• Energy Research

When PV is installed in the field, the module technologies are rated according to their output energy yield under local operating conditions rather than at standard test conditions STC , where the spectrum is set to AM1.5G. Care must be taken as this standard is not optimal for all latitudes and the solar spectral distribution variations are one primary influencing factor on PV performance. In addition, obtaining an accurate estimate of the spectral effects on PV performance, as set out in standard procedures, is hampered by the cost of gathering the inputs and the large amount of spectral data required for such a calculation. In this work, based on measured spectral irradiance data from nine sites of different latitudes and climates, we first show a characteristic trend in the spectral distribution over the year concerning the location latitude. The closer a site is to the equator, the more blue rich the solar spectrum is and the fewer seasonal spectral variations it will contain. Then, we calculate and correlate the most popular metrics device independent and device dependent used to describe the influence of solar spectra on PV performance. In particular, the monthly irradiance weighted Spectral Mismatch Factor for different PV technologies and Average Photon Energy show a global linear correlation for data from these nine sites. We use this global linear relationship to propose PV technology dependent equations that predict annual and monthly spectral gains losses within a prediction half interval of up to 1.66 by only inserting the monthly or annual irradiance weighted Average Photon Energy potentially for any site. Reducing the required spectral data sets for performance estimation through our methodology facilitates a more accessible and less costly communication of databases than complete spectral data sets. Finally, using this spectral data, we demonstrate statistically that the Spectral Mismatch Factor and Integrated Useful Fraction Ratio can be replaced by alternative spectral metrics, which require only averaged spectra and, thus, reduce the computational effort to estimate the above indicators

When PV is installed in the field, the module technologies are rated according to their output energy yield under local operating conditions rather than at standard test conditions STC , where the spectrum is set to AM1.5G. Care must be taken as this standard is not optimal for all latitudes and the solar spectral distribution variations are one primary influencing factor on PV performance. In addition, obtaining an accurate estimate of the spectral effects on PV performance, as set out in standard procedures, is hampered by the cost of gathering the inputs and the large amount of spectral data required for such a calculation. In this work, based on measured spectral irradiance data from nine sites of different latitudes and climates, we first show a characteristic trend in the spectral distribution over the year concerning the location latitude. The closer a site is to the equator, the more blue rich the solar spectrum is and the fewer seasonal spectral variations it will contain. Then, we calculate and correlate the most popular metrics device independent and device dependent used to describe the influence of solar spectra on PV performance. In particular, the monthly irradiance weighted Spectral Mismatch Factor for different PV technologies and Average Photon Energy show a global linear correlation for data from these nine sites. We use this global linear relationship to propose PV technology dependent equations that predict annual and monthly spectral gains losses within a prediction half interval of up to 1.66 by only inserting the monthly or annual irradiance weighted Average Photon Energy potentially for any site. Reducing the required spectral data sets for performance estimation through our methodology facilitates a more accessible and less costly communication of databases than complete spectral data sets. Finally, using this spectral data, we demonstrate statistically that the Spectral Mismatch Factor and Integrated Useful Fraction Ratio can be replaced by alternative spectral metrics, which require only averaged spectra and, thus, reduce the computational effort to estimate the above indicators

Many performance models exist for energy yield prediction. Most of the performance models use physical parameters determined from measured current density-voltage (JV) curves. However, there is no uniform parametrization method. Using the Karmalkar-Haneefa (KH) fit the physical parameters are obtained from one fitting equation. In addition, we investigate different linear parametrization methods and show that the parameters obtained from the KH model are comparable to those determined from two linear fits. Thereby, it is recommended to use a weighting factor of around 30 near the short circuit current for the KH fit to achieve better comparison with the linear fits. Thus, they can be used for performance models like the Loss Factor Model. For the analysis we used outdoor data for thin-film modules measured over one year in Cologne, Germany.

Many performance models exist for energy yield prediction. Most of the performance models use physical parameters determined from measured current density-voltage (JV) curves. However, there is no uniform parametrization method. Using the Karmalkar-Haneefa (KH) fit the physical parameters are obtained from one fitting equation. In addition, we investigate different linear parametrization methods and show that the parameters obtained from the KH model are comparable to those determined from two linear fits. Thereby, it is recommended to use a weighting factor of around 30 near the short circuit current for the KH fit to achieve better comparison with the linear fits. Thus, they can be used for performance models like the Loss Factor Model. For the analysis we used outdoor data for thin-film modules measured over one year in Cologne, Germany.

We suggest a design for a coating that could be applied on top of any solar cell having at least one diffusing surface. This coating acts as an angle and wavelength selective filter, which increases the average path length and absorptance at long wavelengths without altering the solar cell performance at short wavelengths. The filter design is based on a continuous variation of the refractive index in order to minimize undesired reflection losses. Numerical procedures are used to optimize the filter for a 10 μm thick monocrystalline silicon solar cell, which lifts the efficiency above the Auger limit for unconcentrated illumination. The feasibility to fabricate such filters is also discussed, considering a finite available refractive index range.

We suggest a design for a coating that could be applied on top of any solar cell having at least one diffusing surface. This coating acts as an angle and wavelength selective filter, which increases the average path length and absorptance at long wavelengths without altering the solar cell performance at short wavelengths. The filter design is based on a continuous variation of the refractive index in order to minimize undesired reflection losses. Numerical procedures are used to optimize the filter for a 10 μm thick monocrystalline silicon solar cell, which lifts the efficiency above the Auger limit for unconcentrated illumination. The feasibility to fabricate such filters is also discussed, considering a finite available refractive index range.

ABSTRACTThe influence of a retro‐reflective texture cover on light in‐coupling and light‐trapping in thin film silicon solar cells is investigated. The texture cover is applied to the front glass of the cell and leads to a reflectance as low as r ≈ 3% by reducing the reflection at the air/glass interface and indirectly also reducing the reflections from the internal interfaces. For weakly absorbed light in the long wavelength range, the texture also enhances the light‐trapping in the solar cell. We demonstrate an increase of the short circuit current density of exemplary investigated thin film silicon tandem solar cells by up to 0.95 mA cm−2 and of the conversion efficiency by up to 0.74% (absolute). For a planar microcrystalline solar cell, the enhancement of light‐trapping was determined from the reduced reflection in the long wavelength range to be up to 17%, leading to an increase of the external quantum efficiency of up to 12%. Copyright © 2012 John Wiley & Sons, Ltd.