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Research Papers

Statistical Analysis of Surface Nanopatterned Thin Film Solar Cells Obtained by Inverse Optimization

[+] Author and Article Information
Shima Hajimirza

e-mail: Shima@ices.utexas.edu

John R. Howell

e-mail: Jhowell@mail.utexas.edu
Department of Mechanical Engineering,
The University of Texas at Austin,
Austin, TX 78712

In practice, sunlight is not polarized, and therefore a more accurate computation should be based on an averaging of the absorptivity spectra based on all polarization angles from 0 to 45 deg. However, our simulations show that the absorptivity variations are negligible with respect to changes in polarization angle. Therefore, for ease of computations, we ignore including these effects in the current work.

Please see Sec. 6.4 for a brief discussion on the sufficiency of the number of sample points.

Contributed by the Heat Transfer Division of ASME for publication in the Journal of Heat Transfer. Manuscript received June 25, 2012; final manuscript received March 18, 2013; published online July 26, 2013. Assoc. Editor: Zhuomin Zhang.

J. Heat Transfer 135(9), 091501 (Jul 26, 2013) (8 pages) Paper No: HT-12-1307; doi: 10.1115/1.4024464 History: Received June 25, 2012; Revised March 11, 2013

This work is a statistical study of the broadband light absorption in thin film solar cells, enhanced by metallic surface nanotexturing. We consider optimum grating structures on the surface of amorphous silicon solar cells obtained by inverse optimization, and study the joint statistics of the resulting absorption enhancement/spectra in the presence of time and structural variants, such as fabrication error and year around changes in the solar irradiance, as well as the angle of incident. We adopt yearly data for solar irradiation at individual hours. In conjunction with the data for light absorption spectra at various incident angles and random samples of the fabrication error vector, we evaluate the real world performance of optimized solar cells. The resulting conclusions serve as a sensitivity/time analysis for better understanding the limits of performance and robustness of thin film cells and optimal light trapping mechanisms.

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Figures

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Fig. 1

Three-dimensional model of thin film solar cell with metallic nanochip grating used for near field radiation calculation

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Fig. 2

Spectral absorptivity (mean and standard deviation) for the textured and bare silicon based on error samples

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Fig. 3

Average solar irradiance for different hours in the whole year

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Fig. 4

Average solar irradiance for different months in the whole year

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Fig. 5

Spectral absorptivity (mean and standard deviation) of textured and bare silicon for uniform incident angle distribution

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Fig. 6

Empirical pdf of the absorptivity enhancement factor of silicon in the realized cell for all time and error samples

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Fig. 7

Empirical pdf of the spectral absorptivity of bare and textured silicon for the realized cell based on all time and error samples

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Fig. 8

Absorptivity enhancement factor (mean and standard deviation) of silicon in the realized cell pattern for different hours computed based on the year around irradiance uncertainties and all error samples

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Fig. 9

Spectral absorptivity (mean and standard deviation) of the bare and textured silicon in the realized cell for different hours computed based on the year around irradiance uncertainties and all error samples

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Fig. 10

Absorptivity enhancement factor (mean and standard deviation) of silicon in the realized cell pattern for different months computed based on the year around irradiance uncertainties and all error samples

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Fig. 11

Spectral absorptivity (mean and standard deviation) of the bare and textured silicon in the realized cell for different months computed based on the year around irradiance uncertainties and all error samples

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Fig. 12

Empirical pdf of the absorptivity enhancement factor of silicon for the optimal geometry, based on year around irradiance and incident angle uncertainties

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Fig. 13

Absorptivity enhancement factor (mean and standard deviation) of the optimal geometry for different hours computed based on year around solar irradiance and incident angle uncertainties

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Fig. 14

Absorptivity enhancement factor (mean and standard deviation) of the optimal geometry for different months computed based on year around solar irradiance and incident angle

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