Abstract
AbstractWinding hot‐spot temperature (HST) is an important factor that affects the insulation life of an oil‐immersed power transformer. Thus, precise prediction and close monitoring of HSTs are necessary to avoid thermal damage. In this paper, a differential equation for HST prediction is presented, which takes into consideration the effects of the top‐oil temperature variations and thermal dynamics of the load. A discrete form of this equation based on the framework of the Kalman filter (KF) algorithm was used to establish a real‐time estimation model for the HST. The KF‐based model was validated by a sample heat‐run test involving a transformer setup in the laboratory. Moreover, the proposed model was applied to a real, large power transformer and compared with the classical IEEE‐Annex G method. Results show that the HSTs estimated by the KF‐based model are closer to the measured values. The exhibited potential applicability and generality in real‐time prediction for HST demonstrate that the proposed model can be employed for online monitoring of HSTs for large power transformers. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
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