Synchro-Squeezing Transform for High-Impedance Fault Detection in Power Distribution Systems

Distribution systems are most vulnerable to high-impedance faults (HIFs). These types of faults occur when the primary electrical conductor fails or comes into contact with high-impedance substances, such as asphalt, grass, sand, concrete, etc. The magnitude of fault current is particularly low for certain grounding materials due to the nonlinear and high impedance of resistive surfaces. As a result, traditional overcurrent relays usually fail to operate, which may lead to fire hazards. Also, they are unable to detect the characteristics of HIF accurately, leading to maloperation. The motive of this work is to overcome the above-mentioned challenges of conventional relays. This article proposes a linear time-frequency wavelet-based tool called synchro-squeezing transform (SST) for the distortion detection of HIF in power distribution networks. This study uses wavelet SST to redistribute signal energy in the frequency domain. The wavelet SST is applied to the measured phase current signal for maximum time-frequency ridge extraction. Then, the inverse SST operation is performed to reconstruct the signal from the time-frequency domain. The reconstruction error is calculated between the original signal and the reconstructed signal. The reconstruction error value is compared with the base value to discriminate HIF from other non-HIF events. The impact of distributed generation on HIF features are further explored by EV penetration in the RSCAD distribution system and validated on the IEEE-13 node test feeder using RTDS. The main contributions of the proposed method are viz., it can correctly distinguish HIF from severe faults, switching events, energization scenarios, and noisy environments. The algorithm has been compared with the previously reported HIF detection techniques, and the efficacy of SST is presented through real-time simulation results. SST has a fast detection time and less computation burden.