Application of improved genetic algorithm in parameter identification of generator excitation systems

A new method based on improved genetic algorithm for identifying parameters of generator excitation system is introduced in this paper. This method is used to convert the original model of generator excitation system to the standard model of excitation system. By using improved genetic algorithm, with the minimal difference between the output of the original model and that of the standard model being the object, the parameters of generator excitation system are adjusted constantly. Finally, the most suitable parameters of generator excitation system can be obtained. Compared with traditional identification methods, this method solves the problem that nonlinear part of excitation system is difficult to identify, and the result is more accurate. The actual identification result shows that this method can obtain the accurate parameters of the standard model of generator excitation system.