Modeling, imaging and resistance analysis for crystalline silicon photovoltaic modules failure on thermal cycle test

Du, Ying; Wang, Luchuang; Tao, Wusong

doi:10.1016/j.engfailanal.2020.104818

Cited by 12 publications

(3 citation statements)

References 13 publications

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“…Broadly speaking, there are three main causes of thermal degradation. Firstly, there are deterioration processes, which include thermo-chemical reactions [22,23] and thermo-mechanical stresses [24,25]. Secondly, there are cyclic aging conditions [26,27], such as diurnal and seasonal temperature variations, as well as general aging effects.…”

Section: Thermal Degradation and Aerial Thermographic Inspectionmentioning

confidence: 99%

Radiometric Infrared Thermography of Solar Photovoltaic Systems: An Explainable Predictive Maintenance Approach for Remote Aerial Diagnostic Monitoring

Qureshi,

Rashid,

Altini

et al. 2024

Smart Cities

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Solar photovoltaic (SPV) arrays are crucial components of clean and sustainable energy infrastructure. However, SPV panels are susceptible to thermal degradation defects that can impact their performance, thereby necessitating timely and accurate fault detection to maintain optimal energy generation. The considered case study focuses on an intelligent fault detection and diagnosis (IFDD) system for the analysis of radiometric infrared thermography (IRT) of SPV arrays in a predictive maintenance setting, enabling remote inspection and diagnostic monitoring of the SPV power plant sites. The proposed IFDD system employs a custom-developed deep learning approach which relies on convolutional neural networks for effective multiclass classification of defect types. The diagnosis of SPV panels is a challenging task for issues such as IRT data scarcity, defect-patterns’ complexity, and low thermal image acquisition quality due to noise and calibration issues. Hence, this research carefully prepares a customized high-quality but severely imbalanced six-class thermographic radiometric dataset of SPV panels. With respect to previous approaches, numerical temperature values in floating-point are used to train and validate the predictive models. The trained models display high accuracy for efficient thermal anomaly diagnosis. Finally, to create a trust in the IFDD system, the process underlying the classification model is investigated with perceptive explainability, for portraying the most discriminant image features, and mathematical-structure-based interpretability, to achieve multiclass feature clustering.

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Section: Thermal Degradation and Aerial Thermographic Inspectionmentioning

confidence: 99%

Radiometric Infrared Thermography of Solar Photovoltaic Systems: An Explainable Predictive Maintenance Approach for Remote Aerial Diagnostic Monitoring

Qureshi,

Rashid,

Altini

et al. 2024

Smart Cities

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“…Previous researchers have been focused on the reliability of PV module [3,4] , encapsulation material [5,6] and manufacturing process [7,8] about TC aging, but omitted the monitor current impact on PV module. This paper studies the influence of monitor current in the TC test on three types of PV modules (PERC, HJT and TOPCon).…”

Section: Introductionmentioning

confidence: 99%

Influence of Monitor Current on Electrical Performance of Photovoltaic Module (PERC/HJT/Topcon) in Thermal Cycle Test

Zhou

2023

E3S Web of Conf.

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IEC 61215-2: 2016 is an international standard about testing photovoltaic (PV) module reliability, in which the thermal cycle (TC) test item mainly has focused on thermal stress interaction of PV modules between different materials. At TC testing different stages, except for high working current (Imp), low current (Max. 1 %*Imp) has been turned on continuously as monitor current in order to evaluate the field operation situation of photovoltaic modules. In this paper, the test programme are designed meticulously and I-V data&EL pictures test results are discussed according to the influence level of monitor current on PERC, HJT and TOPCon modules. Three types of PV modules have performed the respective I-V characteristics and thus the values of Isc, Voc and Pmp have appeared different trends.

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“…Modules undergoing thermo-mechanical stress and cell breakage may undergo J o1 increases due to increased unpassivated surface area at fracture surfaces, R s losses due to metallization breaks and solder bond failure [11,12], J o2 and junction ideality factor increases, and shunt resistance decreases due to increased physical defects penetrating the junction [13]. Additionally, some fraction of the cell circuit may be removed when the cell and its metallization become electrically disconnected [14].…”

Section: Introductionmentioning

confidence: 99%

In-Situ Measurement of Power Loss for Crystalline Silicon Modules Undergoing Thermal Cycling and Mechanical Loading Stress Testing

2020

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An in-situ method is proposed for monitoring and estimating the power degradation of mc-Si photovoltaic (PV) modules undergoing thermo-mechanical degradation tests that primarily manifest through cell cracking, such as mechanical load tests, thermal cycling and humidity freeze tests. The method is based on in-situ measurement of the module’s dark current-voltage (I-V) characteristic curve during the stress test, as well as initial and final module flash testing on a Sun simulator. The method uses superposition of the dark I-V curve with final flash test module short-circuit current to account for shunt and junction recombination losses, as well as series resistance estimation from the in-situ measured dark I-Vs and final flash test measurements. The method is developed based on mc-Si standard modules undergoing several stages of thermo-mechanical stress testing and degradation, for which we investigate the impact of the degradation on the modules light I-V curve parameters, and equivalent solar cell model parameters. Experimental validation of the method on the modules tested shows good agreement between the in-situ estimated power degradation and the flash test measured power loss of the modules, of up to 4.31 % error (RMSE), as the modules experience primarily junction defect recombination and increased series resistance losses. However, the application of the method will be limited for modules experiencing extensive photo-current degradation or delamination, which are not well reflected in the dark I-V characteristic of the PV module.

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Modeling, imaging and resistance analysis for crystalline silicon photovoltaic modules failure on thermal cycle test

Cited by 12 publications

References 13 publications

Radiometric Infrared Thermography of Solar Photovoltaic Systems: An Explainable Predictive Maintenance Approach for Remote Aerial Diagnostic Monitoring

Radiometric Infrared Thermography of Solar Photovoltaic Systems: An Explainable Predictive Maintenance Approach for Remote Aerial Diagnostic Monitoring

Influence of Monitor Current on Electrical Performance of Photovoltaic Module (PERC/HJT/Topcon) in Thermal Cycle Test

In-Situ Measurement of Power Loss for Crystalline Silicon Modules Undergoing Thermal Cycling and Mechanical Loading Stress Testing

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