Real-time calculation method of transformer winding temperature field based on sparse sensor placement

Abstract

The Real-time obtain of the transformer winding temperature field is of great significance for understanding the operation status of the transformer. Limited by the spatial sampling rate of the sensor measurement method and the computational efficiency of the Computational Fluid Dynamics (CFD) method, the existing techniques cannot complete the real-time obtain of the transformer winding temperature field well. In this study, an estimator is designed, and used as a bridge to establish the relationship between the sparse measurement data of the winding temperature and the winding temperature field, and the real-time obtain of the winding temperature field is realized. Firstly, the proper orthogonal decomposition (POD) modes are obtained based on the prior information on the winding temperature field. Then, a sparse placement strategy of sensors is designed based on the QR factorization with column pivoting (QR-pivot) method, the measurement matrix is formed, and the sparse measurement data of the winding temperature are obtained. Finally, an estimator is designed to complete the winding temperature field's real-time calculation using the winding temperature's sparse measurement data. The transformer temperature rise test proves the effectiveness of the method. This study can provide a new approach for the real-time obtain of transformer winding temperature field.