@inproceedings{d6d1ec0fe5044ab580d1fb29188ba3b0,
title = "Localization of forced oscillations in the power grid under resonance conditions",
abstract = "This paper proposes a data-driven method to pin-point the source of a new emerging dynamical phenomenon in the power grid, referred to 'forced oscillations' in the difficult but highly risky case where there is a resonance phenomenon. By exploiting the low-rank and sparse properties of synchrophasor measurements, the localization problem is formulated as a matrix decomposition problem, which can be efficiently solved by the exact augmented Lagrange multiplier algorithm. An online detection scheme is developed based on the problem formulation. The data-driven nature of the proposed method allows for a very efficient implementation. The efficacy of the proposed method is illustrated in a 68-bus power system. The proposed method may possibly be more broadly useful in other situations for identifying the source of forced oscillations in resonant systems.",
keywords = "Big Data, Forced oscillations, phasor measurement unit (PMU), resonant systems, robust principal component analysis (RPCA)",
author = "Tong Huang and Freris, {Nikolaos M.} and Kumar, {P. R.} and Le Xie",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 52nd Annual Conference on Information Sciences and Systems, CISS 2018 ; Conference date: 21-03-2018 Through 23-03-2018",
year = "2018",
month = may,
day = "21",
doi = "10.1109/CISS.2018.8362302",
language = "English (US)",
series = "2018 52nd Annual Conference on Information Sciences and Systems, CISS 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--5",
booktitle = "2018 52nd Annual Conference on Information Sciences and Systems, CISS 2018",
}