An Improved Tagging System for Equipment Portrait of UPFC Based on K-means Algorithm and Multidimensional Data

The Unified Power Flow Controller (UPFC) is an important application to enhance the transmission capacity of power grids. However, the state detection of UPFC faces challenges such as multidimensional data, difficulty in information collection and classification, making it challenging to achieve better control of UPFC. This paper integrates various types of data related to UPFC and utilizes equipment portrait technology to assign comprehensive tags to UPFC, establishing a tag system based on UPFC. Furthermore, models for UPFC equipment portrait are built based on the characteristic tags, which facilitates an objective and comprehensive understanding of the operational status of UPFC. Additionally, the implementation of the tag system in performance evaluation is proposed. Moreover, the generation method of third-level tags is optimized, and the accuracy of tag acquisition is improved through an enhanced K-means clustering algorithm in MATLAB, enabling precise equipment portrait and fine-grained management of UPFC.