Multi-type signal-based power system low-frequency oscillation analysis method

Abstract

The invention discloses a multi-type signal-based power system low-frequency oscillation analysis method, and belongs to the field of analyzing the stability of the power system. The method mainly comprises the steps of analyzing internal physical contact among multi-type curves of sets; formulating amplitude deviation and phase deviation evaluation indexes based on the contact, and evaluating the accuracy degree of extracting oscillation mode by the Prony algorithm; in order to avoid the signal in some type from being covered caused by over large amplitude difference of the curves in different types, performing translation processing on the amplitude of the signals in different types; giving a dominant oscillation mode identifying method, establishing a comprehensive evaluation index of a multicomputer signal, and reflecting the reliability of the Prony algorithm. The index system provided by the invention has engineering application value; according to the system, the reliability of extracting the oscillation mode information can be reflected; the appropriate Prony algorithm order can be selected according to the comprehensive index.

Description

technical field [0001] The invention belongs to the field of power system stability analysis, and in particular relates to a low-frequency oscillation analysis method of a power system based on multi-type signals. Background technique [0002] The low-frequency oscillation of the power system directly affects the operation of the interconnected system. The characteristic root method based on the linearization model has a clear physical concept and provides a wealth of information, but it is difficult to calculate for large systems and it is difficult to reflect the influence of nonlinearity. The disturbed trajectory of the system can contain nonlinear effects, and the trajectory acquisition is less affected by the system scale. With the introduction of the Wide Area Measurement System (WAMS), it is possible to monitor the operation of the system in real time without relying on the system model, which provides important information for low-frequency oscillation analysis. dist...

AI Technical Summary

Problems solved by technology

[0003] Trajectory-based analysis of low-frequency oscillations mainly includes analysis of stationary oscillation characteristics and non-stationary oscillation characteristics. At present, the analysis of non-stationary oscillation characteristics is mainly based on a single trajectory. Common methods include window Fourier ridge, wavelet ridge, HHT, etc.; stationary oscillation characteristic analysis is applicable It is suitable for single trajectory and multi-machine disturbed trajectory. The common method is Prony algorithm. This algorithm is simple to calculate, but the anti-interference performance is poor, and the appropriate model order needs to be selected.

At present, the determinant method and singular value decomposition method are commonly used to determine the order of the Prony algorithm. These methods are mainly used to distinguish the effective data space and the noise space, and it is difficult to evaluate the identification results of different orders of the Prony algorithm.

For systems with certain nonlinearity, using this method to determine the order of the algorithm may cause overfitting

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