A Novel Subspace Decomposition with Rotational Invariance Technique to Estimate Low-Frequency Oscillatory Modes of the Power Grid

Abstract

. Tis paper proposes modifed Karhunen–Loeve transform with total least square estimation of signal parameters using rotational in-variance technique (MKLT-TLS-ESPRIT) to approximate the low-frequency oscillatory modes. MKLTdecreases the impact of highly correlated additive colored Gaussian noise (ACGN) from the signal by diferentiating the correlation matrix w.r.t from the fnal time instance. A quantitative study of the suggested method with other estimation methods is used to evaluate the effectiveness of the proposed method. Monte Carlo simulations with 50,000 runs are conducted to test the robustness of the estimation scheme for MKLT-TLS-ESPRIT. Te evaluation of the efciency of the proposed method in real-time perspective, the two-area system, and New England sixty-eight bus test system has been considered. Te analysis shows that the suggested methodology correctly measures the interarea modes and lowers their mean and standard deviation to a minimum value.