Study On Optimal Control Of Stability Of Synchronous Generator Excitation System

With the large-scale interconnection of power systems and the wide application of ultra high voltage,ultra long distance and large capacity transmission and distribution system,the overall capacity of the power system is increasing,the structure is more complex,the power system operation for stability and safety requirements are also getting higher and higher.In many measures to improve the stability of power system,the stability control of excitation system of synchronous generator is considered to be one of the effective measures.This thesis presents a method of model-free excitation control based on Adams prediction,and the improved bacterial foraging optimization algorithm is used to optimize the controller parameters,which can improve the excitation control effect and improve the stability and security of power system.This thesis introduces the development and current situation of the excitation control system and model free adaptive control at first,then on the basis of analyzing the mathematical model of the classical excitation control system,in view of the problem that some state variables in the mathematical model of the classical synchronous generator are difficult to measure,the mathematical model of the excitation control system based on the new state variable is derived,and the affine nonlinear model is given.Based on the mathematical model of the excitation control system with affine nonlinear form,Adams four order prediction and correction algorithm is introduced to realize the high precision prediction of the model output,and the adaptive control of the excitation control system is realized by the model free adaptive control.The Simulink simulation model of Adams-MFAC controller and single machine infinite excitation system is built by using Matlab simulation platform,and the conventional excitation control,basic model free control and Adams-MFAC control are compared and analyzed.The simulation results show that compared with the conventional excitation control method,the Adams-MFAC control has better control effect,improve the stability of the excitation control system,and verify the feasibility and effectiveness of the control method.In order to improve the control effect of the Adams-MFAC excitation controller,the bacterial foraging optimization algorithm is introduced to optimize the parameters of the Adams-MFAC excitation controller.Taking into account the high precision of the bacterial foraging optimization algorithm,there are some shortcomings of slow convergence rate,therefore,the algorithm is improved in the way of the step size,the range of contraction and the search method.Based on the single machine infinite system excitation model,the improved bacterial foraging optimization algorithm is simulated and compared with the basic bacterial foraging optimization algorithm and particle swarm optimization algorithm,the simulation results show that the improved algorithm has faster search speed and higher convergence precision,and the control effect of Adams-MFAC excitation controller is improved,and the effectiveness of the improved algorithm is verified.