An adaptive method for detection and correction of errors in PMU measurements

Di Shi, Daniel Tylavsky, Naim Logic

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

PMU data are expected to be GPS-synchronized measurements with highly accurate magnitude and phase angle information. However, this potential accuracy is not always achieved in actual field installations due to various causes. It has been observed in some PMU measurements that the voltage and current phasors are corrupted by noise and bias errors. This paper presents a novel method for detection and correction of errors in PMU measurements with the concept of calibration factors. The proposed method uses nonlinear optimal estimation theory to calculate calibration factor using a traditional model of an untransposed transmission line with unbalanced load. This method is intended to work as a prefiltering scheme that can significantly improve the accuracy of the PMU measurement for further use in system state estimation, transient stability monitoring, wide area protection, etc. Case studies based on simulated data are presented to demonstrate the effectiveness and robustness of the proposed method.

Original languageEnglish (US)
Article number6279481
Pages (from-to)1575-1583
Number of pages9
JournalIEEE Transactions on Smart Grid
Volume3
Issue number4
DOIs
StatePublished - Aug 27 2012

Keywords

  • Bad data detection
  • PMU measurements
  • bias errors
  • calibration factor
  • non-linear estimation theory
  • transmission line modeling

ASJC Scopus subject areas

  • Computer Science(all)

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