Artifact Interpretation of Spectral Response Measurements on Two-Terminal Multijunction Solar Cells

Journal Article (2016)
Author(s)

FT Si (TU Delft - Photovoltaic Materials and Devices)

O. Isabella (TU Delft - Photovoltaic Materials and Devices)

M. Zeman (TU Delft - Electrical Sustainable Energy)

Research Group
Photovoltaic Materials and Devices
Copyright
© 2016 F.T. Si, O. Isabella, M. Zeman
DOI related publication
https://doi.org/10.1002/aenm.201601930
More Info
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Publication Year
2016
Language
English
Copyright
© 2016 F.T. Si, O. Isabella, M. Zeman
Research Group
Photovoltaic Materials and Devices
Issue number
6
Volume number
7
Pages (from-to)
1-14
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Abstract

Multijunction solar cells promise higher power-conversion efficiency than the single-junction. With respect to two-terminal devices, an accurate measurement of the spectral response requires a delicate adjustment of the light- and voltage-biasing; otherwise it can result in artifacts in the data and thus misinterpretation of the cell properties. In this paper, the formation of measurement artifacts is analyzed by modeling the measurement process, that is, how the current–voltage characteristics of the component subcells evolve with the photoresponse to the incident spectrum. This enables the examination on the operation conditions of the subcells, offering additional information for the study of artifacts. In particular, the influence of shunt resistance, bias-light intensity, and bias voltage on the measurement is examined. Having observed the dynamics and vulnerability of the measurement, the proper ways to configure and interpret a measurement are discussed in depth. As a practical example, simulations of the measurements on a quadruple-junction thin-film silicon solar cell demonstrate that the modeling can be used to interpret eventual irregularities in the measured spectral response. The application of such tool is especially meaningful taking account of the diverse and rapid development of novel hybrid multijunction solar cells, in which the role of reliable characterizations is essential.