A comparative study of three LS-based power system state estimators for bad data identification

Ibrahim O. Habiballah; M. R. Irving

doi:10.1080/073135600268397

A comparative study of three LS-based power system state estimators for bad data identification

Ibrahim O. Habiballah^*, M. R. Irving

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

This paper presents a comparative study between three least squares–based state estimators. The study compares the performance of these estimators in identifying the presence of bad measurements of different types and magnitudes. Running a series of simulations with varying measurement redundancies assesses the performance of these estimators.

Original language	English
Pages (from-to)	105-114
Number of pages	10
Journal	Electric Machines and Power Systems
Volume	28
Issue number	2
DOIs	https://doi.org/10.1080/073135600268397
State	Published - Feb 2000

Keywords

Bad data identification
Least squares
State estimators

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1080/073135600268397

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title = "A comparative study of three LS-based power system state estimators for bad data identification",

abstract = "This paper presents a comparative study between three least squares–based state estimators. The study compares the performance of these estimators in identifying the presence of bad measurements of different types and magnitudes. Running a series of simulations with varying measurement redundancies assesses the performance of these estimators.",

keywords = "Bad data identification, Least squares, State estimators",

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year = "2000",

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AU - Irving, M. R.

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AB - This paper presents a comparative study between three least squares–based state estimators. The study compares the performance of these estimators in identifying the presence of bad measurements of different types and magnitudes. Running a series of simulations with varying measurement redundancies assesses the performance of these estimators.

KW - Bad data identification

KW - Least squares

KW - State estimators

UR - https://www.scopus.com/pages/publications/21544484087

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DO - 10.1080/073135600268397

M3 - Article

AN - SCOPUS:21544484087

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VL - 28

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JO - Electric Machines and Power Systems

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ER -

A comparative study of three LS-based power system state estimators for bad data identification

Abstract

Keywords

ASJC Scopus subject areas

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