Network phasing technology based diagnostic methodology for phase sequence anomalies in box-type transformers

Grid phase abnormality poses a critical threat to the safe operation of distribution networks. Conventional phasing verification methods struggle to efficiently locate fault sources in complex circuits due to their reliance on power outages and limitations imposed by equipment enclosure constraints. This paper presents an innovative diagnostic methodology integrating network phasing technology, multi-level progressive investigation, and relative entropy modelling, using a phase sequence anomaly event at a Shanghai box-type substation as a case study. Through three systematic inspections combining non-contact measurements and voltage vector analysis via the GC6100 network phasing equipment, the fault was conclusively traced to reversed B-C phase sequence wiring within the first substation. Experimental results demonstrate 62% improvement in troubleshooting efficiency, 75% reduction in outage duration, operational cost reduction to ¥8,000 per maintenance event, and ±0.5m localization accuracy in multi-node coupling scenarios. Comparative analysis against bridge and secondary pulse methods verifies the superior diagnostic capability of network phasing technology for enclosed equipment. This study establishes a replicable technical framework for complex grid phase anomaly resolution while providing practical support for intelligent maintenance of next-generation power systems.