With the large-scale integration of wind power,power system subsynchronous oscillation(SSO)events occur frequently,which seriously threatens the safe and stable operation of the power grid.The accurate detection of SSO in wind power grid-connected system is of great significance to ensure the stable operation of the power systems.Most of the existing SSO detection methods are single-channel methods,which are difficult to take into account the global SSO characteristics of the systems.Therefore,this paper proposes a SSO detection method for wind power grid-connected system based on multivariate empirical mode decomposition(MEMD).Firstly,the multivariate empirical mode decomposition is performed on the measurements of wind power grid-connected points,and then the IMF components with SSO mode are screened out via Teager-Kaiser energy operator(TKEO).Then,the Hilbert-Huang transform(HHT)is used to identify the SSO frequency and damping ratio.Finally,the proposed detection method is analyzed by the improved 4-machine 2-area system simulation data,and the results verify the effectiveness of the proposed method.
关键词
次同步振荡检测/量测信息/多元经验模态分解/Teager-Kaiser能量算子/希尔伯特黄变换
Key words
subsynchronous oscillation detection/measurements/multivariate empirical mode decomposition/Teager-Kaiser energy operator/Hilbert-Huang transform
维普
万方数据