As a critical facility for the safe operation of power systems, grounding grids face severe corrosion issues that significantly compromise fault current dissipation and personnel safety. In response to the challenges of severe corrosion in widely used steel grounding grids and the limitations of existing diagnostic methods (e.g., poor anti-interference capability and a predominant focus on fault localization), this paper proposes a fault type diagnosis method for grounding grids based on trends in key parameter variations. By selecting grounding resistance, touch voltage, and step voltage as key parameters, the correlation between parameter variation trends and fault types (e.g., conductor thinning without breakage, conductor fracture) is systematically analyzed. Compared to traditional approaches, this study emphasizes fault type identification, reducing reliance on power outages and large-scale excavation during diagnosis, thereby providing theoretical support for improving the operational efficiency and safety of grounding grid maintenance.

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Fault Type Diagnosis Method for Grounding Grids Based on Trends in Key Parameter Variations

  • Liu Shaoyong,
  • Liu Yaqing,
  • Luo Jinwen,
  • Le Lingling

摘要

As a critical facility for the safe operation of power systems, grounding grids face severe corrosion issues that significantly compromise fault current dissipation and personnel safety. In response to the challenges of severe corrosion in widely used steel grounding grids and the limitations of existing diagnostic methods (e.g., poor anti-interference capability and a predominant focus on fault localization), this paper proposes a fault type diagnosis method for grounding grids based on trends in key parameter variations. By selecting grounding resistance, touch voltage, and step voltage as key parameters, the correlation between parameter variation trends and fault types (e.g., conductor thinning without breakage, conductor fracture) is systematically analyzed. Compared to traditional approaches, this study emphasizes fault type identification, reducing reliance on power outages and large-scale excavation during diagnosis, thereby providing theoretical support for improving the operational efficiency and safety of grounding grid maintenance.