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- W2371583031 abstract "Power system low frequency oscillation are complex,and often have the characteristics of multi-mode and mode changing,whereas,it can still use the non-variable characteristics roots to describe the electromechanical oscillation modes in second time window.Through the comparison of sliding window spectral components,the damping and the changing of mode can be identified.Because of LFO narrow bandwidth,in order to improve the noise immunity,spectrum analysis method based on Fourier Basis Functions neural network are used.The dominant mode frequency can be calculated by the weights.Through the sliding window training,the damping,magnitude and mode changes can be identified.Sliding-window analysis are suitable for the measured data on-line analysis process.The improved spectral analysis method not only retains the original engineering experience,but also solves practical problems.In the case of interference and multi-mode,simulation results show that the method has good noise resistance characteristics,and identifies more accuracy." @default.
- W2371583031 created "2016-06-24" @default.
- W2371583031 creator A5038311574 @default.
- W2371583031 date "2013-01-01" @default.
- W2371583031 modified "2023-09-28" @default.
- W2371583031 title "Low frequency oscillation sliding window spectrum analysis method for dominant modes of low frequency oscillation" @default.
- W2371583031 hasPublicationYear "2013" @default.
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