Research On Excitation Transformation Of Power Plant Based On Modern Optimization Algorithm

Excitation control systems for power transmission capacity of stability has a very important influence,with the development of productive forces,expanding the power system,science and technology,continuous progress control theory,people on excitation control system to improve power system stability role understanding gradually deepened.It works as follows:(1)Power plant generator excitation system modeling: The excitation system structure and the transfer function,then separately for each part of the unit excitation system modeling and parametric analysis,the final integration of the entire excitation system modeling(2)Power plant generator excitation system to identify the parameters: frequency domain methods were used,time-domain method,modern optimization algorithms to identify the parameters of the excitation system,frequency domain method using a fast Fourier transform,using the time domain method is PLPF law,modern optimization algorithms designed the two,the first is to improve the genetic algorithm parameter identification,analysis and matlab examples,the second is based on support vector machine and particle swarm algorithm parameter identification,and matlab actual analysis.(3)Power generator excitation system,control system based on the transformation of modern optimization algorithms: excitation control system are introduced and studied variable precision rough set and RBF neural networks that are used for excitation control based on neural network improved design.