLAR RESOURCE
ASSESSMENT FOR CSP PLANTS
Manuel A. Silva Pérez
Group of Thermodynamics and Renewable Energy
ETSI – University of Seville
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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
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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 WIrradiance: 6,35 x 107 W/m2
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0,0 0,5 1,0 1,5 2,0 2,5 3,0
0
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2500
0,0 0,5 1,0 1,5 2,0 2,5 3,0
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n I 0
(W·m-2 ·m-1)
(m)
Blackbody @ 5777 K
Extraterrestrial solar spectrumVisible
http://rredc.nrel.gov/solar/standards/am0/wehrli1985.new.html
UV IR
THE SUN AS A BLACKBODY
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Rayleigh
diffusion Mie diffusion
Beam
irradiance
Diffuse
irradiance
Albedo
irradiance
Beam
irradiance
INTERACTION BETWEEN SOLAR RADIATION AND THE
E ARTH’S ATMOSPHERE
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INTERACTION BETWEEN SOLAR RADIATION
AND THE E ARTH’S ATMOSPHERE
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Longitud de onda (micras)
W / m 2 · m
Extraterrestre
5777 K
In
Idh
IT
http://rredc.nrel.gov/solar/standards/am0/wehrli1985.new.html
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(Cloudless sky)
Absorption
%
8
100%
Air molecules
1
1 to 5
0.1 a 10
5 Dust, aerosols
Moisture0.5 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 E ARTH’S ATMOSPHERE
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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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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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SOLAR RADIATION CHARACTERISTICS
GEOGRAPHY
Cloudless sky: Solar radiation depends mainly on
latitude.
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SOLAR RADIATION CAHRACTERISITICS
R ANDOM COMPONENT
Solar radiation is modulated by meteorological
conditions – CLOUDS
Local climatic characteristics have to be taken into
account!
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Meteorological Station at the Seville Engineering School (since 1984)
Solar radiation measurement
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Hora Solar
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Hora Solar
W / m 2
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Hora Solar
W / m 2
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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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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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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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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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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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FILTER 5: VISUAL INSPECTION
0
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1200
1400
-8 -6 -4 -2 0 2 4 6 8
hora solar
i r r a d i a n c i a s W / m 2
IDmedida
ig
id
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TIME OFFSET
Incorrect time stamp
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Ig
horas sol
1orto
ocaso
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dmdt
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-8 -6 -4 -2 0 2 4 6 8
Ig
horas solIgcorregida
orto ocaso
22'1'
1
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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 globalhorizontal irradiation
Etc.
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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 ahorizontal 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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ESTIMATION OF DIRECT NORMAL IRRADIATION
FROM SUNSHINE DURATION
0
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-8 -6 -4 -2 0 2 4 6 8
hora solar / h
E b n
/ W · m - 2
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Decomposition models (estimation of beam and diffuse
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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
K d
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
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KD – KT MODELS
Modelos Kt-Kd diarios
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0.2
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0.6
0.8
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1.2
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Kt
K d
Collares Muneer Liu-Jordan GTER00-05 Ruth and Chant GTERD00-05
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SOLAR RADIATION ESTIMATION FROM
SATELLITE IMAGES
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SOLAR RADIATION ESTIMATION FROM
SATELLITE IMAGES
Energy balance
t a se0 E E I I
a se g E I I
A
I
0
1
1
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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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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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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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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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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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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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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/
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THE N ATIONAL SOLAR R ADIATION D ATABASE.
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 itsterritories. 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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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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SOLAR RESOURCE ASSESSMENT
FOR CSP PLANTS
1. Estimate the solar resource from readily availableinformation (expertise required!)
1 Surface measurements1 On site
2 Nearby
2 Satellite estimates
3 Sunshine hours
4 Qualitative information
2. Set up a measurement station1. Datalogger
2. Pyrheliometer
3. Pyranometer (global and diffuse)4. Meteo (wind, temperature, RH)
3. Maintain the station (frequent cleaning!)
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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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THANKS FOR YOUR ATTENTION!
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