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

Access to Document

10.1080/073135600268397

Cite this

@article{782ae0ebe0324dc6bbf8b7e727fe8905,

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",

author = "Habiballah, \{Ibrahim O.\} and Irving, \{M. R.\}",

year = "2000",

month = feb,

doi = "10.1080/073135600268397",

language = "English",

volume = "28",

pages = "105--114",

journal = "Electric Machines and Power Systems",

issn = "0731-356X",

publisher = "Taylor and Francis Ltd.",

number = "2",

}

TY - JOUR

T1 - A comparative study of three LS-based power system state estimators for bad data identification

AU - Habiballah, Ibrahim O.

AU - Irving, M. R.

PY - 2000/2

Y1 - 2000/2

N2 - 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.

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

U2 - 10.1080/073135600268397

DO - 10.1080/073135600268397

M3 - Article

AN - SCOPUS:21544484087

SN - 0731-356X

VL - 28

SP - 105

EP - 114

JO - Electric Machines and Power Systems

JF - Electric Machines and Power Systems

IS - 2

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this