There is a problem of the lack of effective identification methods for power grid dispatching business intentions. Thus a method for power grid dispatching intention recognition based on ALBERT (A Lite BERT) and a fully integrated residual vector-embedding vector-encoded vector (RE2) fusion model is proposed. First, the dispatching professional language text features are calculated based on the ALBERT pre-trained dynamic word vector, a dispatching intention classification model is built. A text similarity calculation model is built through training dispatching professional languages based on RE2. Then the similarity value is calculated using the dispatching language similarity model between the recalled and the classified text to reorganize the ALBERT intention classification weight. Finally, through the professional language verification of a dispatching and control center, the proposed power grid dispatching intention recognition method has stronger classification ability and generalization ability than other methods. The average accuracy rate, recall rate and F1 value of 20 kinds of dispatching intent recognition reached 98.11%, 97.96%, and 98.03% respectively. This work is supported by the Science and Technology Project of the Headquarters of State Grid Corporation of China (No. 5700-202028362A-0-0-00).