Novel Principal Harmonics-Based Arc Grounding Fault Detection Strategy in Resonant Grounding Distribution Network

The distribution network's arc grounding fault (AGF) significantly threatens personal and equipment safety. In resonant grounding distribution networks (RGDN), the distortion features commonly used for arc detection are altered by the frequency characteristic of the equivalent zero mode network, which will pose a considerable challenge to ensure the effectiveness of AGF detection and faulty feeder selection. To address the issues, this paper proposes a principal harmonic-based approach for AGF detection and faulty feeder selection in RGDN. The amplitude-frequency-phase characteristic of principal harmonics in arc current is analyzed in detail based on multi-model simulation to obtain more intuitive and compatible arc signatures. The relations in phase and amplitude of principal harmonics have been investigated and represented for constructing explicit signature sets of arc faults. Then, the distortion discrepancy between different measurement positions and their causes and influences was thoroughly investigated using reasonable equivalence and frequency characteristic analysis of the mode system. Moreover, to avoid misaligning AGF detection methods by fault signals in the outlet of feeders due to the variations of distortion features, the estimation equation of current at the fault point has been derived to obtain the signal more suitable for AGF detection. Furthermore, a novel strategy for AGF detection and faulty feeder selection has been designed combining Taylor-Fourier transform (TFT) based dynamic parameters extraction and the characteristic of principal harmonics. The effectiveness of the proposed strategy has been verified using simulation data and in-field data.