Abstract
In this paper, the Prony analysis tool with the software used in the actual operation has a large error. The improved Prony method is used to identify the low-frequency oscillation mode of the power system. The traditional Prony algorithm has the problem of insensitivity to parameter error estimation in low frequency oscillation, which affects the accuracy and accuracy of the least squares calculation. Therefore, this paper proposes a Prony method power system low frequency oscillation method using Householder transform to make the calculation more Accurate and proven to be more efficient and reliable.
Highlights
With the continuous development of intelligent largescale power grids, power systems include water, fire, nuclear, wind, light and other forms of power supply
The dynamic stability of the power grid analysis is based on the PSD-SSAP power system small interference stability analysis program for frequency analysis, using PSD-BPA electromechanical transient simulation software for time domain simulation analysis [1], but the prony toolbox analysis error Larger, theoretically, a more accurate analysis method for lowfrequency oscillations is needed
In order to prove the parameter value of the lowfrequency oscillation of the power system low-frequency oscillation mode based on the Householder transform, the traditional Prony algorithm and the Prony method based on Householder transform can be compared and analyzed
Summary
With the continuous development of intelligent largescale power grids, power systems include water, fire, nuclear, wind, light and other forms of power supply. The dynamic stability of the power grid analysis is based on the PSD-SSAP power system small interference stability analysis program for frequency analysis, using PSD-BPA electromechanical transient simulation software for time domain simulation analysis [1], but the prony toolbox analysis error Larger, theoretically, a more accurate analysis method for lowfrequency oscillations is needed. The current Prony algorithm is a common method for studying low-frequency oscillations in power systems, it can extract the oscillation characteristics more accurately and find the dominant oscillation mode [3]. The QR decomposition method of Householder transformation is used to improve the fitting precision The improvement of this algorithm is helpful and be used in the analysis of actual low frequency oscillation actual work through the comparison of examples. Perform calculations and analysis; the fifth part is summary and outlook
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