Skip to main content

Dynamic topology adaptation for distributed estimation in smart grids

Author(s): Xu, Songcen; de Lamare, Rodrigo C; Poor, H Vincent

Download
To refer to this page use: http://arks.princeton.edu/ark:/88435/pr1028pd2k
Full metadata record
DC FieldValueLanguage
dc.contributor.authorXu, Songcen-
dc.contributor.authorde Lamare, Rodrigo C-
dc.contributor.authorPoor, H Vincent-
dc.date.accessioned2024-02-18T06:00:14Z-
dc.date.available2024-02-18T06:00:14Z-
dc.date.issued2014-01-20en_US
dc.identifier.citationXu, Songcen, de Lamare, Rodrigo C, Poor, H Vincent. (2013). Dynamic topology adaptation for distributed estimation in smart grids. 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 10.1109/camsap.2013.6714097en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1028pd2k-
dc.description.abstractThis paper presents new dynamic topology adaptation strategies for distributed estimation in smart grids. A dynamic exhaustive search-based topology adaptation algorithm and a dynamic sparsity-inspired topology adaptation algorithm, which can exploit the topology of smart grids with poor-quality links and obtain performance gains, are proposed. An optimized combining rule, named the Hastings rule, is incorporated into the proposed dynamic topology adaptation algorithms. Compared with existing techniques for distributed estimation, the proposed algorithms have a better convergence rate and significantly improve the system performance. The performance of the proposed algorithms is compared with that of existing techniques in the IEEE 14-bus system.en_US
dc.language.isoen_USen_US
dc.relation.ispartof2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)en_US
dc.rightsAuthor's manuscripten_US
dc.titleDynamic topology adaptation for distributed estimation in smart gridsen_US
dc.typeConference Articleen_US
dc.identifier.doidoi:10.1109/camsap.2013.6714097-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

Files in This Item:
File Description SizeFormat 
1401.3148v1.pdf109.61 kBAdobe PDFView/Download


Items in OAR@Princeton are protected by copyright, with all rights reserved, unless otherwise indicated.