On Line Parameter Identification Of Synchronous Generator

With the continuous development of modern power grid,there are more and higher requirements for reliability and safe operation.The basis of power system simulation,fault diagnosis and operation analysis is accurate mathematical model and parameters,which are of great significance to the safe operation of power grid.Therefore,fast and accurate acquisition of reliable power grid model parameters is the basic problem to ensure the safe operation of power system.Phasor measurement unit(PMU)provides a key measurement device for the safe and stable operation of power system.PMU plays an important role in the safety monitoring,reasonable dispatching,power grid state monitoring and dynamic process control of generator in power system.This paper focuses on the problem of parameter identification of synchronous generator.Firstly,the basic principle and process of parameter identification of synchronous generator are described.The basic voltage equation,flux equation and several practical models of synchronous generator are given.On the basis of identifiability analysis,the sixth order model of synchronous generator is selected for parameter identification.Then,the problem of parameter identifiability of synchronous generator based on PMU data is studied,and an algorithm of parameter identifiability analysis of synchronous generator based on main Hessian direction method is proposed.The parameter identification objective function of synchronous generator is established,and the feasibility of parameter identification is analyzed.Based on the PHD algorithm,a scheme of parameter identifiability analysis is proposed,and the identification correlation parameters are analyzed.Secondly,the simulation model is built in Simulink of MATLAB,and the excitation voltage model is established to simulate the dynamic operation process of synchronous generator under various disturbances.The six order practical model parameter identification scheme based on the improved particle swarm optimization algorithm is used to identify the parameters of the simulated operation state of generator.The feasibility and universality of the identification scheme are verified by the analysis of the identification results.Finally,based on the measured data of generator PMU in two power plants,the improved particle swarm optimization algorithm is used to identify the parameters.The feasibility and stability of the scheme are verified by analyzing the identification results.Then,the traditional identification scheme is used to identify the parameters.Through the comparative analysis of the parameter identification results of the two schemes,the improved particle swarm optimization algorithm is shown It is concluded that the improved particle swarm optimization algorithm has smaller identification objective function and closer dynamic description of synchronous generator to actual operation condition.