The impact of cracks on photovoltaic power performance

Dhimish, Mahmoud; Holmes, Violeta; Mehrdadi, Behrooz; Dales, Mark

doi:10.1016/j.jsamd.2017.05.005

Cited by 74 publications

(47 citation statements)

References 14 publications

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“…This paper presents a micro cracks solar cell detection setup using the conventional EL imaging procedure. The EL process has been previously discussed in former articles such as [7] and [17]; for ease of visualizing, a typical EL imaging setup is shown in Fig. 1(a).…”

Section: Ultra-fast High-resolution Solar Cell Cracksmentioning

confidence: 99%

Ultrafast High-Resolution Solar Cell Cracks Detection Process

Dhimish

Mather

2020

IEEE Trans. Ind. Inf.

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This paper presents the advancement of an ultrafast high-resolution cracks detection in solar cells manufacturing system. The aim of the developed process is to (i) improve the quality of the calibrated image taken by a low-cost conventional electroluminescent (EL) imaging setup, (ii) proposing a novel methodology to enhance the speed of the detection of the solar cell cracks, and finally (iii) 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 0.1s to 0.3s, excluding the EL imaging time.

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Section: Ultra-fast High-resolution Solar Cell Cracksmentioning

confidence: 99%

Ultrafast High-Resolution Solar Cell Cracks Detection Process

Dhimish

Mather

2020

IEEE Trans. Ind. Inf.

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“…36,37 During severe discoloration a total loss of ~10% is observed which implies that EVA discoloration is absurd for a complete failure of silicon modules. Dhimish et al 38 reviewed various types of cell cracks and their effects and proposed a statistical analysis-based approach to identify them. The observations revealed about the various types of cracks namely Multi Directional Cracks, Diagonal cracks, and cracks which are parallel and perpendicular to bus bars.…”

Section: Review Of Failures Found In Silicon Wafer-based Pv Modulesmentioning

confidence: 99%

Fault diagnosis of Photovoltaic Modules

Haque

Bharath

Khan

et al. 2019

Energy Science & Engineering

101

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Fault diagnosis and condition monitoring are important to increase the efficiency and reliability of photovoltaic modules. This paper reviews the challenges and limitations associated with fault diagnosis of solar modules. A thorough analysis of various faults responsible for failure of solar modules has been discussed. After reviewing relevant work, a monitoring tool is designed using thermography and artificial intelligent systems that allows the detection of various types of faults in PV modules and at the same time the designed tool aims to filter the nonsignificant anomalies. A neural network (NN) classifier is applied to the transfer characteristics (I‐V data) of the faulty PV module for the diagnosis which adapts multilayer perceptron (MLP) networks to identify the type and location of occurring faults. The Discrete wavelet transform (DWT) based signal processing technique is utilized in the feature extraction process to reduce the NN input size. The developed detection algorithm is adapted for 24/7 automated surveillance. For a given fault condition, the average fault detection time is observed to be <9 seconds, which is lower than the previous work done. The developed algorithm achieved 100% accuracy when tested on a predetermined fault data set.

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“…The hot-spots are also the key reason of enhanced PV degradation, and occasionally permanent damage of a complete PV panels [4]. There are a number of other reliability problems affecting PV panels such as discontinuation [5], maximum power point tracking (MPPT) faults [6] and [7], micro-cracks [8], and variations in the wind speed and humidity [9]. All of these factors affect the PV panels output power performance and its main electrical parameters such as temperature coefficient, hence diminution its annual energy production.…”

Section: Introductionmentioning

confidence: 99%

Photovoltaic Hot-Spots Fault Detection Algorithm Using Fuzzy Systems

Dhimish

Badran

2019

IEEE Trans. Device Mater. Relib.

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Faults in photovoltaic (PV) modules, which might result in energy loss and reliability problems are often difficult to avoid, and certainty need to be detected. One of the major reliability problems affecting PV modules is hot-spotting, where a cell or group of cells heats up significantly compared to adjacent solar cells, hence decreasing the optimum power generated. In this article, we propose a fault detection of PV hot-spots based on the analysis of 2580 PV modules affected by different types of hot-spots, where these PV modules are operated under various environmental conditions, distributed across the UK. The fault detection model comprises a fuzzy inference system (FIS) using Mamdani-type fuzzy controller including three input parameters, namely, percentage of power loss (PPL), short circuit current (Isc), and open circuit voltage (Voc). In order to test the effectiveness of the proposed algorithm, extensive simulation and experimental-based tests have been carried out; while the average obtained accuracy is equal to 96.7%.

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The impact of cracks on photovoltaic power performance

Cited by 74 publications

References 14 publications

Ultrafast High-Resolution Solar Cell Cracks Detection Process

Ultrafast High-Resolution Solar Cell Cracks Detection Process

Fault diagnosis of Photovoltaic Modules

Photovoltaic Hot-Spots Fault Detection Algorithm Using Fuzzy Systems

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