Power system low-frequency oscillation online identification method based on recursive stochastic subspace

The invention relates to a power system low-frequency oscillation online identification method based on a recursive stochastic subspace. According to the method, in order to solve the problem that the real-time performance and dynamic identification effect of low-frequency oscillation modal identification are poor due to the need of SVD decomposition with high algorithm complexity in a stochastic subspace identification algorithm, a forgetting factor is introduced to update a Hankel covariance matrix, and a projection approximation subspace tracking method is used to perform recursive operation on the subspace. Thus, SVD operation is avoided, and the computational complexity is reduced significantly. In each recursive calculation, the complexity of the algorithm of the invention is 3In+O(I ), which is far lower than O(I ), the complexity of SVD calculation. By adopting the method of the invention, the real-time performance of identification can be improved effectively. The invention is suitable for online identification of low-frequency oscillation modal, and can provide effective support for power system online monitoring and stability analysis under multiple spatial and temporal scales.