Simultaneous fault detection algorithm for grid‐connected photovoltaic plants

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

doi:10.1049/iet-rpg.2017.0129

Cited by 57 publications

(25 citation statements)

References 25 publications

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“…As the developed algorithm relies on the MPPT tolerance rate, based upon data available in the manufacturer datasheet, the tolerance rate equals to 2% has been included in the algorithm to calculate the faulty regions (including VKnee/Vmpp thresholds) as shown in Fig. 7(b) [20]. In fact, this figure contains all the analysis of the developed algorithm and its theoretical development has been discussed earlier in section III.…”

Section: A Examined Pv Modules Configurationmentioning

confidence: 99%

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Novel Open-Circuit Photovoltaic Bypass Diode Fault Detection Algorithm

Dhimish

Chen

2019

IEEE J. Photovoltaics

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In this paper, a novel photovoltaic (PV) bypass diode fault detection algorithm is presented. The algorithm consists of three main steps. First, the threshold voltage of the I-V curve is obtained using different failure bypass diode scenarios. Second, the theoretical prediction for the faulty regions of bypass diodes is calculated using the analysis of voltage drop in the I-V curve as well as the voltage at maximum power point. Lastly, the actual I-V curve under any environmental condition is measured and compared with theoretical predictions. The proposed algorithm has been experimentally evaluated using a PV string that comprises three series-connected PV modules, and subtotal nine bypass diodes. Various experiments have been conducted under diverse bypass diodes failure conditions. The achieved detection accuracy is always greater than 99.39% and 99.74% under slow and fast solar irradiance transition respectively.

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Section: A Examined Pv Modules Configurationmentioning

confidence: 99%

“…Nevertheless, there are limited number of PV fault detection algorithms that can detect failures of the bypass diodes integrated in PV modules. Certainly, [20] - [22] attempts to detect faults associated with bypass didoes. However, their detection accuracy for this particular type of PV fault is ranging from 70% to 95%.…”

Section: Introductionmentioning

confidence: 99%

Novel Open-Circuit Photovoltaic Bypass Diode Fault Detection Algorithm

Dhimish

Chen

2019

IEEE J. Photovoltaics

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“…Other methods of PV fault detection are based on the comparison of simulated and measured efficiencies by analyzing losses on the DC side of the GCPV [16,17]. In addition, Silvestre et al [18] offers a new defect detection procedure in GCPV systems, based on the evaluation of current and voltage indicators.…”

Section: Introductionmentioning

confidence: 99%

Robust Method for Diagnosis and Detection of Faults in Photovoltaic Systems Using Artificial Neural Networks

Djalab

Rezaoui

Mazouz

et al. 2020

Period. Polytech. Elec. Eng. Comp. Sci.

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During their operation, PV systems can be subject of various faults and anomalies that could lead to a reduction in the effectiveness and the profitability of the PV systems. These faults can crash, cause a fire or stop the whole system. The main objective of this work is to present a sophisticated method based on artificial neural networks ANN for diagnosing; detecting and precisely classifying the fault in the solar panels in order to avoid a fall in the production and performance of the photovoltaic system. The work established in this paper intends in first place to propose a method to detect possible various faults in PV module using the Multilayer Perceptron (MLP) ANN network. The developed artificial neural network requires a large database and periodic training to evaluate the output parameters with good accuracy. To evaluate the accuracy and the performance of the proposed approach, a comparison is carried out with the classic method (the method of thresholding). To test the effectiveness of the proposed approach in detecting and classifying different faults, an extensive simulation is carried out using Matlab SIMULINK.

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“…Other reliability issues in PV modules such as PV micro cracks [9], PV module disconnection [10], maximum power point tracking (MPPT) efficiency [11], and PV wind speed and humidity variations [12]. These factors can affect the PV modules output power performance, thus decrease its annual yield energy.…”

Section: Introductionmentioning

confidence: 99%