Maximum likelihood estimation of solid-rotor synchronous machine parameters from SSFR test data

Based on previous work (presented at the IEEE/PES 1989 Winter Meeting, New York) in which it was established that multiple parameter sets are obtained when the machine parameters are estimated from noise-corrupted frequency-domain data, the effects of noise on time-domain parameter estimation of synchronous machine models are studied. The proposed approach can be applied to the SSFR test data or time-domain 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 maximum-likelihood estimation technique is used to estimate machine parameters