Concentrated Solar Power Course - Session 5 - Solar Resource Assessment

By Manuel A. Silva Pé[email protected]

May 5, 2010

Concentrated Solar Thermal PowerTechnnology Training

Session 5 – SOLAR RESOURCE ASSESSMENT FOR CSP PLANTS

http://www.leonardo-energy.org/csp-training-course-5-lessons

SOLAR RESOURCE ASSESSMENT FOR CSP PLANTS

Manuel A. Silva PérezGroup of Thermodynamics and Renewable EnergyETSI – University of Seville

http://www.leonardo-energy.org/csp-training-course-lesson-5-assessing-solar-resource-csp-plants



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




UNDERSTANDING THE SOLAR RESOURCE

FOR CSP PLANTS

The Sun as an energy source

Mass:1,99

x 1030 kgDiameter:

1,392 x 109 mArea:

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




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

nI 0

(W·m-2 ·m-1)

(m)

Blackbody @ 5777 KExtraterrestrial solar spectrum

Visible

http://rredc.nrel.gov/solar/standards/am0/wehrli1985.new.html

UV IR

THE SUN AS A BLACKBODY




Rayleighdiffusion Mie diffusion

Beam irradiance

Diffuse irradiance

Albedo irradiance

Beam irradiance

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

m

Extraterrestre

5777 K

In

Idh

IT

http://rredc.nrel.gov/solar/standards/am0/wehrli1985.new.htmlhttp://www.leonardo-energy.org/csp-training-course-lesson-5-assessing-solar-resource-csp-plants



(Cloudless sky)

Absorption%

8

100%

Air molecules1

1 to 5

0.1 a 10

5Dust, aerosols

Moisture 0.5 to 10

2 to 10

Diffuse%

Reflection to space %

Beam

83% to 56%11% to 23% 5% a 15%





SOLAR RADIATION CHARACTERISTICSCYCLES

Daily Day – night Modulation of solar radiation

during the day

Seasonal Modulation of solar radiation

during the year




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




SOLAR RADIATION CHARACTERISTICS GEOGRAPHY

Cloudless sky: Solar radiation depends mainly on latitude.




SOLAR RADIATION CAHRACTERISITICS RANDOM COMPONENT

Solar radiation is modulated by meteorological conditions – CLOUDS

Local climatic characteristics have to be taken into account!




Meteorological Station at the Seville Engineering School (since 1984)

Solar radiation measurement

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 SolarW

/m2

Global irradiance

Diffuse irradiance

Beam irradiance

Solar radiation measurement

Sunshine duration

Campbell – Stokes heliograph

Pyranometer

Shaded Pyranometer

Pyrheliometerhttp://www.leonardo-energy.org/csp-training-course-lesson-5-assessing-solar-resource-csp-plants



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




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




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)


http://rredc.nrel.gov/solar/pubs/qc_tnd/



QUALITY CONTROL OF SOLAR RADIATION DATA

Physically Possible Limits Extremely Rare Limits Comparisons vs other measurements Comparisons vs model Visual inspection




FILTER 5: VISUAL INSPECTION

0

200

400

600

800

1000

1200

1400

-8 -6 -4 -2 0 2 4 6 8

hora solar

irra

dia

nci

as W

/m2

IDmedida

ig

id




TIME OFFSET

Incorrect time stamp

0

100

200

300

400

500

600

700

800

900

-8 -6 -4 -2 0 2 4 6 8

Ig

horas sol

t1torto

tocaso

t2

dmdt

0

100

200

300

400

500

600

700

800

900

-8 -6 -4 -2 0 2 4 6 8

Ig

horas sol

Igcorregida

torto tocaso

t2t2't1'

t1




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.http://www.leonardo-energy.org/csp-training-course-lesson-5-assessing-solar-resource-csp-plants



ESTIMATION OF DAILY OR MONTHLY GLOBAL HORIZONTAL IRRADIATION FROM SUNSHINE DURATION

Angstrom – type formulasH/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




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

Eb

n /

W·m

-2




Daily or hourly global horizontal irradiation values

0.00.20.40.60.81.0

0 0.2 0.4 0.6 0.8 1Kt

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

KD – KT MODELS

Modelos Kt-Kd diarios

0

0.2

0.4

0.6

0.8

1

1.2

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Kt

Kd

Collares Muneer Liu-Jordan GTER00-05 Ruth and Chant GTERD00-05




SOLAR RADIATION ESTIMATION FROM SATELLITE IMAGES




SOLAR RADIATION ESTIMATION FROM SATELLITE IMAGES

Energy balance

tase0 EEII

aseg EIIA

I

011




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 http://www.leonardo-energy.org/csp-training-course-lesso

n-5-assessing-solar-resource-csp-plants



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.




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.




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.





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.





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.




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/

http://www.helioclim.net/index.html

http://www.soda-is.com/eng/index.html

http://www.helioclim.net/esra/

http://re.jrc.cec.eu.int/pvgis/pv/

http://www.solemi.de/home.html

http://rredc.nrel.gov/solar/old_data/nsrdb/1991-2005/tmy3

http://eosweb.larc.nasa.gov/sse/

http://www.meteotest.ch/en/mn_home?w=ber




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.




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?)





1. Estimate the solar resource from readily available information (expertise required!)

1 Surface measurements1 On site2 Nearby

2 Satellite estimates3 Sunshine hours4 Qualitative information

2. Set up a measurement station 1. Datalogger2. Pyrheliometer3. Pyranometer (global and diffuse) 4. Meteo (wind, temperature, RH)

3. Maintain the station (frequent cleaning!)





5. Perfom quality control of measured data6. 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




THANKS FOR YOUR ATTENTION!




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Concentrated Solar Power Course - Session 5 - Solar Resource Assessment

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