Estimating Electromechanical Oscillation Modes from Synchrophasor Measurements in Bulk Power Grids Using Fast Iterative Stochastic Subspace Identification

Multi-order stochastic subspace identification (MOSSI) has been extensively used to estimate the electromechanical oscillation modes from probing, ambient and ringdown data. It has been validated with good performances, while the computational burden is still a major obstacle. This study develops a fast iterative MOSSI (FSSI) approach for computational enhancement of MOSSI in mode estimation. In the proposed approach, an initial cluster of eigenvalues is formulated through FSSI with repetitive calculations (RCs), and electromechanical oscillation mode separation (EOMS) is utilised to discriminate the electromechanical modes. The RCs within the FSSI is calculated through changing the model order successively over the defined range given by a mean of singular values based order determination strategy. Additionally, the proposed approach is highly reliable against prevalent measurement noises owing to RCs and the EOMS. The performance of the proposed method is evaluated in Kundur's two-area test system by comparing with MOSSI, Prony and autoregressive moving average exogenous. Its applicability for both the ringdown and ambient data is also demonstrated with the phasor measurement units field-measurement data from the China Southern Power Grid. The results confirmed the accuracy, robustness and efficiency of the proposed approach for oscillation mode estimation.