High Impedance Fault Location in Distribution Systems: A Novel Approach With Enhanced Metrics and Intelligent Algorithms

Locating faults in a distribution system (DS) is a challenging task, especially with the increasing integration of distributed generation (DG). Among the various fault types in DSs, high impedance faults (HIFs) are particularly difficult to address due to their low fault currents and erratic behavior, often resulting from contact between a conductor and a low-conductivity surface. Despite of the numerous papers addressing HIFs, there is still a lack of consensus on the most effective metrics and techniques for their detection and location. This article proposes a comprehensive analysis aiming to identify the adequate metrics for artificial intelligent algorithms to locate HIFs in a DS in the presence of DG. This analysis provides valuable insights into developing more efficient HIF location methods. Therefore, these insights are applied to develop a new HIF location method, based on artificial intelligence. The analysis is carried out by evaluating the correlation between almost 11,000 metrics with the HIF distance. The metrics showing the strongest correlation with HIF location are then used as input data for intelligent algorithms designed to accurately estimate the HIF position. Subsequently, these algorithms are evaluated and compared based on their error rates in locating HIFs. Finally, a new intelligent-based method for HIF location in DSs is proposed and extensively evaluated, including a comparison with existing approaches and a generalization analysis, which showed high successful rates and strong potential for practical application.