On fault detection in a grid-connected photovoltaic system under two different operating modes

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dc.contributor.authorHarkane, Mohamed Amine
dc.contributor.authorKouadri, Abdelmalek (Supervisor)
dc.contributor.authorBakdi, Azzeddine (Supervisor)
dc.date.accessioned2022-01-18T11:18:32Z
dc.date.available2022-01-18T11:18:32Z
dc.date.issued2018
dc.description54 p.en_US
dc.description.abstractThis project proposes an efficient fault detection method based on process history method using Principal Component Analysis (PCA) technique in dimension reduction and feature extraction for Grid Connected PhotoVoltaic System (GCPV) labeled data. The Fault Indicator (FI) developed in this work is an elliptic threshold based on the gaussian distribution of Normal Operation Condition (NOC) of the two different operating modes, Maximum Power Point Tracking (MPPT) and Power Rating (PR), of the system. The proposed fault detection method has been validated experimentally by the evaluation of the False Alarms Rate (FAR), Fault Detection Rate (FDR) and the Detection Delay (DD).The resultsen_US
dc.description.sponsorshipUniversité M'Hamed Bougara Boummerdes : Institut genie électrique et électroniqueen_US
dc.identifier.urihttps://dspace.univ-boumerdes.dz/handle/123456789/7567
dc.language.isoenen_US
dc.subjectFault detectionen_US
dc.subjectFault Detection and Diagnosisen_US
dc.subjectGCPV Systemen_US
dc.titleOn fault detection in a grid-connected photovoltaic system under two different operating modesen_US
dc.typeThesisen_US

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