Entity alignment method in power grid monitoring field based on ontology vocabulary

In the face of increasing power grid monitoring information, existing data is stored in different databases. There is an urgent need to unify multi-source data specifications into the same database effectively. The power grid monitoring field introduces knowledge graphs to store associated massive data. However, the research on the efficient fusion of multi-source data is still in its infancy. In order to solve the problem of low fusion accuracy of existing entity alignment methods, this paper proposes a new idea based on the fusion of domain ontology vocabulary on the basis of a similarity comparison algorithm. By dividing some entities into different categories and then comparing and categorizing the remaining entities, the standardization of fusion is enhanced, and the possibility of misclassification is reduced. Finally, after a comparison of calculation examples, the results show that the entity alignment method in the field of power grid monitoring based on the ontology vocabulary proposed in this paper improves the accuracy of fusion compared with the previous similarity algorithms and provides new ideas for the further development of multi-source data fusion in the field of power grid monitoring.