The application discloses a kind of power
system low-
frequency oscillation characteristic
signal extraction methods, comprising: the electrical variation data of acquisition each generator outlet is preprocessed;Through complementary ensemble empirical mode
decomposition, variation data is decomposed, and
noise component is filtered out;SPA
smoothing algorithm is used to process the electrical variation
signal after denoising;
Prony method is used to decompose the
signal after
smoothing, and the amplitude and phase of each frequency component are extracted;The application has more excellent
noise suppression capability and
signal fidelity, can effectively solve the problem of
modal aliasing, can adaptively identify and filter out various
noise components, and shows good adaptability to noise interference under different operating conditions of power
system;SPA
smoothing algorithm reduces the error introduced by complementary ensemble empirical mode
decomposition while effectively retaining the key features of low-
frequency oscillation;Combined with
Prony method, the characteristic parameters of the oscillation signal can be accurately extracted in a strong noise environment, providing a reliable data basis for low-
frequency oscillation source identification.