Spectral solar irradiance models and data sets

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  • Solar Cells, 18 (1986) 223-232 223

    SPECTRAL SOLAR IRRADIANCE MODELS AND DATA SETS*

    C. J. RIORDAN

    Solar Energy Research Institute, 1617 Cole Boulevard, Golden, CO 80401 (U.S.A.)

    (Accepted July 3, 1985)

    1. Introduction

    The spectral distribution of solar irradiance at the earth's surface varies with the elevation of the sun above the horizon and atmospheric conditions. This variation is important to photovoltaic (PV) applications because PV devices are spectrally selective (Fig. 1). Therefore, data on the spectral distribution of irradiance throughout the day and year for different climates are required to predict the field performance of PV devices and to design devices for optimum energy conversion efficiency at specific locations. This paper reviews the nature of spectral irradiance variations and their impact on PV device performance, the models and data sets used to characterize spectral irradiance variations, and issues related to the specification of spectral irradiance conditions for PV device performance analyses.

    0.8

    l i

    == o, t g == ~ ]

    o! 0.2 o.4 0.6 0.8 1.o 1.2

    Wavelength (pm)

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    "~ 0.6

    E "q 0.4- C

    o 0.2-

    1.4 1.6 0.2 0.4 0.6

    ! I

    11 '\\

    0.8 1.0 1.2 1.4

    Wavelength (p,m)

    Fig. 1. Examples of spectral response and quantum efficiency of several different PV device materials, a, CdTe/CdS; o, Si high efficiency; A, Si; -}-, GaAs; , CuInSe2/CdZnS high efficiency.

    *Paper presented at the SERI Photovoltaics and Insolation Measurements Workshop, Vail, CO, U.S.A., June 30 - July 3, 1985.

    0379-6787/86/$3.50 Elsevier Sequoia/Printed in The Netherlands

  • 224

    2500 -

    2000 t

    E1500

    '~" 1000 J 8

    ~s00-

    01 0.0 110 2.0 r T ~ I 3.0 4.0 Wavelength (pm)

    Fig. 2. Spectral distribution of extraterrestrial irradiance (from C. FrShlich and C. Wehrli, World Radiation Center, Davos, Switzerland, 1981). The integral under the spectral irradiance curve is called the solar "constant" which varies around 1370 W m -2.

    A P

    E v

    o r.. (u

    L . .

    1800

    1500

    1200

    900

    600

    300

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    I ~ H (SUN)

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    v ~:~,~iii'~ "~ , 0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 2.1 2.3

    Wavelength (~m) Fig. 3. Global spectral irradiance with atmospheric absorption features indicated.

  • 225

    1._ Extraterrestrial irradiance Atmosphere %~ Aerosols }

    " \ ~ Water vapor f \ " Ozone Spectral absorption

    ( \ Clouds and scattering ~, ~ (etc.) of solar radiation

    E a ~ / / / / / / / / / / / / / / / J / / / / Diffuse Direct

    irradiance beam irradiance

    Global irradiance Fig. 4. Transmittance of solar irradiance through the earth's atmosphere, which functions as a temporally and spatially variable filter.

    2. The nature of spectral solar irradiance and its relationship to PV device performance

    The spectral distribution of solar irradiance outside the earth's atmo- sphere, called extraterrestrial irradiance, is shown in Fig. 2. This distribution is modified by wavelength-dependent scattering and absorption within the atmosphere. Some of the major absorbers that determine the structure of spectra at the earth's surface are identified in Fig. 3. The atmosphere acts as a spatially and temporally variable filter (Fig. 4), with the major variables being clouds, aerosols and water vapor. Irradiance that is transmitted (not scattered or absorbed) directly to the earth's surface is direct beam irrad- lance, and that which is scattered out of the direct beam but reaches the surface is diffuse irradiance. PV collectors are designed to utilize either direct or global (direct plus diffuse) irradiance (Fig. 5). These components have different spectral distributions; therefore they are characterized separately.

    The amount of scattering and absorption of solar irradiance in the atmosphere and the impact on spectral solar irradiance distribution depends on atmospheric constituents and the path length of irradiance through the atmosphere (air mass). Air mass depends on the angle of the sun from the vertical (zenith) position (or the elevation above the horizon) and decreases from sunrise and sunset to solar noon (Fig. 6). Some examples of the impact of changes in air mass, aerosol amount (turbidity) and water vapor amount on direct normal and global spectral solar irradiance distributions and the

  • 226

    Zenith

    Horizontal , i

    Zenith

    Horizontal

    Zenith ~'-,~

    ,

    "r ~,'~~ Horizontal

    4

    Concentrators utilize direct normal Irradlance

    Tracking flat plates utilize direct normal plus diffuse Irradiance (global normal irradiance)

    Fixed-tilt flat plates utilize direct beam Irradiance projected* onto the surlace plus diffuse irradiance (global-tilt Irradlance) * Direct normal X cos ( incidence angle)

    Fig. 5. Solar irradiance uti l ized by various types of PV collectors. Flat-plate col lectors that are not hor izontal also receive solar irradiance that is ref lected f rom the ground onto the col lector surface.

    Solar noon ~ Zenith

    , , 1 Air mass 1.0 _(/q_" co I

    " , ( / /~ ~.4ir , ~ . ~ ~ ~ ~ --'At m os p h e re

    Sunrise/ Earth sunset

    Fig. 6. Air mass is the path length of the solar beam through the atmosphere, which depends on the angle of the sun f rom the vertical.

    total (integrated) solar irradiance axe shown in Fig. 7. These are modeled results using a simple spectral solar irradiance model for cloudless skies [1]. In each plot, two parameters are held constant at mid-range values and one is varied. Increasing air mass results in lower total irradiance and a shift toward longer wavelengths due to greater scattering of the shorter wavelengths. This shift is less prominent in the global irradiance case since a fraction of the scattered irradiance is added back into the total (global) irradiance as diffuse

  • 227

    (a)

    1800.

    1600.

    1400 f" ~ 1200 ? E 1000

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    Global No~mal

    - 97797 W m -z 869 79 W m -2 773.05 W m-2

    693 08 W m-Z - 622 11 W m-Z

    0.2 0.4 0.6 0.8 1.0 1 2 1.4 1 6 1 8 2.0 22 2.4 26 Wavelenglh (pm)

    (b) 1800-

    1600-

    1400-

    ~ 1200- ? E IO00-

    c

    4OO

    HZO ; 1 42 c{n 1800 ] Direct Normal H20 = 1 42 cm r0.s~m = 0.27 ~ 70.5#m = 0 27

    1600 E

    14co t Legend ~" r / 759 51 W m~

    k

    [3 AM 1 5 E 1200 ] ~ 66296 W m-- Legend I P~ f ~583 11 W m-2 C] AM 1 5

    *AM30 ~ / ~ ~]K ' ,~ 464.15 W m-2 ~AM25 AM 3,5 o~ 80Q + AM 3"0

    02 04 0.6 08 1.0 1 2 1.4 16 18 2.0 2.2 24 2.6 Wavelength (,urn)

    Global Normal

    1~545 20 W m-Z 977 97 W m-Z

    4:08 W m-2

    o.2 o.4 0.6 0.8 ~.0 12 1.4 ~6 ~8 2.0 22 2.4 2.6 Wavelength (pm)

    HZO = 1 42 cm 1800 AM ; 15

    1600

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    800 g J 15 F~IO-

    (c) 1800

    1600

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    200-

    400-

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    0=I

    Dlrecl Normal H20 = 1 42 cm AM = 1.5

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    , , , ~ , ~ , , ,~7~7~-~,, 0.2 0.4 06 0.8 1.0 1.2 14 16 18 20 22 24 26

    Wavelength (,um)

    1800 Global Normal AM = 1 5

    r 0.~jm = 027 1600

    DireCl Normal AM = 15 T0.5~m = 0.27

    Legend ~ 1200 O WV-O5cm 1018 80 W m-Z OWV - 15cm 97570Wm-Z ~ 1000

    WV - 2 5 cm 954.08 W m-Z * - . . - ~ 800

    41111

    21111

    0

    Legend (3 WV - 05 cm 795.07 W m-2 O WV- 1.5cm 757.55Wm-2

    WV - 2 5 cm 73885 W m-2

    O- 0.2 0.4 0.6 0.8 10 12 1.4 1.6 18 2.0 2.2 24 26 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 22 2.4 2.6

    Wavelength ~um) Wavelength Cure)

    Fig. 7. Examples of the impact on global normal and direct normal spectral i r rad iance d i s t r ibut ions of increasing (a) air mass (AM), (b) turbidity (Tau) and (c) water vapor (wv).

    irradiance. Increased turbidity (increased aerosol attenuation) results in decreased irradiance mostly in the visible region of the spectrum (0.4 - 0.7 #m), especially in the case of direct normal irradiance which does not include the scattered irradiance that reaches the surface in the global

  • 50-

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    0.2 1.0 3.0 34. 3.8 4.2 (b )

    1.4 1.8 2.2 2.6

    Wavelength Cum)

    Fig. 8. Photon flux vs. wavelength for (a) Si and (b) amorphous Si. The integral of the shaded area represents the number of photons collected, i.e. photon flux density x quan- tum efficiency.

    irradiance case. Finally, increased water vapor decreases the total irradiance because of increased absorption in the water absorption bands.

    The impact of spectral solar irradiance variations on the performance of PV devices can be evaluated by integrating the product of different spectral irradiance distributions (or photon flux densities) and spectral response (or quantum eff iciency) to obtain the number of photons col lected. For example, the shaded areas in Fig. 8 represent the quantum efficiencies of two types of materials multipl ied by global photon flux density for a

  • 229

    1400

    1200.

    ~ IO00- E 8oo-

    ~ 600-

    400-

    200-

    0.2 0.6 1.0 1.4 1.8 2.2 2.6 Wavelength (/~m)

    Fig. 9. Comparison of direct normal plus circumsolar irradiance calculated using a NASA model [3,4] and a complex radiative transfer code (BRITE [2]), showing overestimation of the circumsolar component in the NASA results. ~, NASA 1977 model, direct normal; o, SERI Brite model, direct normal.

    particular air mass and set of atmospheric conditions, and the integral of the shaded area yields the number of photons collected. PV device efficiency is obtained by converting total photons to short-circuit current density Jsc, multiplying Jsc by modeled or measured values for open circuit voltage Voc and fill factor FF to obtain power output, and dividing power output by total integrated irradiance (power input). That is

    J~c X Voc X FF Power output

    Integrated irradiance Power input

    3. Spectral solar h'radiance models, measurements and data sets

    Spectral solar irradiance variations can be characterized using models and measurements. The existing models vary in complexity from sophisti- cated statistical (Monte Carlo) codes [2] to simple codes that can be implemented on microcomputers [1]. Some of the models calculate only direct irradiance, such as the Thekaekara code used in early PV device performance modeling [3, 4] and the LOWTRAN (1- 5) codes [5], and other models calculate both direct and diffuse irradiance [1, 2, 6- 9]. Inputs to the models include the significant variables such as sun angle (air mass), atmospheric water vapor and turbidity, and collector orientation/ configuration. The simple models [1, 9] treat the atmosphere as a single layer and use approximations to calculate atmospheric scattering. The more

  • 230

    2100-

    1800-

    ~ 1500- E 1200-

    900- E

    600"

    300-

    Air Mass 0 ~ 50-

    ~. /~Globa l , 37 Tilt, Air Mass 1.5 ~ ~ 404

    ~ ~Direct Normal, Air Mass 1.5 30- ~ 2o~

    'i ~ lO E g 1.0 1.8 2.6 3.4 412 g. 0.2

    Wavelength (,um) ( b ) 0.2

    (o) - > 50

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    ~ 3o x z

    ~ 20

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    Air Mass 0

    Global, 37 Tilt, Air Mass 1.5

    Direct Normal,

    ~ ,~ .~.~ Air Mass 0 (~IL'~ ~- -G loba l , 37 Tilt, ~ . .~ Air Mass 1.5

    1.0 1.8 2.6 3.4 4.2 Wavelength (#m)

    ~. 0.3 0.9 1.5 2.1 2.7 3.3 3.9 4.5 ( C ) Photon Energy (eV)

    Fig. 10. Updates to the ASTM spectral irradiance standards [11-14] in units of (a) spectral irradiance, (b) photon flux density per wavelength interval and (c) photon flux density per energy (eV) interval.

    complex codes [2, 5 -8 ] divide the atmosphere into multiple layers with variable constituents and properties, and calculate scattering and absorption within each layer.

    NASA modified the Thekaekara direct normal irradiance model [3] and produced a tabular direct normal spectrum that was published in 1977 for use in PV device analyses [4]. A modification of the Thekaekara model to account for forward-scattered irradiance around the sun (circumsolar irradiance) was found to greatly overestimate circumsolar irradiance [10] (see Fig. 9) when compared with results of a complex radiative transfer code (BRITE [2]). The BRITE code was subsequently used to produce both direct normal and global spectral data sets that were accepted as standards by ASTM [11, 12]. Updates to the ASTM standards [13, 14] are shown in Fig. 10(a), and representations of these data in units of photon flux density per wavelength and per energy interval are shown in Fig. 10(b) and (c). Other spectral data sets (for cloudless skies) produced using BRITE are given in ref. 15. Additional data sets can be produced using the spectral irradiance models.

  • 231

    High quality spectral irradiance measurements using spectroradiometers are difficult to make [16] and are severely lacking. They are, however, needed to validate the models and to develop cloud-cover modifiers for the cloudless sky irradiance models. SERI is in the process of taking spectral measurements at Golden, CO, and is cooperating with others to obtain spectral irradiance data at other locations. The spectral irradiance models, cloud cover modifiers, and high-quality measurements will allow us to develop long-term average spectral irradiance data sets for different climates. These data sets can be used with PV device spectral response curves to predict cell performance and to optimize PV devices (especially multi- bandgap devices) for particular atmospheric (irradiance) conditions and locations.

    4. Issues

    Since spectral irradiance is climate/location-dependent, and PV devices are spectrally dependent, important issues for PV applications are as follows.

    (1) What spectral irradiance data are/should be used to design PV devices and to optimize energy conversion efficiency for particular loca- tions/climates?

    (2) What spectral irradiance data exist/are needed to understand and predict the field performance of PV devices?

    (3) How do PV device efficiency measurements made under particular spectral irradiance conditions (outdoor or simulator) relate to outdoor performance of the devices throughout the day and year for a particular climate?

    References

    1 R. E. Bird and C. J. Riordan, Simple solar spectral model for direct and diffuse irradiance on horizontal and tilted planes at the earth's surface for cloudless atmospheres, SERI/TR-215-2436, 1984 (Solar Energy Research Institute, Golden, CO).

    2 R.E. Bird, Terrestrial solar spectral modeling, Sol. Cells, 7 (1983) 107. 3 M. P. Thekaekara, Survey of quantitative data on the solar energy and its spectral

    distribution, Conf. COMPLES (Cooperation M~diterran~ene sur l'~nergie solaire), Dahran, Saudi Arabia, 1975.

    4 NASA, Terrestrial photovoltaic measurement procedures, ERDA/NASA/1022- 77/16, NASA TM 73702, 1977 (NASA Lewis Research Center, Cleveland, OH, U.S.A.).

    5 Air Force Geophysics Laboratory (AFGL), Atmospheric transmittance/radiance codes -- LOWTRAN I Through 5, (AFGL, Hanscom AFB, MA, U.S.A.).

    6 Air Force Geophysics Laboratory (AFGL), Atmospheric transmittance~radiance codes - -LOWTRAN 6, (AFGL, Hanscom AFB, MA, U.S.A.).

    7 R. E. Bird and R. L. Hulstrom, Availability of SOLTRAN-5 solar spectr...

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