期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2018
卷号：170
期号：4
页码：042009
DOI：10.1088/1755-1315/170/4/042009
语种：English
出版社：IOP Publishing
摘要：This paper describes a fault diagnosis method of photovoltaic (PV) module, which bases on equivalent circuit module and probabilistic neural network (PNN). The output characteristics of the PV module under normal, dust deposition, abnormal aging and partial shading conditions are simulated by using the equivalent circuit model. The simulated data are used as characteristic parameters to fault type diagnosis. The performance of the fault diagnosis model is evaluated, and the results indicate that the method can detect the fault types correctly.
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