A novel technique to estimate and model parameters of a 460-MVA large steam turbine generator from operating data is presented. First, data from small excitation disturbances are used to estimate linear model armature circuit and field winding parameters of the machine. Subsequently, for each set of steady state operating data, saturable inductances and are identified and modeled using nonlinear mapping functions-based estimators. Using the estimates of the armature circuit parameters, for each set of disturbance data collected at different operating conditions, the rotor body parameters of the generator are estimated using an output error method (OEM). The developed nonlinear models are validated with measurements not used in the estimation procedure.Index Terms-Armature circuit and rotor body parameters, large utility generators, parameter identification.
This paper presents a methodology to estimate armature circuit and field winding parameters of large utility generators using the synthetic data obtained by the machine natural abc frame of reference simulation. First, a onemachine infinite bus. system including the machine and its excitation system is simulated in abc frame of reference by using parameters provided by the machine manufacturer. A proper data set required for estimation is collected by perturbing the field side of the machine in small amounts. The recursive maximum likelihood (RML) estimation technique is employed for the identification of armature circuit parameters. Subsequently, based on the estimates of armature circuit parameters, the field winding and some damper parameters are estimated using an Output Error Estimation (OEM) technique. For each estimation case, the estimation performancc is also validated with noise corrupted measurements. Even in case of remarkable noise corruption, the agreement between estimated and actual parameters is quite satisfactory.
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