Spectral study and classification of worldwide locations considering several multijunction solar cell technologies

Núñez, Rubén; Jin, Chen; Victoria, Marta; Domínguez, César; Askins, Stephen; Herrero, Rebeca; Antón, Ignacio; Sala, Gabriel

doi:10.1002/pip.2781

Cited by 15 publications

(7 citation statements)

References 41 publications

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“…This work is a continuation of the studies by Victoria et al [26] and Nuñez et al [12] for locations others than Madrid. In Figure 2, a schematic of the simulation model is shown.…”

Section: Simulation Model and Methodologysupporting

confidence: 70%

“…Both locations show a similar effect, due to the decrease in low wavelength transmittance of the SOG, a red shift of the spectra can be identified (J ratio < 1). The spectra in Lanai is bluer, due to the high content of precipitable water in the air [12]. Knowing this we would expect the losses caused by the SOG to be higher, yet this is not the case.…”

Section: -4mentioning

confidence: 97%

“…Philipps et al [11] and many more such as [10], [11]. Taking into account the spectral variability of a certain location, which varies according to spectral parameters like precipitable water (PW), aerosol optical depth (AOD) and the air mass (AM) different sites can be studied [12]. One of these yearly series is the typical metrological year (TMY3) spectral database [13], which is used in this specific simulation.…”

Section: Impact Of the Temperature Dependence Of Cpv Optics Transmittmentioning

confidence: 99%

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Impact of the temperature dependence of CPV optics transmittance on the current mismatch of multi-junction solar cells

Jost¹,

Núñez²,

Victoria³

et al. 2018

AIP Conference Proceedings

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The influence of spectra and temperature dependence of concentrator photovoltaics (CPV) optics is investigated by modelling yearly series of ambient conditions, such as typical meteorological year (TMY) data, and simulating the response of relevant CPV technologies. Results show the influence the optics have on the effective spectra available at the solar cell level. This allows us to find the limiting factors of a CPV module performance and permits energy yield predictions.

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“…This work is a continuation of the studies by Victoria et al [26] and Nuñez et al [12] for locations others than Madrid. In Figure 2, a schematic of the simulation model is shown.…”

Section: Simulation Model and Methodologysupporting

confidence: 70%

Section: -4mentioning

confidence: 97%

Section: Impact Of the Temperature Dependence Of Cpv Optics Transmittmentioning

confidence: 99%

See 1 more Smart Citation

Impact of the temperature dependence of CPV optics transmittance on the current mismatch of multi-junction solar cells

Jost¹,

Núñez²,

Victoria³

et al. 2018

AIP Conference Proceedings

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“…However, a single design spectrum does not convey any information about the variability of spectra at a particular site. This variability is crucial, because it affects the annual energy production (AEP), [3][4][5][6][7][8][9][10][11][12][13] and thereby the levelized cost of electricity of a system, and may also affect the design of multijunction cells for such systems. Here, we show how a set of~50 000 spectra representing spectral conditions over the course of a year can be reduced to a much smaller set of "proxy" spectra.…”

Section: Introductionmentioning

confidence: 99%

Spectral binning for energy production calculations and multijunction solar cell design

García

McMahon

Habte

et al. 2017

Progress in Photovoltaics

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Currently, most solar cells are designed for and evaluated under standard spectra intended to represent typical spectral conditions. However, no single spectrum can capture the spectral variability needed for annual energy production (AEP) calculations, and this shortcoming becomes more significant for series-connected multijunction cells as the number of junctions increases. For this reason, AEP calculations are often performed on very detailed yearlong sets of data, but these pose 2 inherent challenges: (1) These data sets comprise thousands of data points, which appear as a scattered cloud of data when plotted against typical parameters and are hence cumbersome to classify and compare, and (2) large sets of spectra bring with them a corresponding increase in computation or measurement time. Here, we show how a large spectral set can be reduced to just a few "proxy" spectra, which still retain the spectral variability information needed for AEP design and evaluation. The basic "spectral binning" methods should be extensible to a variety of multijunction device architectures. In this study, as a demonstration, the AEP of a 4-junction device is computed for both a full set of spectra and a reduced proxy set, and the results show excellent agreement for as few as 3 proxy spectra. This enables much faster (and thereby more detailed) calculations and indoor measurements and provides a manageable way to parameterize a spectral set, essentially creating a "spectral fingerprint," which should facilitate the understanding and comparison of different sites. For design purposes, standard direct spectra can be developed for specific regions. For example, the ASTM G173 direct spectrum represents the spectral content of the direct spectra in the arid southwestern region of the United States.1,2 This is quite useful, because it ensures that a concentrator photovoltaics (CPV) system designed for a particular standard spectrum will be suitable for use in the corresponding geographic area.However, a single design spectrum does not convey any information about the variability of spectra at a particular site. This variability is crucial, because it affects the annual energy production (AEP), 3-13 and thereby the levelized cost of electricity of a system, and may also affect the design of multijunction cells for such systems. Here, we show how a set of~50 000 spectra representing spectral conditions over the course of a year can be reduced to a much smaller set of "proxy" spectra. Our results show that, with an effective binning process, a very small set of just 3 proxy spectra retains enough information about spectral variability to accurately compute and design for AEP.Such a small set of proxy spectra can greatly reduce the time needed for AEP calculations, enabling much more detailed and thorough investigations. Although in some cases it may be possible to use a full yearlong set of spectra, the time needed for computations can become prohibitive due to the large number of spectra (around 50 000 for 5-min time incremen...

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“…Concentrator photovoltaic devices (CPV) employing multi-junction (MJ) solar cells exhibit strong spectral sensitivities due to their series-connected nature. The use of "isotype" or "component" cells for spectral monitoring is widely used in CPV [1][2][3] to fix the spectral conditions of the impinging irradiance. Component or isotype cells are spectrally-matched sensors to a particular MJ technology, i.e., devices whose spectral response is as similar as possible to a single sub-cell of the MJ cell to be characterized, and are made by epitaxially growing an identical MJ stack with only one electrically active p-n junction while the others act purely as optical filters.…”

Section: Introductionmentioning

confidence: 99%

From component to multi-junction solar cells for spectral monitoring

Jost¹,

Antón²,

Núñez³

et al. 2018

AIP Conference Proceedings

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Concentrator photovoltaic usually embeds multi-junction solar cells, which exhibit high spectral sensitivity due to the internal series connection of the sub-cells. The use of so-called isotype or component cells with the same spectral response as the corresponding sub-cell, is widely applied for characterizing the spectral content of the impinging irradiance. These isotype sensors can be substituted by the multi-junction cells themselves, which are inherently spectrally tuned to any evolution of the multi-junction technology. To convert a multi-junction cell in a spectral sensor, it is necessary to add bias light within the spectral response of all but one of the sub-cells to saturate the corresponding junctions, so the nonsaturated limits the current under any specified impinging spectrum. This paper shows indoor and outdoor side-by-side comparison of the so-called pseudo isotypes, based on a triple-junction solar cell, and genuine isotypes. The conditions to ensure an accurate spectral response, particularly for the bottom pseudo-isotype, are presented and discussed.

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Spectral study and classification of worldwide locations considering several multijunction solar cell technologies

Cited by 15 publications

References 41 publications

Impact of the temperature dependence of CPV optics transmittance on the current mismatch of multi-junction solar cells

Impact of the temperature dependence of CPV optics transmittance on the current mismatch of multi-junction solar cells

Spectral binning for energy production calculations and multijunction solar cell design

From component to multi-junction solar cells for spectral monitoring

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