Research on single-phase grounding fault detection method based on vision transformer

Abstract

In China's power distribution network, low-current grounding is mainly used. Single-phase ground fault is one of the most common faults in the low-current grounding mode. If effective measures are not taken in a timely manner when a single-phase ground fault occurs in the distribution network, it will pose a safety threat to pedestrians and inspection personnel. In serious cases, it can also affect the stable operation of the power grid system, cause power outages in other areas, and lead to even greater safety hazards. In order to detect the occurrence of single-phase ground faults in the lowcurrent grounding mode of the distribution network, this paper proposes a new single-phase ground fault detection method based on the vision transformer algorithm, combined with the steady-state characteristics of zero-sequence current. First, the zero-sequence current data of the line where the single-phase ground fault occurred is sampled. Secondly, the time-series zero-sequence current data is transformed into a two-dimensional image using the Gramian Angular Field (GAF) method. Finally, the transformed two-dimensional image is classified using the vision transformer algorithm to achieve the purpose of detecting the occurrence of single-phase ground faults. The algorithm was verified on an experimental platform, and the results show that the proposed algorithm can effectively detect single-phase ground faults in the low-current grounding mode of the distribution network.