Estimating the electromechanical oscillation characteristics of power system based on measured ambient data utilizing stochastic subspace method

Estimating low-frequency oscillation modes and the corresponding mode shapes based on ambient data from WAMS measurements has a promising prospect of application in power system analysis and control. The present approaches estimate the modes and mode shapes respectively, which greatly reduce the computational efficiency. Besides, there is no good solution for the problem of discriminating real modes from the spurious ones caused by numerical error. A method based on stochastic subspace method was proposed in this paper. By choosing the angle measurements of all buses as input signals for the method, the modes and simultaneously the corresponding mode shapes of any bus can be estimated conveniently. By introducing the idea of reference channels, the computation complexity was substantially reduced without decreasing the accuracy. Stabilization diagrams technique was introduced to discriminate the real modes from the spurious ones. The test case based on the IEEE-118 system indicated that the method proposed is satisfying in respect of both computational efficiency and accuracy of results.