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Application of the Singular Spectrum Analysis on Electroluminescence Images of Thin-Film Photovoltaic Modules

In: Artificial Intelligence, Big Data and Data Science in Statistics

Author

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  • Evgenii Sovetkin

    (IEK5-Photovoltaik)

  • Bart E. Pieters

    (IEK5-Photovoltaik)

Abstract

This paper discusses an application of the singular spectrum analysis method (SSA) in the context of electroluminescence (EL) images of thin-film photovoltaic (PV) modules. We propose an EL image decomposition as a sum of three components: global intensity, cell, and aperiodic components. A parametric model of the extracted signal is used to perform several image processing tasks. The cell component is used to identify interconnection lines between PV cells at a sub-pixel accuracy, as well as to correct incorrect stitching of EL images. Furthermore, an explicit expression of the cell component signal is used to estimate the inverse characteristic length, a physical parameter related to the resistances in a PV module.

Suggested Citation

  • Evgenii Sovetkin & Bart E. Pieters, 2022. "Application of the Singular Spectrum Analysis on Electroluminescence Images of Thin-Film Photovoltaic Modules," Springer Books, in: Ansgar Steland & Kwok-Leung Tsui (ed.), Artificial Intelligence, Big Data and Data Science in Statistics, pages 321-342, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-07155-3_14
    DOI: 10.1007/978-3-031-07155-3_14
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