The Modeling Of Excitation System Of Generator

The excitation system parameters of large synchronous generator have great effects on modern power system stability studies.However,owing to the shortage of the real parameters in the running,It may obtain unreliable stability analysis of power system.The thesis dissertates on the principles of excitation system parameter identification at first.and obtain the standard model of excitation system by professional parameter identification.The structure and characteristics of various excitation systems are introduced firstly,then the traditional identification methods,time domain identification(Piece Linear Polynomial Function) and modern identification(genetic algorithm),are studied.Based on principle induction and large number of simulation tests,the guidelines of parameter settings for the time domain method。It develops the efficiency of the two traditional identification methods.The thesis makes field test real parameters for excitation system of generator,and gains step-up test curve which parameter identification is obtained.In this thesis,the structure and characteristics of excitation system that often be used for large steam turbine generator excitation system are introduced firstly.So the paper introduces genetic algorithm in the parameter identification that makes the nonlinear system parameters identification possible.Then we take a real 300MW generator excitation system for example,set the generator excitation system models in MATLAB/SIMULINK,and identify the model parameters by intelligent identification. and comparing the simulating results with the real system.The results of research and application indicate that the genetic algorithm can validly identify non-linear systems and has the advantages of high accuracy.