A New Technique for Synchronous Machine Parameters Estimation from Frequency Tests

K.M. El-Naggar, A.K. Al-Othman, and H.K. Ebraheem (Kuwait)


Synchronous machine, estimation, Particle swarm, frequency tests.


A new particle swarm optimization (PSO) algorithm for estimating synchronous machine parameters from frequency test is presented in this paper. The proposed method uses a digital set of measurements for the direct axis impedance magnitude and phase as functions in the frequency for estimating both the d-axis and q-axis parameters, such as the direct reactance and both axes different time constants. The problem is formulated as an optimization problem and solved using the proposed method. Two Different models along with different fitness functions are suggested to be used with the proposed PSO algorithm. A practical example from the literature is used to test the proposed algorithm. The obtained results are compared with those obtained earlier in the literature using other methods. The results and comparison show that the new algorithm is very applicable and highly accurate.

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