Usage of non-invasive technique to diagnose a photovoltaic plant

dc.contributor.authorEsposito, Marcelo
dc.contributor.authorCalegari, Renato
dc.contributor.authorGuerreiro Marques, Joaquim
dc.contributor.authorMesbahi, Oumaima
dc.contributor.authorTlemçani, Mouhaydine
dc.date.accessioned2025-06-17T10:02:51Z
dc.date.available2025-06-17T10:02:51Z
dc.date.issued2024-08-22
dc.description.abstractThe present work utilizes an intelligent technique to lower photovoltaic systems’ operating and maintenance costs. In 2013, inverter manufacturer Huawei pioneered this concept with the development of multi-MPPT (Maximum Power Point Tracking) string inverters covering 14 different types of faults of photovoltaic systems. So far, the main advantage that the authors of this work have identified when using Huawei’s “Smart I-V Curve Diagnosis” function is the ease with which mismatch situations can be perceived and located in the photovoltaic plant, without having to install individual optimizers in each of the modules. This methodology required a specific data logger and a software license. Additionally it is only available for large inverters, over 100 kW. The “Smart” function indicates the faulty string. To identify the damaged module, the authors used thermographic images. The diagnostic approach showed that all strings achieved the nominal. Fill Factor (FF) of 78%. Commissioning tests concluded all strings were normal, but I4S1 and I4S2 tests required repetition due to their unique configuration. A fault in module 1 of I4S7, undetected during commissioning, was later confirmed by Smart I-V Curve Diagnosis and infrared thermography.por
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dc.identifier.doihttps://doi.org/10.1080/15567036.2024.2392041por
dc.identifier.urihttps://www.tandfonline.com/doi/figure/10.1080/15567036.2024.2392041?scroll=top&needAccess=true
dc.identifier.urihttp://hdl.handle.net/10174/38725
dc.language.isoporpor
dc.peerreviewednopor
dc.publisherTaylo & Francispor
dc.rightsrestrictedAccesspor
dc.subjectPhotovoltaicpor
dc.subjectinverterpor
dc.subjectdiagnosispor
dc.subjectintelligencepor
dc.subjectartificialpor
dc.titleUsage of non-invasive technique to diagnose a photovoltaic plantpor
dc.typearticle

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