A Prony Analysis Method Applicable to the Identification of Low Frequency Oscillations and Subsynchronous Oscillations

Abstract

The present invention provides a Prony analysis method suitable for low-frequency oscillation and subsynchronous oscillation identification, including: constructing an extended-order sample matrix based on measured data; The calculation order of the algorithm; the characteristic polynomial is solved, and a new matrix equation is constructed according to the obtained characteristic root; the method based on BP neural network is used to iteratively solve the matrix equation constructed above; the solution of the characteristic root and matrix equation obtained based on the above solution Calculate Prony parameters: amplitude, attenuation factor, frequency, initial phase. By using the Prony analysis method which is suitable for the identification of low-frequency oscillation and subsynchronous oscillation proposed by the present invention, the deficiency of the calculation order selection method in the traditional algorithm can be overcome, and the accurate order determination can be realized, and the method based on BP neural network is used for iterative solution. , which improves the deficiencies of the past algorithms in complex matrix calculation, and improves the speed of solving complex matrix equations of the Prony algorithm.

Description

technical field [0001] The invention relates to the field of monitoring and analysis of low-frequency oscillations and subsynchronous oscillations in power systems, in particular to a Prony analysis method suitable for identification of low-frequency oscillations and subsynchronous oscillations. Background technique [0002] In recent years, with the acceleration of my country's cross-regional networking process, the advancement of UHV transmission networks, the increase in long-distance transmission power, and the use of series capacitor compensation in long-distance AC transmission systems to increase the transmission capacity of the grid, these measures have all It may cause low-frequency oscillation or subsynchronous oscillation of the power system. At present, these two oscillation problems have become one of the important factors that destroy the safe and stable operation of the power system. Nonlinear time variation is an important feature of large-scale complex power...

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Problems solved by technology

However, the algorithm is very sensitive to noise and is easily disturbed by noise, and it is difficult to reflect the non-stationarity of the dynamic process; it is difficult to solve the complex matrix equations of the algorithm, and there is a problem of large amount of calculation, resulting in high sensitivity; and the traditional order determination method needs The threshold is artificially selected, and the fluctuation of the threshold will bring errors to the accurate order determination

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