Spectral effects on amorphous silicon photovoltaic cells literature review: Difference between revisions

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Spectral effects on amorphous PV cells

• The effect of spectral albedo on amorphous silicon and crystalline silicon solar photovoltaic device performance
• Rob W. Andrews and Joshua M. Pearce, The effect of spectral albedo on amorphous silicon and crystalline silicon solar photovoltaic device performance, Solar Energy, 91,233–241 (2013). DOI:10.1016/j.solener.2013.01.030 open access
  • Theory of mismatch factor of terrestrial solar spectrum extended for surface albedo.
  • Effects of effective albedo on amorphous and crystalline silicon photovoltaics used.
  • New formulation for albedo spectral mismatch factor and spectral-weighted albedo.
  • Results help solar systems evaluation and systems design and geographic optimization.

• Effects of spectral albedo on solar photovoltaic devices
• M.P. Brennan, A.L. Abramase, R.W. Andrews, J. M. Pearce, Effects of spectral albedo on solar photovoltaic devices, Solar Energy Materials and Solar Cells, 124, pp. 111-116,(2014). DOI: http://dx.doi.org/10.1016/j.solmat.2014.01.046. [open access soon]
  • Spectral bias from ground albedo impacts optimal selection of photovoltaic materials.
  • Analyzed specular reflectivity of 22 commonly occurring surface materials.
  • Determined albedo effects on the performance of seven PV materials.
  • Investigated solar farms, commercial flat rooftops and residential pitched roofs.
  • Results enable PV selection for environments enabling geographic optimization.

--Effect of atmospheric parameters on the silicon solar cells performance, M. Chegaar, P. Mialhe Spectral effects simulated for Algeirs

effects in short-circuit current due to turbidity, decrease of: 4.41%, 4.7%, 7.34% for mono multi and amorphous. Turbidity decreases UV radiation

Increasing water vapor leads to decrease of 4.57%,4.4%, o.2% for same

Efficiency increase with air mass for crystalline, decrease for amorphous

-- [1. Rüther R, Kleiss G, Reiche K. Spectral effects on amorphous silicon solar module fill factors. Solar Energy Materials and Solar Cells 2002 Feb;71(3):375-385.]

amorphous silicon is more efficient in the summer

crystalline more efficient in winter

A:Si matches very well with indoor illumination spectra, they are more efficient indoors

Spectral mismatch factor: ratio between Isc rated and Isc extrapolated to 1000W/m2

Does not necessarily hold true for a:Si cells: "However, in amorphous silicon solar cells, the proposition of the non-dependence of sðlÞ on the operating voltage does not hold. It is known that in p-i-n structures a typical blue-dispersion of the spectral response occurs for higher bias voltages [14]. Since the field-driven transport is the dominant mechanism with respect to diffusion, and since the electrical field is extended over practically the whole cell, the generation profile inside the cell produces a feedback on the internal quantum efficiency. In a-Si cell modelling, one takes advantage of this effect by application of the DICE method [12,15,16] to yield for a spatially resolved description of the field distribution inside the cell."

FF is the ratio between Imp and Isc

Used a filtered pyranometer to find "Red" and "Blue" spectra

Plots of FF vs Isc,shows much scatter in the central area of Isc.

Attributed to the spectral effect, blue increasing FF, red to decrease it

Shows curves of spectral sensitivity as a function of irradiation

--1. Rüther R, Livingstone J. Seasonal variations in amorphous silicon solar module outputs and thin film characteristics. Solar Energy Materials and Solar Cells 1995 Jan;36(1):29-43.

Outdoors testing of A:Si generally leads to better efficiency in summer, worse in winter

Attributed to thermal annealing and seasonal spectral variations

Conclusion of this paper is that spectral effects are dominating

first cells utilized indoors in calculators

power efficiency from 71% in winter to 83% in summer

bandgap from 360-780

Crystal silicon is better in the winter

therefore, the seasonal variation is likely due to the seasonal changes in spectrum, not annealing. Does not really support this with numbers

--R. Gottschalg, Experimental study of variations of the solar spectrum of relevance to thin film solar cells, Solar Energy Materials and Solar Cells. 79 (n.d.) 527-537.

useful fraction can very in the range of +6 to -9% from annual average

spectral mismatch factor: Fabero and Chenlo [7] and Merten [8] model the spectral mismatch with a spectral mismatch factor for the short circuit current of crystalline and amorphous silicon

Hirata and Tani [9], who used a pyranometer and 6 filters up to a maximum wavelength of 1200 nm and investigated the effect of the spectral changes on a-Si and c-Si devices.

Difficult to quantify the effects on multijunction units because it will cause a mismatch in the series connects cells, leading to non-linear effects [13]

spectral effects though air mass and cloud cover(clearness index)

Annual fluctuations in useful fractions ~10%

--Y. Hirata, T. Tani, Output variation of photovoltaic modules with environmental factors--I. The effect of spectral solar radiation on photovoltaic module output, Solar Energy. 55 (1995) 463-468.

Panels set at 35.5 degrees due south

Calculated output based upon global irradiation

Compared this to actual output: 20% variation in A:Si, derived a 3.7% increase in output over predicted

--J. Merten, J. Andreu, Clear separation of seasonal effects on the performance of amorphous silicon solar modules by outdoor I/V-measurements, Solar Energy Materials and Solar Cells. 52 (1998) 11-25.

clearness index: H/H0/Hmax/Ho

I-V Curve at 10 min intervals

Use silver paste to T/C measurements

Spectral effect is ~16% increase in summer

--R. Gottschalg, T.R. Betts, D.G. Infield, M.J. Kearney, On the importance of considering the incident spectrum when measuring the outdoor performance of amorphous silicon photovoltaic devices, Meas. Sci. Technol. 15 (2004) 460-466.

The fraction of the spectrum falling into spectrally useful ranges is 10% to -15%

Previous studies utilize clear sky models of irradiance for spectral distribution

< 10W/m2 ignored

Use a custom detector with spectral range 300-1700nm

Useful fraction is defined as ratio of irradiation within useful range to total irradiation (300-780 nm)

UF for 300-1700nm is 60.4%

--[http://www.stefankrauter.com/info/23rd_EU_PVSEC_Krauter_Preiss_et%20al.pdf S. Krauter,, PV YIELD PREDICTION FOR THIN FILM TECHNOLOGIES AND THE EFFECT OF INPUT PARAMETERS INACCURACIES, (n.d.).] Outlines the errors in measurement for various PV technologies. Quantifies error due to albedo byt hrouwing out a number

Has created a computer program to simulate the performance of an a:Si PV module, however up to 20% inaccuracy due to innacuracy of inputs.

Good list of inputs for PV simulation

--R.P. Kenny, A. Ioannides, H. Müllejans, W. Zaaiman, E.D. Dunlop, Performance of thin film PV modules, Thin Solid Films. 511-512 (2006) 663-672.

Outdoors measurement of amorphous, crystalline and CIS modules

Using eppley spectroradiometer, 5 min scans up to 2500nm with integrating sphere

Air pressure utilized to measure pressure corrected air mass

Uses an ESTI reference cell, divided in two sections, one shorted with a shunt resistor and one open circuit. Cell temperature derived from open circuit voltage

Temperature coefficient for Voc

Contains equations for translating the Isc, Impp and Vmpp to STC, omitting curve correction factor

Shows mismatch factor for measurement of c-si, a-si and CIS with pyran and reference cell as reference. graphs show high mismatch factors for a-si when using both techniques. shows that using a pyranometer with MMF correction can remove spectral effects

spectral mismatch factor, calculations included

Tests performed on days with <20% diffuse fraction therefore spectram mismatch was largely dependent upon AM

Very comprehensive spectral evaluation resource

Spectral effects on c Si cells

--M. Simon, E.L. Meyer, The effects of spectral evaluation of c-Si modules, Prog. Photovolt: Res. Appl. 19 (2011) 1-10.

• Defines Weighted Useful fraction

Spectral modelling and prediction

Atmospheric turbidity

Clouds

Atmospheric modelling