Dynamic topology adaptation for distributed estimation in smart grids

Songcen Xu, Rodrigo C. De Lamare, H. Vincent Poor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

This 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.

Original languageEnglish (US)
Title of host publication2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013
Pages420-423
Number of pages4
DOIs
StatePublished - 2013
Event2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013 - Saint Martin, France
Duration: Dec 15 2013Dec 18 2013

Publication series

Name2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013

Other

Other2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013
Country/TerritoryFrance
CitySaint Martin
Period12/15/1312/18/13

All Science Journal Classification (ASJC) codes

  • Computer Science Applications

Keywords

  • Dynamic topology adaptation
  • distributed estimation
  • smart grids

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