Fault detection in photovoltaic power converter

Please use this identifier to cite or link to this item: https://dspace.univ-ouargla.dz/jspui/handle/123456789/30771

Title:	Fault detection in photovoltaic power converter
Authors:	KAFI, Mohamed Redouane KAFI, Omar Rafik ABDESSAMED, Zakaria
Keywords:	Faultdiagnosisbasedmachinelearning multicellularpowerconverter photovoltaicsystem nolinearcontrol
Issue Date:	2022
Abstract:	This workdealswithfaultdiagnosisofpowerconverterusedinphotovoltaicsystems whichsupplyandisolatedelectricloadandhowittransformthecurrentsafelytodevices. this thesistreatthemulticellularpowerconverterdescribehowmuchthepowerconverter failures influencetotheloadcurrentthemainfocusingisinthecapacitorsfaultswhich can affectbadlytotheloadcurrentssoitcanresultbadconsequencesondevices.which proposedasolutionforthisproblemusing(KNN)k-nearestneighbormachinelearning algorithm tobuildaclassificationmodelfordiagnosis.andusingtwomodesofcontrolin order tocompareintermofthefunctionunderfailures,loadcurrentpreservationand the smoothest,andintermoftheaccuracyoftheclassificationmodelbuilt.aswellas to usingtheslidingmodecontrolmodeandtheexactlinearizationmode,thisisforthe purposeofcomparisonintermsofsystemperformanceduringtheoccurrenceoffaults and theextentoftheirimpactontheloadcurrentbyexaminingtheshapeofitssignal and analyzingtherobustnessofthetwocontrolsinnotbeinggreatlyaffectedbythe faults andshowingit.
Description:	Automatic and systems
URI:	https://dspace.univ-ouargla.dz/jspui/handle/123456789/30771
Appears in Collections:	Département d'Electronique et des Télécommunications - Master

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