Identification of Coherent Generator Groups Based on Stochastic Subspace Algorithm

With continuous expansion of power grid scale, the research of low-frequency oscillation has been the hot spot of power system stable operation. The load of power system possesses the characteristic of continuous variation in certain time span. This variation usually is random, and its effect can be simulated by the influence of ambient noise on system. The conventional analysis method, getting state matrix from system mathematic model, has encountered application limitation. Therefore, under the premise of ambient noise, this chapter adopted stochastic subspace method to identify coherence generator group which is in low-frequency oscillation. Based on state-space model and measured signal, by identifying system state matrix through stochastic subspace method and analyzing its eigenvalue, the method of identifying system coherence generators could be found. Through analyzing the system example of 3 generators and 9 nodes, and 16 generators and 68 nodes, the result indicated that the identification method this chapter adopted had higher identification accuracy and calculation efficiency.