A robust ALOHA and sequential clustering-based mode estimator for low frequency oscillations in power system using...

Accurate estimation of low frequency modes in power system are very much important for improving small signal stability. The parametric model parameters estimator known as Total least square estimation of signal parameters via rotational invariance techniques (TLS-ESPRIT) works effectively even in noisy conditions. However, this model parameter estimator requires prior information about numbers of modes of the signal. There are different Model order (MO) estimation techniques discussed in the recent past, which consider the significant eigenvalues of auto-correlation matrix (ACM) for its estimation. As the eigenvalues of ACM highly affected by bad measurements and Outliers, making these techniques inefficient and harder to automate in real time. So, to overcome aforementioned limitations, this paper proposes a robust mode estimation technique that can precisely detect the signal low frequency modes even in the presence of high variance noise and outliers. So, in this proposed work, an annihilating filter-based low-rank Hankel matrix (ALOHA) technique is implemented to obtain the rank deficient Hankel matrix to nullify the existence of noise and outliers in Phasor measurement unit (PMU) signal, thereafter approximated low rank Hankel matrix is considered for estimation of signals dominant modes. Wherein a sequential clustering technique (Sequential K-Mean++) is implemented for detection of numbers of prominent low frequency modes by segregating eigenvalues of ACM into two opponents i.e the signal and noise subspace. Thereafter the estimated MO is considered for estimation of modes through TLS-ESPRIT. The robustness of the proposed technique is validated by scheduling comparative study with recently developed techniques for synthetic signal, two area data, real PMU data of Western Electricity Coordinating Council (WECC) and oscillatory power data obtained from Western System Coordinating Council (WSCC) 9 bus system and IEEE68 bus system simulated through Real Time Digital Simulator (RTDS).