Automatic detection of faults in a photovoltaic power plant based on the observation of degradation indicators

Labar Hocine, Kelaiaia Mounia Samira, Mesbah Tarek, Necaibia Salah and Kelaiaia Samia

Renewable Energy, 2021, vol. 164, issue C, 603-617

Abstract: PV modules are costly devices, so, their lifetime is an important parameter in the investment evaluation. The aim of this paper is to propose an earlier degradation detection that affects glass, EVA, wires etc … Where many researchers propose degradation evaluation based on scheduled eye observation, which becomes problematic for large scale PV power production, because it takes much more time and mobilizes skilled workers. This type of degradation evaluation is very expensive and must be carried out by expert workers. To automate PV panels self evaluation, the degradations models are embedded in a microcontroller as software which operates with instantaneous measured parameters. The degradation phenomena of each PV module’s element are also presented and discussed. For this purpose an Observing Degradation System (ODS) program is proposed and detailed, based on modeling of each recognized degradation. Where new parameters are introduced to improve the fault type detection. This recognition method of degradation types based on P–V characteristics and checklist is developed and successfully tested.

Keywords: PV module; Degradation; EVA; MPPT; Faults detection (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:164:y:2021:i:c:p:603-617

DOI: 10.1016/j.renene.2020.09.094

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