High-Impedance Fault Detection Method Based on Stochastic Resonance For a Distribution Network With Strong Background Noise

When a high-impedance fault (HIF) occurs in a distribution network, the fault current is very weak and can be easily confused with capacitor switching (CS), load switching (LS) or inrush current (IC). This can lead to an inaccurate judgment of current protection. Furthermore, when the external noise is too strong, the above problems become more prominent. To address these problems, this paper, based on the build-up characteristics of HIF current, proposes a novel method combining stochastic resonance (SR) using noise and variational mode decomposition (VMD). First, SR is used to detect the transient zero-sequence current in strong background noise and obtain the output current. Second, VMD is adopted to decompose the output current, and low-frequency and high-frequency intrinsic mode functions (IMFs) are obtained. Then, kurtosis and skewness values are calculated to construct the starting and identification criteria, respectively. Finally, when the kurtosis value is greater than 3.0, the protection device is started, and then, when the skewness value is less than 0, that is, when negative skewness occurs, it is judged as a HIF; conversely, when the skewness value is greater than 0, that is, when positive skewness occurs, it is judged as CS, LS or IC. A large number of tests show that the method can realize accurate identification in strong background noise with an SNR = −10 dB.