The invention relates to a low frequency oscillation identification method for a power system based on an O3KID algorithm. The method embeds an observer in the stochastic model of the power system, and uses the basic equation of the O3KID algorithm and the least squares method to estimate the Markov parameters and residuals of the observer, and transforms the stochastic system identification of the power system into an identification problem of the deterministic system. The introduced device is equivalent to the Kalman filter. The Hankel matrixes are respectively constructed by using the output of the observer and the residual time series. The orthogonal projection and singular value decomposition methods of the deterministic system are used to effectively identify the reduced-order modelof the power system, and accurately extract the frequency, damping ratio and vibration mode parameter information of the dominant mode of the low-frequency oscillation. The method provided by the invention is suitable for the low-frequency oscillation mode analysis of the power system for the WAMS synchronous measurement environment excitation signal and the transient ring-down signal, and the IEEE-39 node system simulation and the US Eastern Power Grid WAMS measured data analysis verify the effectiveness of the method.

Low frequency oscillation identification method for power system based on O3KID algorithm

The invention discloses an online identification method for electromechanical oscillation modal characteristic parameters of an electric power system, and belongs to the technical field of electric power system state analysis. On the basis that random data generated due to uncertain factor interference in the environment where the power system is located is selected, the application of a new analysis method of O3KID-ERA/DC is provided to carry out small interference on-line calculation and analysis of the power system. Analysis of small interference of electric power system is carried out through example simulation calculation verification. The ERA/DC algorithm has good applicability; in addition, compared with a traditional classic SSI algorithm, the method has higher robustness. According to the method, more excellent capability is shown on the precision and stability of modal parameter identification, a new and reliable solution is provided for real-time online monitoring and analysis of the small interference stability level based on random data in the operation process of the power system, and the method has high practical application value.

Online identification method for electromechanical oscillation modal characteristic parameters of electric power system

A high-permeability wind-driven power system wind power branch mode energy analysis method belongs to the technical field of power system operation and maintenance. The method constructs a simple andvisualized wind-driven power system wind power branch mode potential energy function with a clear physical meaning by modeling the wind-driven power system wind power branch mode energy, can accordingly analyze the composition and the variation law of the wind power branch mode potential energy, studies the influence of the change of the branch mode potential energy on the small disturbance stability of the system, can also analyze the sensitivity to state variables of the wind power branch mode potential energy, analyzes the sensitivity to different state variables, and controls and suppresses the low-frequency oscillation by adjusting the state variables. The method constructs a simulation example, compares the wind power branch mode potential energy measured after disturbance with the frequency-domain mode potential energy, verifies validity, and has a high practical value.

High-permeability wind-driven power system wind power branch mode energy analysis method

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Online identification method for electromechanical oscillation modal characteristic parameters of electric power system

High-permeability wind-driven power system wind power branch mode energy analysis method