With the rapid growth of the distribution network and the high penetration of distributed resources, the topology of distribution networks has become increasingly complex, posing significant challenges to fault location analysis. When applying matrix algorithms and intelligent optimization algorithms to fault location, it is necessary to construct network matrices or establish optimization models based on changing topology information. This greatly increases the computational burden and complexity, leading to low efficiency in data processing and computation. Therefore, this paper first constructs a graph data model for the distribution network topology. Utilizing graph projection techniques, it extracts optimized subgraphs tailored for fault tracing scenarios from the panoramic power grid graph. On this basis, the Yen"s shortest path search algorithm is employed to find potential fault paths from the power source to the abnormal nodes. By traversing the line nodes and assessing their overcurrent information, the fault section is identified, thereby resolving the issues of accurate representation and rapid search of the power grid topology. This enables quick and precise fault localization in large-scale complex distribution networks, greatly enhancing fault search efficiency while ensuring the accuracy of fault tracing.