Synchronous Machine Parameters Estimation using Stochastic Method | ||||||
Author(s) | M. L. Zhu; M. Crappe; M. Renglet; B. Mpanda-Mabwe | |||||
Abstract | The paper describes an original time-domain method for the identification of Synchronous Machine (SM) parameters using on-line tests. The method combines Kalman Filter (KF) to estimate the state of the system and Maximum Likelyhood (ML) method for parameter estimation. The proposed on-line measurement based approach to generator modelling has the advantage of the direct measurement of actual transient behaviors of synchronous machine under system operating conditions. This algorithm is able to identify the parameters of SM using the data measured during any transient period. It is robust to the noise in the process and measurements. The emphasise the sensitivity of the estimated parameters to load conditions, various tests are performed on a micro machine rated (2 kVA, 220 V, 1500 rpm). It is shown that the different sets of parameters obtained are coherent. |
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Type | Members Only | |||||
Date | Last modified 2006-04-18 by System | |||||
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