PMU Measurement Based Generator Parameter Calibration by Black-Box Optimization with A Stochastic Radial Basis Function Surrogate Model

In this paper, we propose a synchrophasor measurement based generator parameter calibration method by a black-box optimization approach with a stochastic radial basis function (RBF) surrogate model. Based on comparison between the outputs of the generator model with estimated parameters and the phasor measurement unit (PMU) measurements, we define an objective function for the black-box optimization problem, which is approximated by a RBF surrogate model. The prior information of the parameters is treated as constraints in the black-box optimization problem. The formulated black-box optimization problem is then solved by a Stochastic Response Surface Method (MSRSM). The effectiveness of the proposed method is tested and validated on a hydro generator. The simulation results show that the proposed approach can accurately and efficiently estimate the generator parameters subject to gross errors in the prior distributions of the parameters.