Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/38725
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Title: | Usage of non-invasive technique to diagnose a photovoltaic plant |
Authors: | Esposito, Marcelo Calegari, Renato Guerreiro Marques, Joaquim Mesbahi, Oumaima Tlemçani, Mouhaydine |
Keywords: | Photovoltaic inverter diagnosis intelligence artificial |
Issue Date: | 22-Aug-2024 |
Publisher: | Taylo & Francis |
Abstract: | The 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. |
URI: | https://www.tandfonline.com/doi/figure/10.1080/15567036.2024.2392041?scroll=top&needAccess=true http://hdl.handle.net/10174/38725 |
Type: | article |
Appears in Collections: | DEM - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
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