Impact of measured spectrum variation on solar photovoltaic efficiencies worldwide

Geoffrey S. Kinsey*, Nicholas C. Riedel-Lyngskær, Alonso Abella Miguel, Matthew Boyd, Marília Braga, Chunhui Shou, Raul R. Cordero, Benjamin C. Duck, Christopher J. Fell, Sarah Feron, George E. Georghiou, Nicholas Habryl, Jim J. John, Nipon Ketjoy, Gabriel López, Atse Louwen, Elijah Loyiso Maweza, Takashi Minemoto, Ankit Mittal, Cécile MoltoGuilherme Neves, Gustavo Nofuentes Garrido, Matthew Norton, Basant R. Paudyal, Enio Bueno Pereira, Yves Poissant, Lawrence Pratt, Qu Shen, Thomas Reindl, Marcus Rennhofer, Carlos D. Rodríguez-Gallegos, Ricardo Rüther, Wilfried van Sark, Miguel A. Sevillano-Bendezú, Hubert Seigneur, Jorge A. Tejero, Marios Theristis, Jan A. Töfflinger, Carolin Ulbrich, Waldeir Amaral Vilela, Xiangao Xia, Márcia A. Yamasoe

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

In photovoltaic power ratings, a single solar spectrum, AM1.5, is the de facto standard for record laboratory efficiencies, commercial module specifications, and performance ratios of solar power plants. More detailed energy analysis that accounts for local spectral irradiance, along with temperature and broadband irradiance, reduces forecast errors to expand the grid utility of solar energy. Here, ground-level measurements of spectral irradiance collected worldwide have been pooled to provide a sampling of geographic, seasonal, and diurnal variation. Applied to nine solar cell types, the resulting divergence in solar cell efficiencies illustrates that a single spectrum is insufficient for comparisons of cells with different spectral responses. Cells with two or more junctions tend to have efficiencies below that under the standard spectrum. Silicon exhibits the least spectral sensitivity: relative weekly site variation ranges from 1% in Lima, Peru to 14% in Edmonton, Canada.

Original languageEnglish
JournalRenewable Energy
Volume196
Pages (from-to)995-1016
ISSN0960-1481
DOIs
Publication statusPublished - Aug 2022

Keywords

  • Energy yield
  • Forecasting
  • Photovoltaics
  • Spectral irradiance

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