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

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3 Author(s)
Keyhani, A. ; Ohio State Univ., Columbus, OH, USA ; Hao, S. ; Dayal, G.

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

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Energy Conversion, IEEE Transactions on  (Volume:4 ,  Issue: 3 )