Fault Ranking in PV Module based on Artificial Intelligence Technique (AIT)

Perveen, Sana; Ashfaq, Haroon; Asjad, Mohammad

doi:10.1109/icpeca47973.2019.8975619

2019 International Conference on Power Electronics, Control and Automation (ICPECA) 2019

DOI: 10.1109/icpeca47973.2019.8975619

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Fault Ranking in PV Module based on Artificial Intelligence Technique (AIT)

Sana Perveen

Haroon Ashfaq

Mohammad Asjad

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Cited by 2 publications

(2 citation statements)

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“…In [8] the authors have classified faults for the PV module based on artificial intelligence technology. They applied fuzzy logic to evaluate the critical fault of the PV module, according to its arrangement.…”

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confidence: 99%

Photovoltaic fault diagnosis algorithm using fuzzy logic controller based on calculating distortion ratio of values

Lahiouel

Latrèche

Khemliche

et al. 2023

Electrical Engineering & Electromechanics

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Introduction. The efficiency of solar energy systems in producing electricity in a clean way. Reliance on it in industrial and domestic systems has led to the emergence of malfunctions in its facilities. During the operating period, these systems deteriorate, and this requires the development of a diagnostic system aimed at maintaining energy production at a maximum rate by detecting faults as soon as possible and addressing them. Goal. This work proposes the development of an algorithm to detect faults in the photovoltaic system, which based on fuzzy logic. Novelty. Calculate the distortion ratio of the voltage and current values resulting from each element in the photovoltaic system and processing it by the fuzzy logic controller, which leads to determining the nature of the fault. Results. As show in results using fuzzy logic control by calculating the distortion ratio of the voltage and current detect 12 faults in photovoltaic array, converter DC-DC and battery.

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confidence: 99%

Photovoltaic fault diagnosis algorithm using fuzzy logic controller based on calculating distortion ratio of values

Lahiouel

Latrèche

Khemliche

et al. 2023

Electrical Engineering & Electromechanics

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show abstract

“…The system monitors the function of equipment and alerts users when maintenance is required. In [5], fault ranking in a solar standalone system based on AI technology is developed. The developed intelligent technique focusses on the reliability and safety of the integrated photovoltaic system and reduces the risk of fault by taking prior corrective action.…”

mentioning

confidence: 99%

Applying AI in Power Electronics for Renewable Energy Systems [Expert View]

Sitharthan

2020

IEEE Power Electron. Mag.

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Fault Ranking in PV Module based on Artificial Intelligence Technique (AIT)

Cited by 2 publications

References 20 publications

Photovoltaic fault diagnosis algorithm using fuzzy logic controller based on calculating distortion ratio of values

Photovoltaic fault diagnosis algorithm using fuzzy logic controller based on calculating distortion ratio of values

Applying AI in Power Electronics for Renewable Energy Systems [Expert View]

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