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A phase‐plane trajectory vector‐based method for real‐time identification of critical machines
Author(s) -
Yang Songhao,
Hojo Masahide,
Zhang Baohui
Publication year - 2018
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22722
Subject(s) - trajectory , identification (biology) , computation , computer science , phasor measurement unit , control theory (sociology) , moment (physics) , electric power system , power (physics) , transient (computer programming) , process (computing) , tracking (education) , cluster analysis , units of measurement , algorithm , control (management) , artificial intelligence , psychology , pedagogy , botany , physics , quantum mechanics , astronomy , classical mechanics , phasor , biology , operating system
The identification of critical machines (CMs) is the first and most important step of Equivalent‐Single Machine Infinite Bus based methods such as Extend Equal Area Criterion and SIngle Machine Equivalent (SIME) for transient stability assessment and control. This paper presents a novel real‐time CM identification method based on the Phase‐Plane Trajectory Vector (PTV) with Phase Measurement Unit (PMU) information support. The proposed method overcomes the drawbacks of conventional CM identification methods and enables the tracking of the change of CMs during the dynamic process. Only two sample points of all generators from PMUs are required to obtain the PTVs at each moment, and the computation of the feature matrix, as well as the k‐means clustering, is fast and accurate. The application of the PTV‐based method is verified through cases studied in the IEEE 39 bus New England power system. Results are compared with those obtained by conventional methods. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.