Application of the Singular Spectrum Analysis on electroluminescence images of thin-film photovoltaic modules

TL;DR

This paper applies singular spectrum analysis to electroluminescence images of thin-film photovoltaic modules, enabling detailed image decomposition, accurate cell interconnection detection, and physical parameter estimation.

Contribution

It introduces a novel EL image decomposition method using SSA, facilitating precise interconnection line detection and physical parameter estimation in PV modules.

Findings

Accurate detection of interconnection lines at sub-pixel accuracy

Effective correction of image stitching errors

Estimation of physical resistance-related parameters

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 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.