Online State Space Model Parameter Estimation in Synchronous Machines

In this paper a new approach based on the least squares error method for estimating the unknown parameters of the 3rd order nonlinear model of synchronous generators is presented. the proposed approach uses the mathematical relationships between the machine parameters and on-line input/output measurements to estimate the parameters of the nonlinear state space model. the field voltage is considered as the input and the rotor angle and the active power are considered as the generator outputs. in fact, the third order nonlinear state space model is converted to only two linear regression equations. then, easy-implemented regression equations are used to estimate the unknown parameters of the nonlinear model. the suggested approach is evaluated for a sample synchronous machine model. estimated parameters are tested for different inputs at different operating conditions. the effect of noise is also considered in this study. simulation results declare that the efficiency of the proposed approach.