Cracks In Solar Cells Research Articles

Classification of Solar Cell Cracks Using Deep Learning

This study evaluates the efficacy of a Deep Learning model in classifying solar cell images with and without cracks, crucial for early detection and maintenance of photovoltaic systems. The model demonstrates high overall accuracy (94%) and sensitivity (91%), indicating its proficiency in recognizing images with cracks while minimizing false positives. Receiver Operating Characteristic (ROC) analysis supports the model's robust discrimination between positive and negative cases, with an Area Under the Curve (AUC) of 0.93. Despite promising results, opportunities for improvement include dataset expansion to encompass diverse solar cell conditions and types of cracks. Real-world deployment considerations, such as integration into automated monitoring systems, pose challenges requiring further research. The study underscores the importance of ongoing development to enhance model performance for practical application in solar cell inspection and maintenance.

Modelling the effect of defects and cracks in solar cells’ performance using the d1MxP discrete model

Renewable energies are increasingly playing an important role in the world’s energy supply. Society demands new solutions to solve environmental issues caused by fossil fuels. The importance of photovoltaic technology has been increasing and consequently, the necessity to have more accurate models to characterise the performance of solar cells during their entire lifetime has rose as well. Performance problems may appear during devices’ lifetimes associated with factors, such as weather conditions or faulty installation. Cracking might occur, leading to abrupt reductions on the produced power, quite difficult and expensive to fix. The I–V curves of a defected or cracked solar cell might not have the shape imposed by the usual models as 1M5P. In this article, cracked c-Si solar cells are modelled using a novel model: d1MxP. This model is based on the discretisation of the diode’s response on models as 1M5P. Instead of imposing a shape and compute some parameters to fit it on experimental data, the proposed model connects every two points. The results suggest a better fit using the proposed model in comparison with the 1M5P, not only in the original curves, but also modelling cracked cells. As consequence of a better fitting, the computation of important figures of merit as maximum power point or fill factor, reveals to be more precise. It is concluded that the proposed model might characterise the performance of a solar cell, even cracked, which is a huge advance aiming the possibility of simulating complex problems during the cells’ operation lifetime.

Automatic Crack Segmentation and Feature Extraction in Electroluminescence Images of Solar Modules

The effect of cracks in solar cells on the long-term degradation of photovoltaic (PV) modules remains to be determined. To investigate this effect in future studies, it is necessary to quantitatively describe the crack features (e.g., length) and correlate them with module power loss. Electroluminescence (EL) imaging is a common technique for identifying cracks. However, it is currently challenging and time-consuming to identify cracks in a large number of EL images and quantify complex crack features by human inspection. This article introduces a fast semantic segmentation method ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula> 0.18 s/cell) to automatically segment cracks from EL images and algorithms to extract crack features. We fine-tuned a UNet neural network model using pretrained VGG16 as the encoder and obtained an average F1 score of 0.875 and an intersection over union score of 0.782 on the testing set. With cracks and busbars segmented, we developed algorithms for extracting crack features, including the crack-isolated area, the brightness inside the isolated area, and the crack length. We also developed an automatic preprocessing tool for cropping individual cell images from EL images of PV modules ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula> 0.72 s/module). Our codes are published as open-source an software, and our annotated dataset composed of various types of cells is published as a benchmark for crack segmentation in EL images.

Solar cell cracks within a photovoltaic module: Characterization by AC impedance spectroscopy.

Various cell crack modes (with or without electrically inactive cell areas) can be induced in crystalline silicon photovoltaic (PV) cells within a PV module through natural thermomechanical stressors such as strong winds, heavy snow, and large hailstones. Although degradation in the performance of PV modules by cell cracks has been reported occasionally, the mode-dependent evolutions in the electrical signatures of cracks have not yet been elucidated. In this study, we propose that the reduction of the time constant in the AC impedance spectra, which is caused by the elevation of minority-carrier recombination in the p-n junction of a PV cell, is a ubiquitous signature of cracked PV cells encapsulated in a commercially available PV module. Several other characteristics derived from the illuminated current-voltage (I-V) and dark I-V data significantly evolved only in PV cells with inactive cell areas. We also propose that the evaluation by carrier recombination is a crucial diagnostic technique for detecting all crack modes, including microcracks, in wafer-based PV modules.

Efficient and Refined Deep Convolutional Features Network for the Crack Segmentation of Solar Cell Electroluminescence Images

High-quality and fast crack segmentation in solar cell electroluminescence images with heterogeneously textured background disturbance is challenging. We propose an end-to-end Efficient and Refined Deep Convolutional Features Network (ERDCF-Net) for precise and efficient crack segmentation. Firstly, we design a lightweight, efficient deep convolutional features (EDCF) encoder by adopting multilevel deep convolutional features to generate a discriminative feature representation of cracks. Moreover, some complicated background disturbance is restrained by reusing rich crack and background features. Secondly, we present a refined side output (RS) decoder by automatically refining side outputs from the EDCF encoder. The experiments demonstrate that the proposed network excellently performs on the solar cell cracks (MIoU of 92.82%, F - measure of 93.58%, and 89 FPS) and open crack datasets (MIoU of 85.6%, F - measure of 84.1%, and 90 FPS).

Root cause analysis of solar cell cracks at shingle joints

In this work, we report a cracking mechanism occurring on shingle solar cells in PV modules subjected to thermal cycling. Experimental investigations of six different ECAs show that the positions of cracks are precisely limited to the applied ECA in the joint and the occurrence confined to the rear side of the solar cells. Structural mechanic simulations based on the Finite Element Method (FEM) obtain maximum stresses of up to 400MPa on the rear surface of the solar cell orientated towards the back sheet. On the opposing surface, orientated towards the glass, the stresses are on a far lower level at around 230MPa. We measured the characteristic fracture stresses and found values of 96MPa on the rear and 265MPa on the front side of the separated shingle solar cells. The lower values on the rear originate from microfractures at the solar cell edges caused by the laser scribe and mechanical cleave process.

Impact of Solar Cell Cracks Caused During Potential-Induced Degradation (PID) Tests

Potential-induced degradation (PID) of photovoltaic (PV) modules is one of the most severe types of degradation in modern modules, where power losses depend on the strength of the electric field, the temperature and relative humidity, and the PV module materials. Understanding how module defects impact PID is key to reducing the issue. This work investigates the impact of cracks and fractural defects in solar cells and their impact on PID. We have tested using electroluminescence (EL) imaging how solar cells with varying levels of cracks/defects impact PID and our results indicate that such defects have a sizeable influence on the PID. We also confirmed the strong relationship between the size of the initial defect/crack and the presence of hotspots. As the crack (dark) area increased, there was a further increase in the cell’s temperature under standard test conditions (STCs). In this work, it is observed that minor cracks in solar cells have no considerable PID effect for the solar cells providing some reassurance that quality control can reduce this degradation pathway.

An empirical investigation on the correlation between solar cell cracks and hotspots

In recent years, solar cell cracks have been a topic of interest to industry because of their impact on performance deterioration. Therefore, in this work, we investigate the correlation of four crack modes and their effects on the temperature of the solar cell, well known as hotspot. We divided the crack modes to crack free (mode 1), micro-crack (mode 2), shaded area (mode 3), and breakdown (mode 4). Using a dataset of 12 different solar cell samples, we have found that there are no hotspots detected for a solar cell affected by modes 1 or 2. However, we discovered that the solar cell is likely to have hotspots if affected by crack mode 3 or 4, with an expected increase in the temperature from 25^circ C to 100^circ C. Additionally, we have noticed that an increase in the shading ratio in solar cells can cause severe hotspots. For this reason, we observed that the worst-case scenario for a hotspot to develop is at shading ratios of 40% to 60%, with an identified increase in the cell temperature from 25^circ C to 105^circ C.

Analysis of the impact of power loss due to snail trails in a 95-kWp photovoltaic power system

Snail trails are a prevalent degradation phenomenon observed in solar power plants. In a previous study, it was determined that snail trails affected only the appearance of solar cells, without significantly contributing to actual power loss. However, when snail trails are accompanied by solar cell cracks, power loss occurs. We analyzed the snail trails in a specific module in a 95 kW power plant that has been operational since 2015. Moreover, we evaluated the power generation loss arising from snail trails using current–voltage measurements and electroluminescence analysis.

Impact of cracks on crystalline silicon photovoltaic modules temperature distribution

A photovoltaic (PV) module experiences mechanical and thermo-mechanical stress in outdoor conditions, which leads to formation of cracks in solar cells. The cracks give rise to mismatch in the electrical output between the cells, which creates a non-uniform temperature distribution that can have an instantaneous effect on power and long-term effect on PV module reliability. The objective of present work is to investigate the impact of cracks on temperature distribution in a PV module. Based on the electrical behavior of cracked cells, they have been classified as crack with enhanced recombination (C-ER) and crack with loss of active area (C-LAA). The impact of these cracks on temperature distribution has been estimated using an electro-thermal model, which is validated using an experimental setup. Different crack scenarios have been simulated in PV module to analyze the effect of crack type, number of cracked cells, and their biasing on temperature distribution. Results show that under normal operating conditions, the temperature gradient does not change with number of cracked cells. However, when the cracked cell operates under reverse bias either due to change in maximum power point or shading, the temperature gradient decreases with increase in number of cracked cells. Relative comparison between the two types of cracks shows that temperature gradient in PV module is greater in case of C-LAA. The analysis of different crack scenarios presented in this investigation will be useful for detecting cracks in outdoor conditions based on their thermal distribution.

Method for Evaluating the Severity of Solar Cell Cracks in Electroluminescence Images

Method for Evaluating the Severity of Solar Cell Cracks in Electroluminescence Images

Solar cells micro crack detection technique using state-of-the-art electroluminescence imaging

Abstract In this article, we present the development of a novel technique that is used to enhance the detection of micro cracks in solar cells. Initially, the output image of a conventional electroluminescence (EL) system is determined and reprocessed using the binary and discreet Fourier transform (DFT) image processing models. The binary image is used to enhance the detection of the cracks size, position and orientation, principally using the geometric properties of the EL image. On the other hand, the DFT has been used to analyse the EL image in a two-dimensional spectrum. The output image of the DFT consists of structures of all required frequencies, thus improving the detection of possible cracks present in the solar cell. As a result, the developed technique improves the detection of micro cracks in solar cells compared to conventional EL output images.

Ultrafast High-Resolution Solar Cell Cracks Detection Process

This article presents the advancement of an ultrafast high-resolution cracks detection in solar cells manufacturing system. The aim of the developed process is to: first, improve the quality of the calibrated image taken by a low-cost conventional electroluminescence (EL) imaging setup; second, propose a novel methodology to enhance the speed of the detection of the solar cell cracks, and finally develop a proper procedure to decide whether to accept or reject the solar cell due to the existence of the cracks. The proposed detection process has been validated on various cracked/free-crack solar cell samples, evidently it was found that the cracks type, size, and orientation are more visible using the proposes method, while the speed of calibrating the EL images are in the range of 0.1-0.3 s, excluding the EL imaging time.

Enhanced Crack Segmentation (eCS): A Reference Algorithm for Segmenting Cracks in Multicrystalline Silicon Solar Cells

The annually produced quantity of solar modules has steadily increased over the past decades. Rising production speeds and the associated high throughput of wafers, cells, and modules will make an automatized quality inspection mandatory. In the case of visual optical inspection, automatized quality control by using machine vision is already possible. To localize cracks in solar cells, luminescence imaging is used, where several approaches for an automatized inspection exist, but a standard solution for an automatized inspection algorithm is not yet available. This is, in particular, true for multicrystalline solar cells, where the grainy structures in the luminescence images are hard to distinguish from small cracks. Another obstacle in automatic crack analysis is that reference segmentation algorithms are generally not publicly available. Accordingly, a new algorithm can hardly be compared by ranking it to an existing standard. In this paper, we adapted the vesselness algorithm for automatic processing of electroluminescence images of multicrystalline silicon solar cells. Segmentation of cracks in multicrystalline solar cells with the proposed enhanced crack segmentation algorithm shows very promising results on the used database compared with three different commonly used approaches. Furthermore, the segmentation code is made publicly available, and we propose that this algorithm may serve as a reference algorithm, sparking further progress in automatized crack segmentation for multicrystalline silicon solar cells.

Crack detection in monocrystalline silicon solar cells using air-coupled ultrasonic lamb waves

In recent years, solar energy becomes one of the most popular renewable energy resources. Among the solar energy systems, solar cells are considered to be one of the most critical components, which are naturally fragile during either fabrication or service. Thus, nondestructive examination of solar cells is required practically. In this research, solar cells made from monocrystalline silicon are selected as the typical samples. The air-coupled ultrasonic nondestructive testing system, based on the generation and reception of the A0 mode Lamb waves, will be adopted for defects detection. Firstly, the dispersion curves of Lamb waves in anisotropic monocrystalline silicon are calculated theoretically, which provides a theoretical foundation for analyzing the behavior of Lamb waves propagating in silicon solar cells. Then, experiments on monocrystalline silicon solar cells are carried out by introducing the air-coupled ultrasonic Lamb waves. The amplitude distributions of Lamb waves propagating along various rotation angles in silicon solar cells are obtained. It shows a strong anisotropic properties of the tested samples. Finally, artificial cracks in solar cells are scanned circularly and laterally. The results of amplitude distributions give the scattering pattern of cracks, which can be used to determine whether the crack breaks through or not. And the extracted amplitude cross-correlation coefficients can help to estimate the length of them.

Crack Reduction in Tabbing and Stringing Processes for Solar Cells

Wafer cracking is considered to be an important loss in solar cell manufacturing as it crucially affects the production yield as well as the efficiency of solar cells fabricated. There is a certain chance of cracking in wafer when the substrate undergoes some thermal and/or mechanical loads during its fabrication. This research therefore aims to decrease the solar cells cracking in tabbing and stringing processes as the two processes are responsible for a great number of cracks in the substrate. A set of experiments was performed in this study, where soldering temperature and time were tested and the amount of cracks in solar cells was quantified. The findings showed that the use of 185°C soldering temperature with the soldering time of 1,200 ms can reduce the number of cracks in the tabbing and stringing of silicon solar cells. With this setup, the adhesion force between tabbing ribbons and substrate surface can also be promoted, thus preventing the delamination problem in the cell panels.

Experimental investigation of observed defects in crystalline silicon PV modules under outdoor hot dry climatic conditions in Algeria

The paper reviews the different detectable failures of mono-crystalline and poly-crystalline silicon in the research unit in renewable energies in Saharan medium (URERMS) fields. This survey is an effort to inspect and assess the defects of PV modules occurring in recent and older installations in a desert environment and under real operating conditions. The analysis and evaluation of 608 PV modules inside the site of URERMS and in a remote located solar installation (Melouka) using the visual inspection test results in the following failures and degradation modes: delamination, discoloration of the encapsulant, corrosion and discoloration of the metallization (gridlines, busbar, cell interconnect ribbon and string interconnect), solar cell cracks, broken glass, deterioration of the antireflection coating, snail trails, junction box failure, soiling. The electrical performance of some tested modules is also performed in order to give the correlation with the visual defects.

Understanding the Movement of Cracked Solar Cell Parts in PV-modules During Mechanical Loading

We measure the three dimensional movement of cracked solar cell parts in standard sized PV-modules during a four line bending test. We develop a model which explains this movement assuming that the centers of mass of the solar cells or cell parts are fixed to the module glass. The widening of all cell gap widths is proportional to the bending roll displacement until a cell cracks in parallel to the bending rolls due to the tensile stress in the cells. At this point, the crack opens abruptly while the two parallel cell gaps next to the cracked cell close simultaneously by the same distance in sum. From here on, the cell gaps and the cell crack increases proportionally to the bending roll displacement. Since the distance between the centers of mass of both cracked cell parts is independent of the crack position, the crack width is also independent of the crack position for single cracks. Multiple parallel cracks in solar cells have smaller crack widths according to this model. Laminates without a backsheet show about 30% larger crack widths.

Review of Microcrack Detection Techniques for Silicon Solar Cells

Microcracks at the device level in bulk solar cells are the current subject of substantial research by the photovoltaic (PV) industry. This review paper addresses nondestructive testing techniques that are used to detect microfacial and subfacial cracks. In this paper, we mainly focused on mono- and polycrystalline silicon PV devices and the root causes of the cracks in solar cells are described. We have categorized these cracks based on size and location in the wafer. The impact of the microcracks on electrical and mechanical performance of silicon solar cells is reviewed. For the first time, we have used the multi-attribute decision-making method to evaluate the different inspection tools that are available on the market. The decision-making tool is based on the analytical hierarchy process and our approach enables the ranking of the inspection tools for PV production stages, which have conflicting objectives and multi-attribute constraints.

Detection of physical defects in solar cells by hyperspectral imaging technology

A hyperspectral imaging system is developed and is used to identify cracks and fracture defects in solar cells. The basic principles and key technologies of this system are presented, along with a characterization of its performance. The system can provided both single-band images and spectrums of solar cells by laser scanning and hyperspectral imaging. The spectral angle mapper algorithm is used to identify cracks on the surface of solar cells. Experiment results show that this is a non-contact, no-destructive method for detecting cracks in solar cells.