Fault identification in crystalline silicon PV modules by complementary analysis of the light and dark current–voltage characteristics

Spataru, Sergiu; Séra, Dezső; Hacke, Peter; Kerekes, Tamás; Teodorescu, Remus

doi:10.1002/pip.2571

Cited by 33 publications

(23 citation statements)

References 32 publications

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“…The I–V curve of PV modules is an important characteristic tool to evaluate the electrical performance of a PV module [13]. Two portable I–V tracers are used in the survey to record data of multiple PV modules in parallel.…”

Section: Case Study Methodologymentioning

confidence: 99%

Case study of PV output power degradation rates in Oman

Honnurvali¹,

Gupta

Goh

et al. 2018

IET Renewable Power Generation

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To meet the increase in peak electricity demand and to reduce fossil fuel emissions in Oman and as an initiative taken by the government, by 2030, 15% (3000 MW) of the total energy mix (20,000 MW) should be generated from renewable energy resources like Solar and wind etc. It is crucial for the stakeholders and PV enthusiast to predict the return on investments and its performance in the local climatic conditions. In this paper, a case study has been presented where PV modules of different technologies, age and installed in different climatic conditions of Oman are studied. The results showed that the output power degradation for all modules is around 1.96%/year which is almost double compare to the European countries. Electrical analysis of different PV technologies showed that multi-crystalline silicon technology installed in hot and dry climate is degrading (around 2.54%/year) faster, while thin-film technology (CdTe) has shown lowest degradation (average of 0.8%/year) compare to any other PV technology. Furthermore, IR image analysis showed that presence of hot cells in PV modules are also a significant contributing factor in PV degradation rates. Severity of interconnect breakage (SIB) tests confirms the increase of the series-resistance of PV modules which is also a significant contributing factor for reduction in short-circuit current and thus PV maximum output power.

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Section: Case Study Methodologymentioning

confidence: 99%

Case study of PV output power degradation rates in Oman

Honnurvali¹,

Gupta

Goh

et al. 2018

IET Renewable Power Generation

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“…2017, 7, 1199 2 of 13 circuit faults in photovoltaic systems based on the evaluation of three coefficients is presented. By analyzing the light and dark current-voltage (I-V) characteristics of the photovoltaic module, a fault identification method was used to distinguish the faulty photovoltaic modules [8]. The above-mentioned methods are for the photovoltaic modules, of which each photovoltaic module needs to be monitored, leading to high costs.…”

Section: Analysis Of Internal Parameters Of Photovoltaic Array Equivamentioning

confidence: 99%

Fault Diagnosis Model of Photovoltaic Array Based on Least Squares Support Vector Machine in Bayesian Framework

Sun

Fan

et al. 2017

Applied Sciences

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Abstract:With the rapid development of the photovoltaic industry, fault monitoring is becoming an important issue in maintaining the safe and stable operation of a solar power station. In order to diagnose the fault types of photovoltaic array, a fault diagnosis method that is based on the Least Squares Support Vector Machine (LSSVM) in the Bayesian framework is put forward. First, based on the elaborate analysis of the change rules of the output electrical parameters and the equivalent circuit internal parameters of photovoltaic array in different fault states, the input variables of the photovoltaic array fault diagnosis model are determined. Second, through the LSSVM algorithm in the Bayesian framework, the fault diagnosis model based on the output electrical parameters and the equivalent circuit internal parameters of the photovoltaic array is built, which can effectively detect the photovoltaic array faults of short circuit, open circuit, and abnormal aging. Then, the simulation model is built to verify the validity of the LSSVM algorithm in the Bayesian framework by comparing it with the model of LSSVM and the Support Vector Machine (SVM). Moreover, a 5 × 3 photovoltaic array and a reference photovoltaic string are established and experimentally tested to validate the performance of the proposed method.

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“…Potential-induced degradation (PID) has recently attracted considerable attention owing to its significant negative impact on the performance of photovoltaic (PV) systems. 1 It is considered that massive power losses in megawatt PV systems are related to the strong detrimental impact of PID. 2 Associated with the higher potential distress originating in PV systems, PID is distinctly different from other causes of module efficiency deterioration.…”

Section: Introductionmentioning

confidence: 99%

“…Potential‐induced degradation (PID) has recently attracted considerable attention owing to its significant negative impact on the performance of photovoltaic (PV) systems . It is considered that massive power losses in megawatt PV systems are related to the strong detrimental impact of PID .…”

Section: Introductionmentioning

confidence: 99%

Transient carrier recombination dynamics in potential‐induced degradation p‐type single‐crystalline Si photovoltaic modules

Islam

Matsuzaki

Okabayashi

et al. 2019

Progress in Photovoltaics

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In this study, we investigated the recombination dynamics of minority carriers through the decay profile analysis of transient diffuse reflectance spectroscopy (TDRS) for fresh and potential‐induced degradation (PID) modules. The PID‐affected region in terms of the degradation degree on the modules was firstly localized using conventional methods such as electroluminescence (EL) and lock‐in thermal images. The photogenerated carrier density and carrier lifetime were different in photovoltaic (PV) modules in fresh and PID modes. It was found that the dominant recombination involved the carrier transition via shallow trap states. The distribution of the trap states, however, was extended from the surface to the bulk of the solar cell due to Na ions–decorated defects. The behaviors of the carrier dynamics near the surface and bulk were very different, as inferred from the two different pump wavelengths of 532 and 1064 nm, respectively.

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Fault identification in crystalline silicon PV modules by complementary analysis of the light and dark current–voltage characteristics

Cited by 33 publications

References 32 publications

Case study of PV output power degradation rates in Oman

Case study of PV output power degradation rates in Oman

Fault Diagnosis Model of Photovoltaic Array Based on Least Squares Support Vector Machine in Bayesian Framework

Transient carrier recombination dynamics in potential‐induced degradation p‐type single‐crystalline Si photovoltaic modules

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