Diagnosis Method for Electrical Internal Faults in Wind Farms Considering Cable Faults
A wind farm electrical internal fault diagnosis scheme considering cable faults was proposed to address the strong lag and high operating costs of traditional wind farm maintenance schemes.Firstly,the Fourier decomposition algorithm was used to preliminarily process the fault signal of the wind farm,obtaining the Fourier intrinsic band functions(FIBFs)and residual signal,ensuring the stability of the fault signal and facilitating subsequent identification;the graph convolutional neural network was improved for fault identification and diagnosis,and a series model of fault information was designed to classify the faults.Combined with cost sensitive learning,the classification results were adjusted to ensure that the system can still achieve fault diagnosis for wind farms with less samples.The experimental results show that the proposed scheme can effectively identify and diagnose electrical internal faults in wind farms with strong anti-interference ability,and is not easily affected by noise with a fault identification accuracy of 96％.
万方数据
维普
