Abstract: When a single-phase grounding fault occurs in a small current grounding system, the amplitude of the fundamental zero-sequence current is large and the fault characteristics are obvious, resulting in a high accuracy of the zero-sequence current fault line selection method. However, the compensation effect of the arc suppression coil can cause the zero-sequence current line selection method to fail, limiting its application. To solve the problem that existing zero-sequence current fault line selection methods cannot be applied to small current grounding systems with neutral grounding through arc suppression coils, a new fault line selection method for single-phase grounding faults in small current grounding systems based on big data modeling is proposed. Firstly, the fault characteristics of single-phase grounding faults in small current grounding systems are summarized, and the existing main fault line selection methods are reviewed. Analysis indicates that the compensation effect of the arc suppression coil is the main reason limiting the application scenarios of the fundamental zero-sequence current line selection method. Based on these, a big data model is introduced to form characteristic data for the lines, thereby distinguishing between normal and faulty lines and achieving accurate line selection for single-phase grounding faults in small current grounding systems. The results of case studies demonstrate the feasibility and effectiveness of the proposed method.