Improved Singular Value Decomposition for Faulty Feeder Detection in Resonant Grounding Distribution System

In a resonant grounding distribution system (RGDS), the transient zero-sequence current component generated by single-phase-to-ground fault (SPGF) has unique modal characteristics, which is affected by fault initial angles. However, the complex working environment of distribution system complicates the extraction of transient components, especially under high noise levels. Singular value decomposition (SVD) is an effective technique to separate signal components from noise, while the effective singular values are the primary determinant of the separation accuracy. To improve the effective signal separation accuracy, a faulty feeder detection method based on improved SVD is proposed. By analyzing the transient features of zero-sequence current under different fault initial angles, an efficient singular value feature extraction method focusing on proper singular value order selection is developed. Furthermore, the similarity feature of the exponential decay sinusoidal components of zero-sequence current is integrated to achieve faulty feeder detection. Simulation and field tests validate the effectiveness of the proposed method under different fault initial angles. When the signal-to-noise ratio (SNR) exceeds 5 dB, the feeder detection accuracy exceeds 92.5%, which is 47% higher than that of traditional method. Moreover, the proposed method shows excellent robustness under high noise levels.