On-line excitation systems´ parameters identification based on input-output system and hybrid algorithm with PMU

Parameter identification for excitation systems is a foundation for the power system stability analysis. This paper aims at on-line identifying the parameters of the excitation system with the field data obtained with PMU/WAMS. Firstly, the on-line parameters identification of the excitation systems is formulated as an optimization problem of an input-output system. In detail, the input is the PMU data corresponding to the generator´s terminal voltage and the output is the PMU data corresponding to the generator´s excitation voltage/current. The objective of the optimization problem is to minimize the different of the output and virtual output errors during a certain time, the errors are the differences between the measured output and the virtual output of the model. In computational realization, the objective function is the square sum of the differences at different sampling points. The above optimization problem is nonlinear as it involves differential equations, therefore this paper takes the hybrid algorithm which is based on the combination of the genetic algorithm (GA) and gradient-based searching to obtain the solution. Finally, simulation results in a PSASP-12 type excitation system, with the field PMU data, show the effectiveness of the proposed approach.