A Sampling Point Location Method for Fault Initiation Time in Power Systems Based on Peak-to-Peak and Multi-Resolution Morphology

Accurate and rapid localization of power system fault initiation time sampling points is critical for fault isolation, protection optimization, and grid recovery. To address the challenges of imprecise fault initiation time localization and vulnerability to complex grid disturbances, this paper proposes a targeted multi-stage detection method dedicated to pinpointing fault initiation sampling points. This method integrates peak-to-peak analysis, adaptive thresholding, and multi-resolution mathematical morphology, proceeding in three key stages: first, fault intervals are segmented using peak-to-peak characteristics to identify potential disturbance regions; second, a adaptive threshold algorithm is used to narrow down the judgment range of the sampling points at the fault initiation moment; finally, multi-resolution morphological gradient analysis based on mathematical morphology theory is applied to accurately locate the sampling point at the fault initiation moment. Empirical validation using real-world fault datasets demonstrates that the proposed approach achieves 95% accuracy in identifying fault initiation times. These results provide a novel and effective technical solution for real-time fault detection and rapid protection in modern power systems.