Reference : Real-time Fault Diagnosis for Large-Scale Nonlinear Power Networks
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Multidisciplinary, general & others
http://hdl.handle.net/10993/20336
Real-time Fault Diagnosis for Large-Scale Nonlinear Power Networks
English
Pan, Wei mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Yuan, Ye mailto []
Sandberg, Henrik []
Goncalves, Jorge mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Stan, Guy-Bart []
2013
The proceedings of the IEEE 52nd Annual Conference on Decision and Control
IEEE
2340 - 2345
Yes
978-1-4673-5714-2
IEEE 52nd Annual Conference on Decision and Control
December 10-13, 2013
Florence
Italy
[en] In this paper, automatic fault diagnosis in large scale power networks described by second-order nonlinear swing equations is studied. This work focuses on a class of faults that occur in the transmission lines. Transmission line protection is an important issue in power system engineering because a large portion of power system faults is occurring in transmission lines. This paper presents a novel technique to detect, isolate and identify the faults on transmissions using only a small number of observations. We formulate the problem of fault diagnosis of nonlinear power network into a compressive sensing framework and derive an optimisation-based formulation of the fault identification problem. An iterative reweighted ℓ1-minimisation algorithm is finally derived to solve the detection problem efficiently. Under the proposed framework, a real-time fault monitoring scheme can be built using only measurements of phase angles of nonlinear power networks.
http://hdl.handle.net/10993/20336

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