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

被引:113
作者
Livera, Andreas [1 ]
Theristis, Marios [1 ]
Makrides, George [1 ]
Georghiou, George E. [1 ]
机构
[1] Univ Cyprus, Dept Elect & Comp Engn, FOSS Res Ctr Sustainable Energy, PV Technol Lab, CY-1678 Nicosia, Cyprus
关键词
Failure detection; Classification of failures; Data analytic; Grid-connected systems; Photovoltaics; ONLINE FAULT-DETECTION; SILICON SOLAR-CELLS; PV SYSTEMS; INDUCED DEGRADATION; DETECTION ALGORITHM; MODULES; PLANTS; MODELS; LIGHT;
D O I
10.1016/j.renene.2018.09.101
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:126 / 143
页数:18
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