Open AccessMode matching pursuit for estimating dominant modes in bulk power grid
Author(s) -
Jiang Tao,
Jia Hongjie,
Zhao Jinli,
Ledwich Gerard,
Wang Dan,
Zhang Jinan,
Qiu Lulu
Publication year - 2014
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2013.0730
Subject(s) - robustness (evolution) , outlier , oscillation (cell signaling) , subspace topology , mode (computer interface) , computer science , electric power system , grid , control theory (sociology) , low frequency oscillation , power (physics) , algorithm , mathematics , physics , artificial intelligence , biochemistry , chemistry , genetics , geometry , control (management) , quantum mechanics , biology , gene , operating system
This study presents a general approach to identify dominant oscillation modes in bulk power system by using wide‐area measurement system. To automatically identify the dominant modes without artificial participation, spectral characteristic of power system oscillation mode is applied to distinguish electromechanical oscillation modes which are calculated by stochastic subspace method, and a proposed mode matching pursuit is adopted to discriminate the dominant modes from the trivial modes, then stepwise‐refinement scheme is developed to remove outliers of the dominant modes and the highly accurate dominant modes of identification are obtained. The method is implemented on the dominant modes of China Southern Power Grid which is one of the largest AC/DC paralleling grids in the world. Simulation data and field‐measurement data are used to demonstrate high accuracy and better robustness of the dominant modes identification approach.