Spatial‐temporal decomposition approach for systematically tracking dominant modes, mode shapes and coherent groups in power systems

New signal subspace approach to estimate the inter‐area oscillatory modes in power system using TLS‐ESPRIT algorithm

“…Another time-frequency estimation approach, i.e. wavelet transform (WT), recursive continuous WT and multichannel WT (MCWT) [4][5][6], whose behaviour is the same as a band-pass filter. Change of window size in WT provides a multiresolution capability for both slow and fast frequency response.…”

Stochastic subspace identification based data‐driven approach for monitoring electromechanical dynamics from phasor measurement units

“…The mode shape estimation from ambient measurement data was initiated by Trudnowski [17]. Then, frequency domain decomposition [18], spectral method [19], channel matching method [20] and multichannel autoregressive moving average exogenous [21, 22] were proposed. It is worth pointing out that all these methods are special cases of the more general transfer function (TF) method.…”

Holistic data-driven framework for estimating electromechanical dynamic patterns from synchrophasor measurements in bulk power grids

“…The clustering‐based coherency separation methods have been validated to exhibit excellent performance in coherent groups separation, but the major drawback is that a priori parameter about the number of coherent groups or the clustering threshold is needed. Other than the mentioned clustering‐based coherent group estimation algorithms, the direction cosine was further used [26, 27 ].…”