An efficient wavelet based technique for oscillatory mode identification of ambient data via RD and TLS-ESPRIT

摘要

This paper proposes a spectral estimation technique for identification of inter-area oscillatory modes using ambient data. In order to mitigate the effect of high noise level, the proposed method has used a combination of wavelet, random decrement (RD) and modified TLS-ESPRIT for mode identification. The main contribution of this paper is to find the optimal set of wavelet coefficients to represent the clean signal for mode estimation. The proposed method is compared with non-linear filtering and random decrement technique-Ibrahim time domain (RDT-ITD) method over the synthetic signals resembling ambient signals. The effectiveness of the proposed method is further validated for real time ambient data obtained from a PMU located in North Eastern Regional Electricity Board (NEREB) of India and on the probing data of the Western Electricity Coordinating Council (WECC).