Automatic Fault Detection Method for Photovoltaic Grid Connected Inverters Based on Wavelet Neural Network
In order to improve the operational quality and ensure the safety of photovoltaic grid connected inverters,a research on automatic fault detection method for photovoltaic grid connected inverters was carried out using wavelet neural networks.Firstly,configure a data acquisition system to collect data from photovoltaic grid connected inverters.Then,use the collected operational data to extract fault features of the inverter power supply and output the extracted feature parameters.Finally,based on this,a wavelet neural network is constructed,and a diagnostic function is designed to determine whether there is a fault in the inverter according to the output of the network.The results show that after applying the proposed method,the detection results of output voltage and output current of inverters with different fault state types are basically consistent with the actual values,with high detection accuracy.It can accurately identify the operating status of inverters and detect specific fault types.
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维普
