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Revision as of 17:01, 17 June 2011
This page was developed by the Queen's University Applied Sustainability Research Group. |
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Contents
Spectral effects on amorphous PV cells
--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 radiaiton
Increasing water vapour 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 neccesarily 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.
Attrubited to the spectral effect, blue increasing FF, red to decrease it
Shows curves of spectral senstivity as a function of irradiation
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 variatoin is likely due to the seasonal changes in spectrum, not annealing. Does not really support this with numbers
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 connectes cells, leading to non-linear effects [13]
spectral effects though air mass and cloud cover(clearness index)
Annual fluctiations in useful fractions ~10%
Panels set at 35.5 degrees due south
Calculated output based upon global irradiaiton
Compared this to actual output: 20% variation in A:Si, derived a 3.7% increase in output over predicted
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
The fraction of the specturm falling into spectrally useful ranges is 10% to -15%
Previous studies utilize clear sky models of irradiance for spectral disribution
< 10W/m2 ignored
Use a custom detector with spectral range 300-1700nm
Useful fraction is defined as ratio of irradiaion within useful range to total irradiaiton (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
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
Temperatuer 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 dependant upon AM
Very comprehensive spectral evaluation resource
Spectral effects on c Si cells
- Defines Weighted Useful fractoin