Abstract: Dispatching is one of the core businesses in the field of power grid. With the construction of power grid information system in recent years, it presents the characteristics of multiple data structures and complex structures. In order to meet the dispatching requirements of efficient response, this paper proposes an entity recognition technology in the field of power grid based on migration learning, and studies the application of power grid fault handling based on knowledge graph. Firstly, an entity recognition technology based on transfer learning for power grid fault handling text data is proposed. This technology can realize entity recognition with high accuracy in the case of a small number of annotations, and effectively solve the problem of low accuracy in entity recognition of small sample data in power grid field. Secondly, the power grid fault handling knowledge graph is constructed, which converts the multi-source heterogeneous data in the power grid dispatching field into knowledge, and can realize the decision support for multiple fault types. Finally, based on the established grid fault handling knowledge graph, the real-time auxiliary decision function of fault handling is realized and nested into the application of provincial collaborative fault handling engine. Practical application shows that the knowledge and experience obtained through graph database can provide effective reference scheme for dispatchers.