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Robust principal component analysis‐based coherency identification of generators with missing PMU measurements
Author(s) -
Qing Xiangyun,
Wang Shaobo,
Jia Tinggang,
Niu Yugang
Publication year - 2016
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.22186
Subject(s) - phasor measurement unit , principal component analysis , phasor , electric power system , identification (biology) , units of measurement , component (thermodynamics) , generator (circuit theory) , computer science , engineering , power (physics) , artificial intelligence , physics , botany , quantum mechanics , biology , thermodynamics
This study provides a new algorithm for grouping coherent generators in power systems using robust principal component analysis. In coherency identification of generators based on measurements by a phasor measurement unit (PMU), PMU measurements can become unavailable because of unexpected failure of data acquisition or communication links. However, the proposed algorithm is robust to missing PMU measurements and is demonstrated on an IEEE 16‐generator 68‐bus system. This effective identification of coherent clusters with missing PMU measurements is validated and compared with results obtained using the principal component analysis and independent component analysis methods. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.