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García Vara, Iván and McMahon, William E. and Habte, Aron and Geisz, John F. and Steiner, Myles A. and Sengupta, Manajit and Friedman, Daniel J. (2017). Spectral binning for energy production calculations and multijunction solar cell design. "Progress in Photovoltaics: Research and Applications", v. N/A (n. N/A); pp. 1-7. ISSN 1099-159X. https://doi.org/10.1002/pip.2943.
Title: | Spectral binning for energy production calculations and multijunction solar cell design |
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Author/s: |
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Item Type: | Article |
Título de Revista/Publicación: | Progress in Photovoltaics: Research and Applications |
Date: | September 2017 |
ISSN: | 1099-159X |
Volume: | N/A |
Subjects: | |
Freetext Keywords: | energy harvesting efficiency multijunction solar cells spectral binning |
Faculty: | Instituto de Energía Solar (IES) (UPM) |
Department: | Electrónica Física |
UPM's Research Group: | Semiconductores III-V |
Creative Commons Licenses: | None |
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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.
(C) John Wiley & Sons Ltd
Item ID: | 47860 |
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DC Identifier: | https://oa.upm.es/47860/ |
OAI Identifier: | oai:oa.upm.es:47860 |
DOI: | 10.1002/pip.2943 |
Official URL: | http://onlinelibrary.wiley.com/doi/10.1002/pip.294... |
Deposited by: | Dr. Iván García Vara |
Deposited on: | 26 Sep 2017 08:34 |
Last Modified: | 14 Mar 2019 13:54 |