Robust state-estimation procedure using a least trimmed squares pre-processor

Yang Weng, Rohit Negi, Qixing Liu, Marija D. Ilić

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

11 Scopus citations

Abstract

Based on real-time measurements, Static State Estimation serves as the foundation for monitoring and controlling the power grid. The popular weighted least squares with largest normalized residual removed, gives satisfactory performance when dealing with single or multiple uncorrelated bad data. However, when the bad data are correlated or bounded, this estimator has poor performance in detecting bad data, which leads to erroneous deleting of normal measurements. Similar to the Least Trimmed Squares(LTS) method of robust statistics, this paper considers a state estimator built on random sampling. However, different from previous robust estimators, which stop after estimation, we regard the LTS estimator as a pre-processor to detect bad data. A subsequent post-processor is employed to eliminate bad data and re-estimate the state. The new method has been tested on the IEEE standard power networks with random bad data insertions, showing improved performance over other proposed estimators.

Original languageEnglish (US)
Title of host publication2011 IEEE PES Innovative Smart Grid Technologies, ISGT 2011
DOIs
StatePublished - Jun 9 2011
Event2011 IEEE PES Innovative Smart Grid Technologies, ISGT 2011 - Anaheim, CA, United States
Duration: Jan 17 2011Jan 19 2011

Publication series

NameIEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe

Other

Other2011 IEEE PES Innovative Smart Grid Technologies, ISGT 2011
CountryUnited States
CityAnaheim, CA
Period1/17/111/19/11

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Cite this

Weng, Y., Negi, R., Liu, Q., & Ilić, M. D. (2011). Robust state-estimation procedure using a least trimmed squares pre-processor. In 2011 IEEE PES Innovative Smart Grid Technologies, ISGT 2011 [5759135] (IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe). https://doi.org/10.1109/ISGT.2011.5759135