Finite element simulation of inhomogeneous solar cells based on lock-in thermography and luminescence imaging

Frühauf, Felix; Wong, Johnson; Bauer, Jan; Breitenstein, O.

doi:10.1016/j.solmat.2016.12.037

Cited by 24 publications

(12 citation statements)

References 22 publications

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“…Figure c shows the local diode voltage image at 631 mV, which was obtained by evaluating EL images taken at 581 and 631 mV by iteratively fitting as described in Section 2.3. Before this image was used in Local I–V it was artificially blurred by the thermal point spread function for preventing J 01 artefacts between the gridlines to appear, as explained in Ref . Figure d shows the so‐called “RESI‐ R s ” image after Ref., which is based on the blurred V d image and the DLIT‐measured J d image, both at 631 mV.…”

Section: Typical Resultsmentioning

confidence: 99%

“…This error could be corrected by applying a local efficiency analysis based on a finite element solar cell model as proposed in Ref. . Note that, according to the data shown in Figure (c and d), the best regions of the cell predict a possible efficiency of 22.1% and V oc of 677 mV, if a cell would have homogeneously these properties.…”

Section: Typical Resultsmentioning

confidence: 99%

“…Before this image was used in Local I-V it was artificially blurred by the thermal point spread function for preventing J 01 artefacts between the gridlines to appear, as explained in Ref. [32] Figure 3d shows the so-called "RESI-R s " image after Ref., [33] which is based on the blurred V d image and the DLIT-measured J d image, both at 631 mV. This image shows a strong influence of the inhomogeneous dark current distribution visible in (a).…”

Section: Dlit Resultsmentioning

confidence: 99%

“…Of course, this is a too simple model, since the decisive series resistances of a solar cell, which are the horizontal gridline and emitter resistances, carry the current of many elementary diodes, hence these are distributed resistances . For correctly describing R s phenomena in solar cells, actually at least a 2D finite element model is needed, which can be provided, e.g., by the Griddler software . Nevertheless, the model of independent diodes is widely used since, because of its simplicity, it easily allows to obtain quantitative results.…”

Section: Physical Basics Of Imaging Methodsmentioning

confidence: 99%

“…[30] For correctly describing R s phenomena in solar cells, actually at least a 2D finite element model is needed, which can be provided, e.g., by the Griddler software. [31,32] Nevertheless, the model of independent diodes is widely used since, because of its simplicity, it easily allows to obtain quantitative results. It is also used in the Local I-V method for calculating R s at the highest forward bias, where V d is measured by EL, see Section 2.3, and J d is measured by DLIT.…”

Section: Lock-in Thermography (Lit)mentioning

confidence: 99%

See 4 more Smart Citations

Advanced Local Characterization of Silicon Solar Cells

Breitenstein

Frühauf

Bauer

2017

Physica Status Solidi (a)

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Solar cells made from multicrystalline silicon material, which still represent the majority of solar cells produced today, are by nature inhomogeneous devices. Their bulk excess carrier lifetime, which decisively influences the short circuit current density, the saturation current density, and the effective bulk diffusion length, may vary from position to position by an order of magnitude or more. Moreover, such cells may contain ohmic shunts and, in particular in the edge regions, positions of significant depletion region recombination current. The classical local characterization method for solar cells is light beam‐induced current (LBIC) mapping. This method does not give direct information on factors influencing the dark current density. A reliable quantitative local characterization of inhomogeneous cells can be performed by combining dark lock‐in thermography (DLIT) with electro‐ and photoluminescence (EL and PL) imaging. In this contribution, the well‐established and the most recent findings on the application of these methods are reviewed and typical application examples are presented. It is shown that luminescence imaging is most appropriate for local series resistance imaging and for qualitatively imaging of all kinds of recombination‐active defects. DLIT, on the other hand, shows a lower spatial resolution, but is most appropriate for imaging local two‐diode parameters like depletion region‐ and bulk saturation current densities, the latter allowing to draw conclusions also to the local short circuit current density. A comprehensive local characterization of silicon solar cells is possible by applying both DLIT and luminescence imaging, which complement each other.

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Section: Typical Resultsmentioning

confidence: 99%

Section: Typical Resultsmentioning

confidence: 99%

Section: Dlit Resultsmentioning

confidence: 99%

Section: Physical Basics Of Imaging Methodsmentioning

confidence: 99%

Section: Lock-in Thermography (Lit)mentioning

confidence: 99%

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Advanced Local Characterization of Silicon Solar Cells

Breitenstein

Frühauf

Bauer

2017

Physica Status Solidi (a)

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Defect Detection and Degradation Analysis in Photovoltaic Modules using Thermography, Spectroscopy, and Current–Voltage Measurements, and Quantitative Assessment of Their Impact

Akram

Jin

et al. 2020

Energy Tech

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The measurement of defects in photovoltaic (PV) module and their impact assessment can help to improve the reliability and performance of PV systems. Herein, improved defect detection and degradation analysis approach using the combination of infrared (IR) thermography, electroluminescence emission spectroscopy, and current–voltage (I–V) measurements are presented. Moreover, an image‐processing scheme to automatically detect and compute defective area is also proposed. First, experiments are conducted on normal operating modules. Subsequently, different defects and failures are induced, and experiments are conducted again. These modules are analyzed quantitatively and qualitatively. From IR images, defective area, overheating, and underheating computations are carried out. From I–V measurements, power losses, current degradation, and voltage degradation calculations are carried out. The defects that show up in IR images are correlated with I–V curve deviations and their effect on power losses and current/voltage degradation is also analyzed. Moreover, electroluminescence emissions of defective regions are correlated with overheating/underheating calculations. Finally, the observations from experimental results and related quantitative/qualitative computations are summarized. This approach can help to investigate module degradation stage and mode. It can also help in decision making with the use of only IR imaging and related computations in absence of optimum measurement conditions.

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Failures of Photovoltaic modules and their Detection: A Review

Akram

Jin

et al. 2022

Applied Energy

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Finite element simulation of inhomogeneous solar cells based on lock-in thermography and luminescence imaging

Cited by 24 publications

References 22 publications

Advanced Local Characterization of Silicon Solar Cells

Advanced Local Characterization of Silicon Solar Cells

Defect Detection and Degradation Analysis in Photovoltaic Modules using Thermography, Spectroscopy, and Current–Voltage Measurements, and Quantitative Assessment of Their Impact

Failures of Photovoltaic modules and their Detection: A Review

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