Inspection and condition monitoring of large-scale photovoltaic power plants: A review of imaging technologies

Høiaas, Ingeborg Eriksdatter; Grujić, Katarina; Imenes, Anne Gerd; Burud, I.; Olsen, Espen; Belbachir, Nabil

doi:10.1016/j.rser.2022.112353

Cited by 56 publications

(18 citation statements)

References 64 publications

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“…Measurements can also be conducted at the module level, but this requires identifying, locating and disassembling a faulty module. This is time-consuming and costly [4,6]. In addition, the exact location of the fault is not provided, as current and voltage sensors have a limited ability to pinpoint the cause of the power loss [3,7,8].…”

Section: Introductionmentioning

confidence: 99%

A review of imaging methods for detection of photoluminescence in field-installed photovoltaic modules

Vuković,

Wiig,

dos Reis Benatto

et al. 2024

Prog. Energy

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It is predicted that the photovoltaic energy conversion will be the largest installed power capacity by 2027. The least costly option for new electricity generation in many of the world’s countries will be the utility-scale solar photovoltaic electricity generation. Accurate monitoring of solar plants for localizing and detecting faults is expected to be one of the critical tasks facing the energy industry. Imaging of photovoltaic modules for the purpose of fault detection can be more efficient and accurate compared to measurements of electrical parameters. Different spectral regions provide different types of information about a faulty module. Detection of photoluminescence, that is, radiation emitted upon band-to-band recombination after charge carrier excitation with an illumination source, has shown a great potential in the laboratory setting. In the recent years, the first approaches in the outdoor setting have been conducted on silicon modules with the Sun and a LED module as excitation source. The present study sums up the different methods for outdoor photoluminescence imaging and emphasizes their differences regarding filtering of the reflected light from the photoluminescence signal. The different types of photoluminescence images obtained from each method and the image processing algorithms are described. Finally, the interpretation of the different types of photoluminescence images is addressed.

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Section: Introductionmentioning

confidence: 99%

A review of imaging methods for detection of photoluminescence in field-installed photovoltaic modules

Vuković,

Wiig,

dos Reis Benatto

et al. 2024

Prog. Energy

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“…Recent trends in global climate policy stimulated a dramatic growth of photovoltaic (PV) deployment with an expected level of tens of terawatts worldwide to be reached in one to two decades. , This enormous growth serves as a locomotive for the development of associate technologies in the production, monitoring, and recycling of PV modules. In particular, the expected TW scale of PV installations requires efficient high-throughput procedures for automated characterization of the status of deployed PV modules, their integrity, performance, and state of degradation. − The most promising technologies for the high-throughput characterization include different imaging techniques, such as thermography, − electroluminescence (EL), , and photoluminescence (PL) imaging, , which can be realized on automated moving/flying platforms and provide essential information on the module performance and type/population of defects.…”

Section: Introductionmentioning

confidence: 99%

Identification of the Backsheet Type of Silicon Photovoltaic Modules from Encapsulant Fluorescence Images

Stroyuk

Güttler

Buerhop‐Lutz

et al. 2023

ACS Appl. Energy Mater.

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Feasibility of the identification of backsheet (BS) composition of field-aged Si photovoltaic (PV) modules based on the analysis of characteristic patterns of UV-excited fluorescence (UVF) of ethylene vinyl acetate copolymer encapsulant is shown. The approach includes BS identification by vibrational spectroscopies and the formation of a database of BS-related characteristic UVF patterns. A multivariate principal component analysis of the UVF images of unknown samples combined with the UVF pattern database allows the BS type to be identified only from UVF images. The geometric place of particular samples in the principal component plots is indicative of the general degradation status of PV modules. The proposed method can be applied for high-throughput noncontact characterization of solar PV plants.

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“…As the energy generated from PV systems increases, many reliable issues related to field-installed PVs are intensifying, such as premature aging and electrical system failure. [8,9] Consequently, the operation and maintenance (O&M) of installed PV systems have become essential to harvesting more energy. The O&M processes aim to detect and classify faults quickly and accurately, ensuring the reliable performance of PV systems.…”

Section: Introductionmentioning

confidence: 99%

Real‐Time Detection and Classification of Bypass Diode‐Related Faults in Photovoltaic Modules via Thermoelectric Devices

Ko,

Kim,

Lee

et al. 2023

Adv Materials Technologies

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The accurate detection and classification of faults in photovoltaic (PV) systems contribute to enhancing their performance. Bypass diode (BD) heating is a common issue afflicting field‐installed PV modules. Although different fault modes exist, they exhibit similar characteristics, which hinder their early detection and classification. Thus, a real‐time fault detection and classification method for heated BDs in PV modules using thermoelectric devices (TEs) is proposed. When PV modules experience partial shading (PS) or exhibit bypass diode faults (BDFs), the temperature of the BD rises. By attaching a TE to the BD, the heat generated due to the PS or BDF can be converted into electrical energy. Additionally, the cause of bypass heating can be classified in real time by analyzing the TE's power‐generation capacity, considering the inverter status and ambient conditions. For example, the power generated by the TE is in the ranges of 8.5–14.7 (PS) and 28–49.4 mW cm−2 (BDF) under operating conditions. Moreover, the power generated by the TE under the PS and BDF conditions is sufficiently high to drive a communication system, guaranteeing the reliability of the detection system. Therefore, the proposed bypass heating detection system can classify the fault modes of PV systems in real time without external power.

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Inspection and condition monitoring of large-scale photovoltaic power plants: A review of imaging technologies

Cited by 56 publications

References 64 publications

A review of imaging methods for detection of photoluminescence in field-installed photovoltaic modules

A review of imaging methods for detection of photoluminescence in field-installed photovoltaic modules

Identification of the Backsheet Type of Silicon Photovoltaic Modules from Encapsulant Fluorescence Images

Real‐Time Detection and Classification of Bypass Diode‐Related Faults in Photovoltaic Modules via Thermoelectric Devices

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