Aiming at the issues of low accuracy and poor efficiency in practical applications of existing methods for three-dimensional identification of substation equipment, a three-dimensional identification method for substation equipment is proposed, which combines the improved iterative nearest point algorithm and Umeyama algorithm. The plane features of device are extracted through random sampling consistency algorithm, the Umeyama algorithm is used to identify several devices with the most similar planar features in the template library, the point cloud key points of device are extracted through point cloud curvature features, and the target matching of devices is carried out by improving the iterative nearest point algorithm. The analysis of its performance is conducted through experiments. The results show that the proposed method has good recognition accuracy and efficiency for 3D recognition of intelligent substation equipment, with a recognition accuracy of 99.50% and an average recognition time of 2.07s, effectively improving the comprehensive performance of 3D recognition technology.