Collaborative Identification Of Power System Oscillation And Coherent Mode Based On Wide Area Measurement Information

With the development of interconnected power system and the increasing electric load, Inter regional power oscillation has become one of the important factors to limit inter regional transmission capacity, and threaten the security and stability of power grid. Accurate identification of power system oscillation modes is of great significance to the online security assessment and stability control of power grid. At the same time, in order to realize the dynamic stability analysis of large power systems subjected to disturbance, we need to divide the large scale systems several subsystems. The coherency method is one of effective methods to decouple the system. This paper proposes a novel spatial-temporal decomposition approach for systematically tracking dominant modes, mode shapes and coherent groups in bulk power systems using measurement data. First, to ensure that edge effect of wavelet transform does not affect the calculation of the RCWT proposed in this paper, least squares support vector machine(LS-SVM) is introduced to handle the problem to improve the accuracy of the calculated wavelet coefficients at both ends of the time window. Secondly, components of the dominant oscillation modes, including frequencies and damping ratios, are identified from measurement data retrieved from phasor measurement units(PMUs) through a proposed Recursive Continuous Wavelet Transform(RCWT). Furthermore, a reconstructed wavelet coefficient, which integrates the wavelet coefficients of all the estimated dominant modes, is used to identify the coherent groups of generators via the Cross-Correlation Coefficient(C3). The proposed approach is applied and evaluated on the simulation data from the 16-machine 68-bus test system and China Southern power Grid(CSG) to show the feasibility of the proposed method.