Maximum likelihood estimation of synchronous machine parameters and study of noise effect from DC flux decay data

The paper presents an evaluation of the performance of the maximum likelihood (ML) method when used to estimate the linear parameters of a synchronous machine model from the standstill time-domain flux decay test data. It is shown that a unique set of parameters can be obtained and the noise effects can be dealt with effectively when the ML estimation technique is used. The results also show that accurate machine parameters can be identified when the signal/noise ratio is approximately 200:1.