Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Parameter Estimation for Hot-spot Thermal Model of Power Transformers Using Unscented Kalman Filters
Author:
Affiliation:

1. Department of Electrical Engineering, University of Seville, Seville, Spain 2. ENGREEN Laboratory of Engineering for Energy and Environmental Sustainability, Seville, Spain

Fund Project:

This work was supported by the project HySGrid+ (No. CER-20191019), the project IDENTICAL (No. TP-20210270), and the project FlexOnGrid (No. PID2021-124571OB-I00).

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    Abstract:

    This paper presents a parameter estimation technique for the hot-spot thermal model of power transformers. The proposed technique is based on the unscented formulation of the Kalman filter, jointly considering the state variables and parameters of the dynamic thermal model. A two-stage estimation technique that takes advantage of different loading conditions is developed, in order to increase the number of parameters which can be identified. Simulation results are presented, which show that the observable parameters are estimated with an error of less than 3%. The parameter estimation procedure is mainly intended for factory testing, allowing the manufacturer to enhance the thermal model of power transformers and, therefore, its customers to increase the lifetime of these assets. The proposed technique could be additionally considered in field applications if the necessary temperature measurements are available.

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History
  • Received:July 26,2022
  • Revised:September 07,2022
  • Adopted:
  • Online: March 25,2023
  • Published: