Identification paramétrique d’un générateur synchrone et filtrage en mode perturbé

Abstract

The work of this thesis focused on parametric identification of synchronous machine with salient poles (SG) equipped with dampers of power 0.3kW. First of all, they have been made in off-line mode from experimental tests according to international standards. For a more precise determination of parameters in perturbed mode, we have developed on-line algorithms by applying different Kalman Filters (KF) in continuous and discrete time: The Discrete Kalman Filter (DKF) is the applied estimator in this study because it gives a good convergence compared to the real parameters; it is used in its various forms, traditional (TDKF) for linear systems or in its extended form (DEKF) when the system is non-linear. Another interesting application of DKF is when it is biased (DEKFB) because it will reduce the squared error (MSE) between the measured and estimated values of the system state variable; as a result, the standardized MSE (NMSE) can be minimized. Similarly, the standard deviation (STD) between the real and estimated values of the parameter can be limited to a tolerable percentage. The different KFs are implemented in a Matlab / Simulink environment in order to demonstrate the effectiveness of the DEKFB estimator compared to other Filters. The simulation results are acceptable since a good match between the real and estimated parameters has been obtained, which reflects the good noise filtering quality of the KF estimators designed and which can be used in on -line parametric identification in disturbed mode of low scale generator.