Fault Type Recognition of Over-head Lines of Distribution Networks Based on Fault Indicator Waveform Data

The waveform data recorded by fault indicators imply rich fault information, and effective information mining of the data can help grasp the distribution of line faults and make targeted measures in distribution networks. In this paper, a fault type identification method based on fault indicator data is proposed. With the consideration of fault indicators' characteristics, such as big error, low reliability of voltage measurement and saturation condition of measured current in short-circuit fault, the characteristics of waveform data in three-phase short circuit, phase-to-phase short circuit, phase-to-phase grounding fault and grounding fault are analyzed respectively. Based on the characteristics analysis, a multi-level fault type identification method is proposed, successfully identifying disturbance and fault, grounding fault and short-circuit fault, symmetrical short-circuit and unsymmetrical short-circuit, phase-to-phase fault and phase-to-phase grounding fault. The effectiveness of the fault type identification method proposed is verified by the field recording data collected by fault indicator. The method proposed in this paper provides a feasible method for the identification of fault type of distribution lines, and it can help master distribution laws of distribution network faults.