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Title: Spectral binning for energy production calculations and multijunction solar cell design

Abstract

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 3more » 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.« less

Authors:
 [1];  [2];  [2];  [2];  [2];  [2];  [2]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States); Univ. Politecnica de Madrid (Spain)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1415018
Report Number(s):
NREL/JA-5J00-68331
Journal ID: ISSN 1062-7995
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Progress in Photovoltaics
Additional Journal Information:
Journal Volume: 26; Journal Issue: 1; Journal ID: ISSN 1062-7995
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; energy harvesting efficiency; multijunction solar cells; spectral binning

Citation Formats

Garcia, Iván, McMahon, William E., Habte, Aron, Geisz, John F., Steiner, Myles A., Sengupta, Manajit, and Friedman, Daniel J. Spectral binning for energy production calculations and multijunction solar cell design. United States: N. p., 2017. Web. doi:10.1002/pip.2943.
Garcia, Iván, McMahon, William E., Habte, Aron, Geisz, John F., Steiner, Myles A., Sengupta, Manajit, & Friedman, Daniel J. Spectral binning for energy production calculations and multijunction solar cell design. United States. doi:10.1002/pip.2943.
Garcia, Iván, McMahon, William E., Habte, Aron, Geisz, John F., Steiner, Myles A., Sengupta, Manajit, and Friedman, Daniel J. Thu . "Spectral binning for energy production calculations and multijunction solar cell design". United States. doi:10.1002/pip.2943. https://www.osti.gov/servlets/purl/1415018.
@article{osti_1415018,
title = {Spectral binning for energy production calculations and multijunction solar cell design},
author = {Garcia, Iván and McMahon, William E. and Habte, Aron and Geisz, John F. and Steiner, Myles A. and Sengupta, Manajit and Friedman, Daniel J.},
abstractNote = {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.},
doi = {10.1002/pip.2943},
journal = {Progress in Photovoltaics},
number = 1,
volume = 26,
place = {United States},
year = {Thu Sep 14 00:00:00 EDT 2017},
month = {Thu Sep 14 00:00:00 EDT 2017}
}

Journal Article:
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