A framework for phasor measurement placement in hybrid state estimation via Gauss-Newton

Xiao Li, Anna Scaglione, Tsung Hui Chang

Research output: Contribution to journalArticle

23 Scopus citations

Abstract

In this paper, we study the placement of phasor measurement units (PMU) for enhancing hybrid state estimation via the traditional Gauss-Newton method, which uses measurements from both PMU devices and Supervisory Control and Data Acquisition (SCADA) systems. To compare the impact of PMU placements, we introduce a useful metric which accounts for three important requirements in power system state estimation: convergence, observability and performance (COP). Our COP metric can be used to evaluate the estimation performance and numerical stability of the state estimator, which is later used to optimize the PMU locations. In particular, we cast the optimal placement problem in a unified formulation as a semi-definite program (SDP) with integer variables and constraints that guarantee observability in case of measurements loss. Last but not least, we propose a relaxation scheme of the original integer-constrained SDP with randomization techniques, which closely approximates the optimum deployment. Simulations of the IEEE-30 and 118 systems corroborate our analysis, showing that the proposed scheme improves the convergence of the state estimator, while maintaining optimal asymptotic performance.

Original languageEnglish (US)
Article number6632977
Pages (from-to)824-832
Number of pages9
JournalIEEE Transactions on Power Systems
Volume29
Issue number2
DOIs
StatePublished - Mar 1 2014

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Keywords

  • Convergence
  • estimation
  • optimal placement

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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