On-line identification of synchronous generator parameter from large disturbance testing data

In this paper, an online synchronous generator parameter identification procedure is presented using large disturbance responses and the extended least square estimation algorithm. It was shown that the entire process of signal generation, injection and response measurement can be performed in real time using an industrial personal computer system. In this study, the nonlinear saturated machine model parameters are identified under different operating conditions. Furthermore, from these identified parameters, the parameter sub-models are identified using the least square estimation algorithm under a wide range of operating conditions. This identification technique is carried out on a practical power system to estimate the parameters of a synchronous machine rated at 125 MW. Simulation studies are performed to validate the accuracy of the identified machine model including parameter sub-model