Reference : Online Fault Diagnosis for Nonlinear Power Systems
Scientific journals : Article
Engineering, computing & technology : Multidisciplinary, general & others
Online Fault Diagnosis for Nonlinear Power Systems
Pan, Wei mailto []
Yuan, Ye mailto [University of Cambridge]
Sandberg, Henrik []
Goncalves, Jorge mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Stan, Guy-Bart []
Pergamon Press - An Imprint of Elsevier Science
Yes (verified by ORBilu)
United Kingdom
[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 optimisationbased
formulation of the fault identification problem. An
iterative reweighted `1-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
Luxembourg Centre for Systems Biomedicine (LCSB): Systems Control (Goncalves Group)

File(s) associated to this reference

Fulltext file(s):

Limited access
Real-time Fault Diagnosis for Large-Scale Nonlinear Power Networks.pdfAuthor preprint402.99 kBRequest a copy

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.