Frequency mode identification using modified masking signal‐based empirical mode decomposition. Issue 8 (27th March 2019)

• Record Type: Journal Article
• Authors: Ray, Papia; Lenka, Rajesh Kumar; Biswal, Monalisa
• Is Part Of: IET generation, transmission & distribution. Volume 13:Issue 8(2019)
• Page Start: 1266
• Page End: 1276
• Publication Date: 2019-03-27
• Subjects: spectral analysis -- time‐frequency analysis -- power system measurement -- Hilbert transforms -- signal processing; extracted modes -- WAMS signal -- frequency mode identification -- modified masking signal‐based empirical mode decomposition -- modified masking empirical mode decomposition -- mode separation capability -- standard EMD -- analysing power system signals -- multifrequency test signal -- dynamic power system signal -- wide area measurement systems -- modal frequency -- signal base EMD -- modified masking EMD -- time–frequency representation; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2018.5527
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : A modified masking empirical mode decomposition (EMD) for effectively improving the mode separation capability of standard EMD while analysing power system signals with closely spaced modes of frequency is proposed here. A multi‐frequency test signal resembling the dynamic power system signal and the actual data recorded by wide area measurement systems (WAMS) from Northern Grid, India, on 1 June 2010 due to generation loss are analysed by both the existing method and the proposed method. Various components of modal frequency extracted by masking signal base EMD are compared with extracted components by the proposed modified masking EMD. Further, the time–frequency representation of extracted modes by Hilbert spectral analysis is implemented to know mode behaviour with time reference. Simulation results prove that the EMD with proposed modification is capable of separating various modes of frequencies present in the WAMS signal.