Research On Identification Method Of Dominant Parameters Of Synchronous Generators In Large Power Grid Response

As the core component of the power system,the accuracy of synchronous generators parameters not only affect the result of power system analysis,but also affect the development of power grid control strategy.Despite years of development,parameter identification of synchronous generators is still a challenging subject.On-line identification method combines the on-line measurement and identification technology,the identified parameters are more in line with the actual operating conditions of the power system.In recent years,it has been a hot topic in the research of power system experts and scholars,But most of the existing studies did not take into account the effects of nonlinear factors in the process of disturbance,so the identification results may be a large estimation error.Therefore,it is of great theoretical and practical significance to study the on-line identification method of synchronous generator parameters based on new theories and new technologies,and to propose the system and feasible generator parameter identification scheme to improve the accuracy of generator parameters.In this paper,the on-line identification method of synchronous generator based on large power grid response is studied.The feasibility of the new method,the identification of the dominant generator,the identification algorithm and the error quantization are systematically studied.The main research work is as follows:1)The identifiability problem of synchronous generator models is studied based on large power grid response.On line identifiability algorithm for synchronous generator parameters based on Principal Hessian Direction(PHD)theory is proposed.Firstly,the objective function of generator nonlinear model parameter identification is established,which provides the basis for the feasibility analysis of parameter identification.Then,the feasibility of on-line identification of synchronous generator parameters based on the PHD algorithm is proposed,in order to avoid the problem that the parameters can not be identified by the local optimal solution of the traditional linear identification algorithm.Finally,the evaluation method based on the correlation parameter is proposed,and the method can improve the robustness and accuracy of parameter identification.The simulation results show that the proposed method can be used to assist the parameter online identification process and provide the basis for the results of parameter identification.2)The on-line identification of strong-related generators is studied based on large-scale grid response and the recognition algorithm of strong correlation generators is proposed in the main oscillation modes considering both the structural characteristics and the perturbation response.It is the first task to identify the strong correlation generators correctly.Firstly,the quantitative relationship is established between the tie-line oscillation mode based on the Prony method and eigenvalue analysis method.Then the identification algorithm based on the strong correlation generator of large power grid is derived,which can solve the problem that the current identification algorithm can not be used to identify the main oscillation mode and the strong correlation generator.The simulation results show that the proposed algorithm is reasonable and can be used as a powerful tool for the rapid identification of generators under the condition of large power grid response..3)The parameter identification method is studied based on KS-PGAS algorithm and the on-line identification of synchronous generator parameters is proposed based on large power grid response.Firstly,based on the characteristics of the large power grid,a discrete nonlinear state space model is established to realize the decoupling of the synchronous generator in the large power grid and improve the identification efficiency.Then the parameters of kernel smoothing algorithm(Kernel Smoothing KS)and ancestor Gibbs(Particle Gibbs particle sampling algorithm of with Ancestor Sampling,PGAS),is proposed for parameter estimation of synchronous generator based on the KS-PGAS algorithm,the identification method has better ability of identification parameters and fast convergence,which is suitable for on-line parameter identification.Finally,according to the different stages of the response based on the grid disturbance,the dominant parameters of the first pendulum maximum power and damping ratio are respectively identified and modified to improve the accuracy of identification.The simulation results show that the parameter identification method of synchronous generator proposed in this paper is suitable for the nonlinear parameter estimation of nonlinear parameters with high robustness.4)The quantitative analysis of synchronous parameterss is studied based on large power grid response,and the quantization method for on-line parameter identification error of synchronous generator is proposed based on the cramer-rao lower bound.Firstly,the probability density function of parameter identification is established based on the error analysis theory.Then,the method of quantization of parameter identification error based on cramer-rao lower bound theory and trajectory sensitivity algorithm is proposed to determine the range of identification error,which solves the lack of error calculation of online identification result.Finally,the parameter identification error of multiple experiments under the same working condition is analyzed based on the Bayesian theory,which improves the accuracy of the identification parameters.The simulation results show that the error quantification method proposed in this paper can effectively estimate the error of parameter identification results of online measured data and can be applied to the error analysis of online parameter identification.