Research On Parameter Identification Of Excitation System Based On PMU

Excitation system of synchronous generator is of vital importance to the security, stability and economic operation of power system, and the accuracy of the model and its parameters is related to the credibility of simulation calculation, which would affect some engineering applications. However, the traditional offline modeling and parameter test method could no longer adapt to the requirements; with the development of phasor measurement unit(PMU) and wide-area measurement system(WAMS), obtaining real-time synchronous phasor data of power system is very convenient, which provides an effective platform and data source for on-line modeling and parameter identification of power system components.In this paper, based on the dynamic synchronous data of excitation system recorded by PMU under the power grid disturbances, the feasibility of parameter identification of excitation system is studied. Firstly, through analyzing the frequency-domain conditions of order reduction or conversion of excitation models and the frequency characteristics of the common power grid disturbance signals from the perspective of the frequency-domain characteristic of model and excitation signal, the numerical identifiability of the common models and its parameters is studied, then the conclusions are verified by time-domain methods; it’s worth mentioning that the proposed identifiability analysis method is different from the existing theoretical analysis and numerical method. Secondly, the influence of the quality of dynamic PMU synchronous data to parameter identification is studied; to some extent, this paper reveals the influence mechanisms of random measurement error and asynchronous input/output data to parameter identification. Further, considering that there may exist bad data in PMU data and measurement error is difficult to determine, an adaptive robust identification method based on the output error criterion is proposed, and the simulations show that the proposed method is valid and the robust method based on IGG weighted function has better ability of noise suppression and robustness. Finally, the classification identification strategies considering the nonlinear links’parameters are proposed; then the feasibility of overall parameter identification considering the nonlinear links based on the large disturbance PMU data is preliminarily analyzed through simulation from the perspective of the curve fitting effect of field voltage.