Non‐linear dynamics based sub‐synchronous resonance index by using power system measurement data. Issue 17 (28th August 2018)

• Record Type: Journal Article
• Authors: Cho, Hwanhee; Oh, Seungchan; Nam, Suchul; Lee, Byongjun
• Is Part Of: IET generation, transmission & distribution. Volume 12:Issue 17(2018)
• Page Start: 4026
• Page End: 4033
• Publication Date: 2018-08-28
• Subjects: time series -- Lyapunov methods -- least mean squares methods -- power system stability -- power system measurement; nonlinear dynamics -- sub‐synchronous resonance index -- power system measurement data -- time‐series analysis approach -- sub‐synchronous oscillation -- mathematical expressions -- fundamental instantaneous signal -- sample discrete signal -- peak values -- power system components -- calculated root‐mean‐square value -- nonlinear oscillation detection -- nonlinear oscillatory index -- maximum Lyapunov exponent -- root‐mean‐square value -- estimated Floquet multiplier -- digital filter -- frequency decomposition; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2018.5414
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : This study proposes a time‐series analysis approach and a non‐linear dynamics originated method to detect sub‐synchronous oscillation in power systems. Mathematical expressions of the fundamental instantaneous signal and sample discrete signal of peak values are derived to examine the phenomenon of interaction between power system components. The results of the circulating trajectory are shown in a two‐dimensional map of the calculated root‐mean‐square value and estimated Floquet multiplier when two signals of different modes are mixed. Without applying a digital filter or frequency decomposition, non‐linear oscillation detection is possible by monitoring a non‐linear oscillatory index based on the maximum Lyapunov exponent.