Conference article

State Estimation of a Thermal Model of Air-cooled Synchronous Generator

Madhusudhan Pandey
University of South-Eastern Norway, Porsgrunn, Norway

Thomas Øyvang
University of South-Eastern Norway, Porsgrunn, Norway

Bernt Lie
University of South-Eastern Norway, Porsgrunn, Norway

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Published in: Proceedings of The 60th SIMS Conference on Simulation and Modelling SIMS 2019, August 12-16, Västerås, Sweden

Linköping Electronic Conference Proceedings 170:29, s. 190-197

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Published: 2020-01-24

ISBN: 978-91-7929-897-5

ISSN: 1650-3686 (print), 1650-3740 (online)


In this paper, we extend a previous study on a totally enclosed thermal model of a synchronous generator, with temperature state estimation using experimental data. The extension includes a new formulation of the system model, with four different model variations with and without temperature dependence in the metal, air, and water heat capacities and the copper resistances, where temperature variation in water and/or air requires a non-standard heat exchanger model. In the former study, the Unscented Kalman Filter (UKF) was used for state estimation. Here, we include both the UKF as well as the Ensemble Kalman Filter (EnKF) in the comparison. UKF and EnKF are compared based on estimation accuracy and computational speed. Results show that EnKF exhibits lower RMSE for the innovation process and thus is more accurate than the UKF even with a “minimum” of 50 particles, but the UKF with 6 sigma points (3 states) is faster. It is too early to conclude which of four models is more accurate, as they need to be tuned individually wrt. parameter fitting.


air-cooled synchronous generator, dynamic model, state estimation, Unscented Kalman ?lter, Ensemble Kalman filter


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