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：2019
卷号：227
期号：5
页码：052063
DOI：10.1088/1755-1315/227/5/052063
出版社：IOP Publishing
摘要：In order to improve the power generation efficiency of photovoltaic systems and to reduce the cost of manual maintenance, this paper proposes a fault diagnosis and operation and maintenance method based on BP neural network with data cloud acquisition. The causes of short circuit and abnormal aging failure of photovoltaic modules are analyzed. BP neural network fault diagnosis model is established in Matlab, combined with the mathematical model of photovoltaic components to simulate the output of various faults, performing sample training on the fault diagnosis model. The data collected by the distributed photovoltaic information processing and data analysis system platform is used as the input data of the neural network. According to the diagnosis result, reasonable suggestions for PV module operation and maintenance are provided from the aspects of component maintenance, photovoltaic panel cleaning, dip angle change, etc. Simulation results verify the correctness and effectiveness of the proposed method.
