the effects of spectral evaluation of c-si modules

PROGRESS IN PHOTOVOLTAICS: RESEARCH AND APPLICATIONS

Prog. Photovolt: Res. Appl. 2011; 19:1–10

Published online 15 July 2010 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/pip.973

RESEARCH ARTICLE

The effects of spectral evaluation of c-Si modules

Michael Simon*,y and Edson L. Meyer

Fort Hare Institute of Technology, University of Fort Hare, Private Bag x1314, Alice 5700, South Africa

ABSTRACT

Outdoor spectral measurements in sub-Sahara, South Africa in particular have not been documented probably due to lack of

data or lack of proper methodologies for quantifying the spectral effects on photovoltaic performance parameters.

Crystalline-Si modules are widely used for system designs in most cases based on the data provided from indoor

measurements or from maritime northern hemispheric conditions. As a result of this, PV systems fail to deliver their

intended maximum power output. In this study, a methodology for quantifying outdoor spectral effects of c-Si modules

commonly found in the African continent is presented. The results of three crystalline-Si modules indicate that these

modules are affected as the spectrum shifts during seasons although these devices are perceived (without outdoor data) that

their performance is not influenced by the seasonal changes in outdoor spectrum. Copyright # 2010 John Wiley & Sons,

Ltd.

KEYWORDS

outdoor spectrum; crystalline-Si modules; spectral effects

*Correspondence

Michael Simon, Fort Hare Institute of Technology, University of Fort Hare, Private Bag x1314, Alice 5700, South Africa.

E-mail: [email protected]

Received 19 May 2009; Revised 12 September 2009

1. INTRODUCTION

It is becoming certain that the impact of PVmodules on our

daily energy needs is increasing tremendously. Their place

of application has also broadened, thereby calling for the

need to understand their performance. Outdoor monitoring

procedure of PV modules should definitely continue since

the operational conditions are different to the conditions on

which rated parameters are based. Understanding the

performance of different PV devices under various

environmental conditions assists in obtaining useful

information that would help system designers in predicting

energy output, making them more reliable and effective.

One such parameter which is not clearly understood and

affects output electrical parameters is the continuous

change of the outdoor spectrum.

2. EXPERIMENTAL PROCEDURE

PVmodules used in this study are placed on a fixed rack on

the roof top of our Research Centre, clear of any

obstruction that might cause shading. The tilt angle of

Copyright � 2010 John Wiley & Sons, Ltd.

328470 facing north is used since this is the latitude of

Alice, in South Africa. Spectral measurements were taken

using the EPP2000 (portable) fibre optic spectrometer. This

instrument is capable of making various types of spectral

measurements in the UV–VIS–NIR (350–1200 nm)

ranges. The EPP2000 provides 2048 wavelengths for each

scan over the pre-configured range. Range and coarse

resolution are determined by the installed spectrometer

grating groove density. EPP2000 is interfaced to a

computer via a digital parallel port using a 25-pin flat

ribbon cable. Outdoor measurements for the current–

voltage data were facilitated by a current–voltage tester

employing a power supply unit as load. Figure 1 illustrates

the module layout and the apparatus for measuring

environmental conditions.

The concept of Useful Fraction (UF) as used according

to Ref. [1] is a useful parameter for quantifying the spectral

influence on PV devices. One major advantage in

comparison with other concepts is its ability to give direct

feedback of a particular device performance since it is

device dependent. One major assumption made in this

concept is that the spectral response (SR) within the device

wavelength range is 100%. In fact not all of the incident

1

Figure 1. PV module layout installed at the Institute of Tech-

nology, South Africa at tilt angle of 328470 facing north.

Spectral evaluation of c-Si modules M. Simon and E. L. Meyer

energy that is within the device’s spectral range will be

converted to useful energy. To compensate for this, it was

therefore necessary to introduce what is referred to as the

Weighted Useful Fraction (WUF) [2]:

WUF ¼ 1

Gtot

ZEg

0

GðlÞdðlÞSRðlÞ (1)

where G(l) is the spectral irradiance encountered by a

given solar cell.

From Equation (1), WUF is defined as an average SR

weighted on a particular solar spectrum. As a quick

example, at 350 nm for an a-Si device, 20% of the incident

energy density (W/m2/nm) received contributes to the

electron–hole (e–h) creation and for mc-Si at the same

wavelength, 60% is used to create e–h pairs. But the UF

considers that at each wavelength, all the energy received

contributes to the e–h, which is one of the shortcomings

observed from this methodology. The idea of using WUF

Figure 2. Illustration of the change in outdoor spectrum at different t

as a % at each w

2 Pr

was to address these short falls which tend to overestimate

the overall device SR. Figure 2 shows the outdoor spectrum

at different times of the day and the SR of the mc-Si

module. Also illustrated is the effective spectrum perceived

(corrected) by the mc-Si module.

From Figure 2 it is observed that the per cent of the

useful energy converted to output energy at each

wavelength differs. This results in the total integrated

energy density within the device spectral range to be lower

than when the % SR at each wavelength is not considered.

The effective spectrum perceived by the module is

calculated with % SR multiplied by the actual spectrum

at that wavelength.

3. RESULTS AND DISCUSSION

The variation of the incident spectrum has an impact on the

modules short circuit (Isc) current [4]. The influence of theback-of-module temperature (Tmodule) and the change in

irradiance also greatly affect the Isc of the module.

Determining the effect of spectral variations requires the

elimination of these factors by plotting each one of them

with the modules Isc. Normalization of Isc was achieved bydividing the module’s Isc with the total irradiance within

the device spectral range (Gspectral range).

3.1. Spectral influence on mc-Si module’sperformance

The commonly adopted correlation existing between the

module’s Isc and back-of-module temperature is of the

imes of the day. Also shown is the mc-Si spectral response curve

avelength [3].

og. Photovolt: Res. Appl. 2011; 19:1–10 � 2010 John Wiley & Sons, Ltd.DOI: 10.1002/pip

0.00

0.05

0.10

0.15

0.20

0.25

65605550454035302520

Temperature (oC)

φ spe

ctra

l ran

ge (A

/Wm

-2)

-1

0

1

2

3

4

200400

600800

1000

20

30

40

50

I sc(A)

Irradiance (W/

m²)

Temperature

(°C)

Figure 3. Correlation between irradiance corrected Isc and Tdevice. Insert is a 3D graph of variations of the 3 parameters.

M. Simon and E. L. Meyer Spectral evaluation of c-Si modules

form Isc ¼ ðC0 þ C1TdeviceÞ � GSpectralRange [5]. Firstly

the relationship between Isc=GSpectralRange ¼ fSpectralRange

(irradiance corrected Isc) is plotted against back-of-

module temperature. The empirical coefficients C0 and

C1 are obtained. This correlation does not clearly show

the device spectral variations, but this can be

overcome by fitting the data to equation of the form:

fSpectralRange ¼ ðC0 þ C1TdeviceÞ � f ðWUFÞ. This procedureallows the spectral variations to be clearly analysed. Figure 3

(insert) illustrates the dependence of irradiance corrected Iscwith temperature.

0.00

0.05

0.10

0.15

0.20

0.25

00.8120.810.8080.806

φsp

ectr

al r

ange

(A/W

-2)

Figure 4. Variation of fSpectralRang

Prog. Photovolt: Res. Appl. 2011; 19:1–10 � 2010 John Wiley & Sons, Ltd.DOI: 10.1002/pip

The variation of fSpectralRange with temperature is linear

as confirmed in Figure 3. From the Figure 3 (insert), a

linear correlation between Isc, temperature and irradiance

is vivid. Since fSpectralRange is the ratio of Isc to Gspectral range

and both Isc and Gspectral range increases with temperature,

the ratio (Isc/Gspectral range) should exhibit a linear

dependence with temperature. To further understand the

behaviour of fSpectralRange with outdoor spectrum, a plot of

fSpectralRange versus WUF is shown in Figure 4.

Observed from Figure 4 is a direct correlation of

fSpectralRange andWUF. This correlation can be explained as

.814 0.8220.820.8180.816

WUF

e against the module’s WUF.

3

Figure 5. The effects of temperature and irradiance as a function

of fSpectralRange.


follows: An increase in fSpectralRange as WUF increases is

due to the fact that each WUF value corresponds to a

particular irradiance value and distribution.WUF increases

not when the irradiance inside the spectral range does, but

also when the spectral distribution light better matches

with the SR [4]. As WUF is a weighted SR, it is expected

that Isc increases with WUF and that fSpectralRange increases

with WUF.

Analysing how both temperature and irradiance affects

fSpectralRange is of paramount importance for further

understanding the effect of spectral variation. Figure 5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

6004002000

Gglobal

I sc (A

) 0.0

0.5

1.0

1.5

2.0

2.5

3.0

5004003002001000

GSpectral Range (W/m2)

I sc (A

)

Figure 6. Illustrates the effects of Gglobal (measured with pyranom

device

4 Pr

illustrates the variation of fSpectralRange with both irradiance

and temperature. It should be noted that the fSpectralRange

values represented in Figure 5 have been increased by a

factor of 200. This was done purely because of the small

fraction values which require many decimal places to

differentiate them. This would result in the graph to look

rather clumsy.

Notably from Figure 5 is the increase in fSpectralRange as

Gspectral range is reduced. This behaviour contradicts what is

expected if the irradiance used in fSpectralRange had been

global. A linear increase relationship with Gglobal would

have been expected since the irradiance effect would

compensate for each other. The reason for this behaviour in

Figure 5 is due to the fact that the Gspectral range used in

fSpectralRange is very sensitive to outdoor changes as

opposed to Gglobal. Therefore the behaviour of these two

parameters is not the same which results in fSpectralRange to

be high at low irradiance. The change in Isc as outdoor

irradiance varies is well understood. High values of

irradiance result in high values of Isc. This relationship (Iscvs. Gglobal) which is illustrated in Figure 6 illustrates less

scatter as Isc and Gglobal varies simultaneously.

Analysing the insert in Figure 7, the variation of Isc asfunction of irradiance within the device spectral range

(Gspectral range) is not a clear linear relationship as in the case

of Isc versus Gglobal. A large scatter observed as the Iscvaries with Gspectral range of a device illustrates how

sensitive the device is to the sudden changes of the outdoor

environment. This shows that PV module’s Isc respond

greatly to the outdoor spectral changes.

Outdoor spectral effects on crystalline-Si has not been as

greatly documented and studied as amorphous-Si devices.

This has been partly due to the ‘perceived’ larger SR range

140012001000800

(W/m2)

600

eter) and Gspectral range (measured with spectroradiometer) on

Isc.


High cloud cover

Low WUF regionHigh WUF region

Sunrise/sunset: Longer wavelengths dominating

0.0

0.4

0.8

1.2

1.6

2.0

1400120010008006004002000

Irradiance (W/m2)

φ Spe

ctra

l Ran

ge (A

/Wm

-2)

Figure 7. Illustration of the dependence of fSpectralRange on the total irradiance as measured by the pyranometer.


of c-Si which theoretically translates to a relatively stable

outdoor performance. But analysing the outdoor spectral

data and correlating this to the device performance data, a

different conclusion is reached. Figure 7 illustrates the

dependence of fSpectralRange on irradiance (Gglobal).

Observing Figure 7, the spectrally corrected fSpectralRange

versus irradiance (Gglobal) reveals the effect of outdoor

conditions on device’s fSpectralRange. For irradiances greater

than 800W/m2, the data points are more defined and less

scattered and linear relationships exists. Below Gglobal of

800W/m2 and close to 300W/m2 the linear trend

relationship that has been exhibited at Gglobal> 800W/

m2 disappears. The scatter is more pronounced with no

clear trend. This figure also reiterates the fact that PV

device performance is greatly affected by the changes in

outdoor conditions. For Gglobal> 800W/m2 it indicates

‘clear sky’ condition typically found under full spectrum

and Gglobal< 300W/m2 also indicate spectrum character-

ized by low WUF, a typical spectrum dominated by longer

wavelength (sunrise/sunset) resulting in poor performance

of the device, as indicated in Figure 7 (green curve). Low

WUF values can also be found under high cloud cover with

mostly shorter wavelength being scattered back into the

sky, letting only longer wavelength to pass through. Also

the high cloud cover acts as a filter for the infrared (IR)

light and will shift the spectrum to full spectrum region (as

defined in previous section) resulting in an increase in

device performance indicated by the upper curve (purple).

These two phenomena lead to both high values of Isc andlow values for Isc, as is evident in Figure 7. The change in

outdoor spectrum is influenced by a number of factors, e.g.

time of the year, sun elevation, meteorological conditions

and tilt of the module [4]. The commonly adopted

reference spectrum of AM 1.5 was created using a radiative

transfer model called BRITE [6]. Most of the input

parameters used were obtained from United States


environment, e.g. tilt angle of 37o which is average

latitude in US continent [6]. Air mass (AM) contributes

greatly to the outdoor spectral variations and consequently

device spectral changes as characterized by WUF. Ideally

an increase in AM results in a decrease in deviceWUF. The

correlation between WUF and AM for mc-Si is presented

in Figure 8. Note that the AM values were calculated at the

same time frame as the WUF. This was done so that the

same time frame when WUF measurements were taken

would be the same as the calculated AM values.

Evident from Figure 8 is a functional relationship

between AM and WUF. Large AM values correspond to

larger wavelength mainly found under low irradiance

levels. At these conditions, the WUF of the device will be

lower than its value at AM 1.5. The variation of WUF with

AM for mc-Si module for both summer and winter has the

same trend as is indicated by the gradients of the two

curves. Although the WUF winter values are not the same,

the functional relationship between the two parameters in

both cases is the same. This shows that the WUF versus

AM relationship is device dependent. Depending on the

type of PV module, the gradient of the WUF versus AM

curve will differ. This, however, will be clear only after

having examined the other modules. Figure 9 shows a

typical daily WUF and AM on clear days for both summer

and winter seasons.

During early morning (before 07:30 h) and late after-

noon (after 16:00 h) the low solar altitude is characterized

by high AM values (>8). The spectrum during these times

is associated with longer wavelengths dominating due to

Raleigh scattering. From the figure it is then deduced that

WUF< 0.78 for summer season is indicative of a ‘red’

spectrum while WUF> 0.78 indicates a full spectrum. The

WUF in summer peaks at 10:30 h at a value of 0.8099

corresponding to an AM¼ 2.19, which is different from

AM 1.5 expected at solar noon, 12:30 h. Furthermore,

5

y = -0.0029x + 0.7245R2 = 0.8231

y = -0.0032x + 0.815R2 = 0.9078

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

181614121086420

Air Mass

WU

F

Winter Summer

Figure 8. Influence of the air mass on device spectral variations as characterized by WUF for mc-Si module for both summer and

winter seasons.


repeating the exercise for clear winter days, it was deduced

also that WUF< 0.71 is indicative of ‘red’ spectrum and

WUF> 0.71 indicates a full spectrum. This procedure was

adopted because the summer and winter spectra are

different. The WUF was found to peak at 13:00 h at a value

of 0.7125, corresponding to AM 1.83 during winter

seasons. To isolate the effect of seasonal spectral changes,

0.40

0.45

0.50

0.55

0.60

0.65

0.70

0.75

0.80

0.85

6:007:12

8:249:36

10:481

WU

F

WUF Summer WUF

10:30 @ WUF= 0.8099 &

13:00 @ W

Red Spectrum

Full Spectrum

Figure 9. Illustrates the seasonal WUF profile again

6 Pr

the influence of WUF on FF was characterized in summer

and winter. Figure 10 illustrates the entire SR range (s2) for

mc-Si during summer and winter. Also illustrated is the

half-width of the Gaussian peaks, s1.

Noteworthy from Figure 10 is the low frequency (or

time spent) under the red spectrum in summer. This implies

that the device preferentially experiences, in summer, a full

2:0013:12

14:2415:36

16:4818:00

-15

-10

-5

0

5

10

15A

ir M

ass

Winter Air Mass

AM2.19

UF= 0.7125 & AM1.83

Full Spectrum

Red Spectrum

st time together with the change in AM values.


0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.000.950.900.850.800.750.700.650.600.550.50

WUF

Fill

Fact

or

0

20

40

60

80

100

120

Freq

uenc

y (%

)

Summer Winter

σ1winter σ1summer

σ2winter (Device range)σ2summer (Device range)

Figure 10. Effect of season on device junction properties as illustrated by Fill Factor.


spectrum to operate optimally. Conversely the wider

s1winter implies that the device operates optimally over a

wider spectral band. More than half of s1winter corresponds

to red-shifted spectrum implying that the device prefer-

entially experiences, in winter a red-dominated spectrum to

operate optimally.

3.2. Performance of mono-Si

Crystalline silicon modules used in this study (mc-Si,

mono-Si and poly-Si) should ideally behave in the same

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

86420

Air

WU

F

Figure 11. Influence of air mass on device spectral varia


way under outdoor conditions. The effect of the three major

outdoor factors that affect their performance should affect

them in the same manner regardless of their ratings.

Figure 11 illustrates the influence of AM on WUF for

mono-Si module for winter and summer seasons.

Closer analysis of Figure 11 reveals that the gradient of

the two curves for both summer and winter seasons is the

same for the mono-Si module. The gradient exhibited in

Figure 11 is the same with that of mc-Si in Figure 8. This

indicates that the two devices have the same AM

dependence although their WUFs are different.

Figure 12 illustrates the variation in WUF due to seasonal

y = -0.003x + 0.5773R2 = 0.9359

y = -0.0032x + 0.6439R2 = 0.9515

1816141210

Mass

Winter Summer

tions as characterized by WUF for mono-Si module.

7

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

6:007:12

8:249:36

10:4812:00

13:1214:24

15:3616:48

18:00

WU

F

-15

-10

-5

0

5

10

15

Air

Mas

s

WUF Summer WUF Winter Air Mass

14:00 @ WUF= 0.5691 2.58& AM

12:00 @ WUF= 0.6457 & AM 1.83 Full spectrum

spectrum Red

Full spectrum

Red spectrum

Figure 12. Illustrates a typical daily WUF and air mass on clear summer and winter day for c-Si module.


changes in the spectrum. Also illustrated is the AM

variation with day time.

The same procedure adopted in Figure 9 was also

applied in analysing the seasonal spectral effects on c-Si

module. For summer period, it is deduced that for

WUF< 0.61 is indicative of the red spectrum while

WUF> 0.61 indicates a full spectrum. For winter season,

WUF< 0.555 indicates a red spectrum and WUF> 0.555

is indicative of a full spectrum.

For summer seasons, the mono-Si module preferentially

experiences a spectrum characterized by low AM values

(AM 1.83). This spectrum which peaks at 12:00 h noon

corresponds to the WUF¼ 0.6457. For winter season, the

WUF was found to peak at 14:00 h at a value of 0.5691,

corresponding to AM 2.58. As evident in both seasons, the

spectrum that is preferentially experienced by the mono-Si

module is different from AM 1.5.

Table I lists the parameters of both mono-Si module and

poly-Si module during summer and winter seasons.

The device spectral range (sspectral range) for mono-Si

module is wider in summer than it is during winter period.

This results in 71.13% difference as the winter sspectral rangeis reduced. The FF and efficiency still remains the same as

indicated by a slight % difference, which is within

experimental errors. The response of mono-Si module to

Table I. Dependence of Fill Factor and efficiency of both mono-Si a

Useful Fraction in summe

mono-Si

sspectral range WUFmean FFAverage hA

Summer 0.41–0.895 0.6457 0.67 1

Winter 0.49–0.630 0.5791 0.67 1

% Difference 71.13 12.31 0

8 Pr

the outdoor changes due to season is not compromised

although its spectral range has been affected.

3.3. Performance of poly-Si

As mentioned earlier on in Section 3.1, the variation of

WUF versus AM depends on the characteristics of the PV

module. It was considered important to analyse the effect

of AM onWUF for poly-Si module for summer and winter

seasons. Figure 13 illustrates the influence of AM on

device spectral variations for the poly-Si module.

The variation of WUF as a function of AM for both

winter and summer does not vary significantly as indicated

by the slope of the two curves. Comparing Figure 13 with

Figures 8 and 11, the poly-Si module’s gradient is different.

Figure 14 shows the summer and winter profiles in relation

to AM for poly-Si module.

Notable from Figure 14 are the low WUF values for the

poly-Si module as compared to the other crystalline-Si

modules. It is deduced from Figure 14 that WUF< 0.551

for both summer and winter seasons is indicative of a ‘red’

spectrum while WUF> 0.551 indicates a full spectrum.

The WUF in summer peaks at 09:30 h at a value of 0.5541

corresponding to an AM¼ 3.36, which is different from

nd poly-Si with outdoor spectrum as characterized by Weighted

r and winter seasons.

poly-Si

verage sspectral range WUFmean FFAverage hAverage

3.36 0.41–0.70 0.5541 0.713 7.21

3.67 0.47–0.66 0.5813 0.676 7.32

2.27 34.5 4.5 5.2 1.5


0.30

0.35

0.40

0.45

0.50

0.55

0.60

6:007:12

8:249:36

10:4812:00

13:1214:24

15:3616:48

18:00

WU

F

-15

-10

-5

0

5

10

15

Air

Mas

s

WUF Summer WUF Winter AM

09:30 @ WUF= 0.5541 & AM 3.36

13:00 @ WUF= 0.5813 & AM 1.83 Full spectrum

Red spectrum

Figure 14. Seasonal WUF for summer and winter profiles for poly-Si module.

y = -0.0022x + 0.5729R2 = 0.7657

y = -0.001x + 0.5688R2 = 0.6943

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

181614121086420AM

WU

F

Winter Summer

Figure 13. Variation of WUF as a function of AM for summer and winter seasons for pc-Si module.


AM 1.5 expected at solar noon, 12:30 h. For clear winter

days, it was also observed that the WUF was found to

peak at 13:00 h at a value of 0.5813, corresponding to AM

1.83.

Poly-Si module’s performance parameters are not signifi-

cantly affected by the outdoor seasonal changes. The device

average efficiency has a 1.5% difference which could be

attributed by some errors associated with the measuring


instruments. Although the device’s sspectral range had increased,

this could not affect both WUFmean and FF greatly.

4. SUMMARY AND CONCLUSION

Evident from the results presented in this study is that the

spectrum received in sub-Sahara is totally different from

9


the standard AM 1.5 spectrum and from that received from

the northern hemisphere regions. Also noted is that

crystalline-Si modules are also affected by the spectrum

shift during seasons although these devices are perceived

(without outdoor data) that their performance is not

influenced by the seasonal changes in outdoor spectrum. It

has been showed that for summer season, mc-Si

preferentially experiences to operate optimally at

WUF¼ 0.8099, which is an indication of a full spectrum

as defined in this study. For winter season the mc-Si

module responds optimally at WUF¼ 0.7125 which

corresponds to AM 2.19. It is evident that the change in

outdoor spectrum due to seasons affects the module’s

spectrum to which it best preferentially experiences to

operate optimally and also the time of the day at the

corresponding spectrum. Results for mono-Si module

showed that the device performs best at WUF¼ 0.6457

which corresponds to AM 1.83 during summer season,

while it operates optimally under a winter spectrum

indicated by WUF of 0.5691 (AM 2.58). The seasonal

changes resulted in the shift in day time corresponding to

the preferentially experiences spectrum. This shift

indicates that these devices should be rated using AM

values that correspond to the WUF values under which the

device operates optimal. For poly-Si, it was also observed

the WUF values are lower than the other two crystalline-Si

counterparts. The poly-Si was observed to preferentially

experiences a low AM spectrum indicated by

WUF¼ 0.5813 during winter season while for summer

it preferentially experiences a spectrum characterized by

WUF¼ 0.5541 at AM 3.36.

10 Pr

5. ACKNOWLEDGEMENTS

Authors acknowledge the Govan Mbeki Research and

Development Centre (GMRC) and Eskom Tertiary

Education Support Programme (TESP) for their financial

support.

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the effects of spectral evaluation of c-si modules

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