Generalized spectral performance evaluation of multijunction solar cells using a multicore, parallelized version of SMARTS

Jaus, J.; Gueymard, Christian A.

doi:10.1063/1.4753849

Cited by 21 publications

(18 citation statements)

References 4 publications

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“…Regarding the first issue, several authors have tackled the problem of analyzing the effect of spectral variations on the energy annually produced by multijunction solar cells [8][9][10][11][12][13][14][15][16]. Some of them have proposed to use a certain spectrum, different from AM1.5D, or they have determined the optimum combination of subcell bandgaps that maximizes the energy harvesting.…”

Section: Introductionmentioning

confidence: 99%

“…Some of them have proposed to use a certain spectrum, different from AM1.5D, or they have determined the optimum combination of subcell bandgaps that maximizes the energy harvesting. The articles cited above neglect the effect of the optics on the spectral distribution of the light reaching the solar cell, most of them assume a cell temperature higher that 25ºC, and they use modeled spectra, some of them based on SMARTS [13][14][15][16], to generate different spectra along the year that are used as inputs for their modeling. Other authors are focused on predicting the power output and energy generation of a certain CPV system and, in order to do that, they model the influence of the spectral variations on the solar cell together with the optics [17,18].…”

Section: Introductionmentioning

confidence: 99%

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Tuning the current ratio of a CPV system to maximize the energy harvesting in a particular location

Victoria

Askins

Núñez

et al. 2013

AIP Conference Proceedings

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Abstract:A method based on experimental data is proposed to optimize the energy harvesting of a silicone-on-glass Fresnel-lens based CPV system. It takes into account the spectral variations along the year in a particular location as well as the thermal and spectral sensitivities of the optics and solar cell. In addition, different alternatives to tune the top/middle subcells current ratio in a CPV module are analyzed and their capacity to maximize the annually produced energy is quantified.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Tuning the current ratio of a CPV system to maximize the energy harvesting in a particular location

Victoria

Askins

Núñez

et al. 2013

AIP Conference Proceedings

View full text Add to dashboard Cite

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“…The latter provides both the α1 and α2 values required by SMARTS. This approach is considered because the single-α model is closer to the original Ångström definition and experimental errors associated with small-band determinations of the τ variation are decreased [24].…”

Section: Spectra Simulationmentioning

confidence: 99%

Energy Simulation of a Holographic PVT Concentrating System for Building Integration Applications

et al. 2016

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Abstract:A building integrated holographic concentrating photovoltaic-thermal system has been optically and energetically simulated. The system has been designed to be superimposed into a solar shading louvre; in this way the concentrating unit takes profit of the solar altitude tracking, which the shading blinds already have, to increase system performance. A dynamic energy simulation has been conducted in two different locations-Sde Boker (Israel) and Avignon (France)-both with adequate annual irradiances for solar applications, but with different weather and energy demand characteristics. The simulation engine utilized has been TRNSYS, coupled with MATLAB (where the ray-tracing algorithm to simulate the holographic optical performance has been implemented). The concentrator achieves annual mean optical efficiencies of 30.3% for Sde Boker and 43.0% for the case of Avignon. Regarding the energy production, in both locations the thermal energy produced meets almost 100% of the domestic hot water demand as this has been considered a priority in the system control. On the other hand, the space heating demands are covered by a percentage ranging from 15% (Avignon) to 20% (Sde Boker). Finally, the electricity produced in both places covers 7.4% of the electrical demand profile for Sde Boker and 9.1% for Avignon.

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“…The set of spectrally-resolved DNI for a number of sites and years, modeled with SMARTS from AERONET data, has been used to obtain SMR spectral indexes [9,10] used in CPV considering a representative operation cell temperature of 90 ºC. However an analysis of the influence in a concrete CPV system should also consider the effect of the optics on the spectral distribution on the MJ cell [11], the change on the transmittance due to temperature variations on the optics [12] and ambient temperature fluctuations.…”

Section: Synthetic World Spectral Networkmentioning

confidence: 99%

Spectral classification of worldwide locations using SMR indexes

Núñez¹,

Jin²,

Antón³

et al. 2016

AIP Conference Proceedings

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Abstract. Spectral variation of solar irradiance can be analyzed by the means of component cells, being useful for multi junction (MJ) and concentrator photovoltaics (CPV) characterization by the use of component cells derived spectral indexes, namely, spectral matching ratios (SMRs). When enough spectral data is available, a location can be also characterized and a MJ solar cell can be locally tuned. The AERONET network of ground-based sun photometers is employed to obtain the atmosphere parameters for 34 sites worldwide. To conclude, the SMR indexes are obtained for every location, and a comparative analysis is completed for four architectures of MJ solar cells technologies (two lattice match and two metamorphic). Based on this information, some cluster of locations that share similar spectral features arise.

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Generalized spectral performance evaluation of multijunction solar cells using a multicore, parallelized version of SMARTS

Cited by 21 publications

References 4 publications

Tuning the current ratio of a CPV system to maximize the energy harvesting in a particular location

Tuning the current ratio of a CPV system to maximize the energy harvesting in a particular location

Energy Simulation of a Holographic PVT Concentrating System for Building Integration Applications

Spectral classification of worldwide locations using SMR indexes

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