Recent advances in failure diagnosis techniques based on performance data analysis for grid-connected photovoltaic systems

Andreas Livera, Marios Theristis, George Makrides and George E. Georghiou

Renewable Energy, 2019, vol. 133, issue C, 126-143

Abstract: Over the last decade, research into photovoltaic (PV) technology has shifted from a race for the highest efficiency to the increase of the performance reliability in the field. A major part of current research activities focuses on the reliability of the installations and the guaranteed lifetime output through constant, solid and traceable PV plant monitoring. In this domain, several PV monitoring strategies for the early diagnosis of failures in grid-connected PV systems have been proposed in the literature and this study seeks to provide an overview of all the data analytic methods used by the research community and industry for the detection and classification of failures from acquired performance data of grid-connected PV systems. Insight into the performance monitoring requirements (parameters and resolution) for the detection of failures in monitored PV systems, as well as the various techniques used for their classification is also provided. Finally, this overview covers the data analytic methods based on electrical signature, numerical and statistical analysis and are summarised according to the type of failure, input requirements and validation procedure.

Keywords: Failure detection; Classification of failures; Data analytic; Grid-connected systems; Photovoltaics (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (25)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:133:y:2019:i:c:p:126-143

DOI: 10.1016/j.renene.2018.09.101

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