An efficient K-SVD based Algorithm for detection of Oscillatory mode from ambient data for synchrophasor application

In this paper, an efficient implementation of K-SVD based technique over a learned dictionary to extract the critical modes from the ambient data is presented. The technique creates an appropriate dictionary iteratively and selects the optimal set of sparse coefficients to extract the clean signal for better estimation of the mode. To prove the effectiveness of the proposed technique, a comparative study of simulation results of the proposed approach with other technique such as sparsity technique and RDT-TLS-ESPRIT is carried out for simulated test signal, the real-time phasor measurement unit (PMU) data of indian power system, and the real-time probing data of Western Electricity Coordinating Council (WECC) network through Matlab simulation.