Optimal sensor placement for hybrid state estimation in smart grid

Xiao Li, Anna Scaglione, Tsung Hui Chang

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

7 Scopus citations

Abstract

A critical task in smart grid is to gain situational awareness by performing state estimation. In this paper, we consider the problem of placing a type of special sensors, called Phasor Measurement Units (PMU), to optimize the performance and convergence of state estimation. We derive a metric to evaluate how the placement impacts the convergence and accuracy of state estimation solved by Gauss-Newton (GN) algorithm. Using the proposed metric, we formulate and solve the placement problem as a semi-definite program (SDP). Simulations of the IEEE 30 and 118 systems corroborate our analysis, showing that the proposed placement stabilizes and accelerates state estimation, while maintaining optimal estimation performance.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages5253-5257
Number of pages5
DOIs
StatePublished - Oct 18 2013
Externally publishedYes
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: May 26 2013May 31 2013

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period5/26/135/31/13

Keywords

  • Optimal placement
  • convergence
  • estimation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Li, X., Scaglione, A., & Chang, T. H. (2013). Optimal sensor placement for hybrid state estimation in smart grid. In 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings (pp. 5253-5257). [6638665] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2013.6638665