State estimation in power engineering using the Huber robust regression technique

Elias Kyriakides; Siddharth Suryanarayanan; Gerald T. Heydt

doi:10.1109/TPWRS.2005.846157

State estimation in power engineering using the Huber robust regression technique

Elias Kyriakides, Siddharth Suryanarayanan, Gerald T. Heydt

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

14 Scopus citations

Abstract

The least-squares method has been used extensively for state estimation in electric power engineering. However, this method is not always suitable when the process matrix is characterized by structural defects. This letter demonstrates the Huber function technique in a power engineering application. This technique is a slight departure from the least-squares method and downweighs large residuals. A statistical test to identify possible structural imperfections in the model is introduced.

Original language	English (US)
Pages (from-to)	1183-1184
Number of pages	2
Journal	IEEE Transactions on Power Systems
Volume	20
Issue number	2
DOIs	https://doi.org/10.1109/TPWRS.2005.846157
State	Published - May 2005

Keywords

Huber
Least squares
Multicollinearity
Rank
Robust estimation
State estimation
Synchronous generators

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering

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10.1109/TPWRS.2005.846157

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title = "State estimation in power engineering using the Huber robust regression technique",

abstract = "The least-squares method has been used extensively for state estimation in electric power engineering. However, this method is not always suitable when the process matrix is characterized by structural defects. This letter demonstrates the Huber function technique in a power engineering application. This technique is a slight departure from the least-squares method and downweighs large residuals. A statistical test to identify possible structural imperfections in the model is introduced.",

keywords = "Huber, Least squares, Multicollinearity, Rank, Robust estimation, State estimation, Synchronous generators",

author = "Elias Kyriakides and Siddharth Suryanarayanan and Heydt, {Gerald T.}",

note = "Funding Information: Manuscript received February 26, 2004; revised May 20, 2004. This work was supported in part by the Power Systems Engineering Research Center (PSERC) and by Arizona Public Service (APS). Paper no. PESL-00020-2004. E. Kyriakides is with the University of Cyprus, 1678 Nicosia, Cyprus (e-mail: elias@ucy.ac.cy). G. T. Heydt is with Arizona State University, Tempe, AZ 85287 USA (e-mail: heydt@asu.edu). S. Suryanarayanan is with Florida State University, Tallahassee, FL 32310 USA (e-mail: sid.suryanarayanan@ieee.org). Digital Object Identifier 10.1109/TPWRS.2005.846157",

year = "2005",

month = may,

doi = "10.1109/TPWRS.2005.846157",

language = "English (US)",

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AU - Kyriakides, Elias

AU - Suryanarayanan, Siddharth

AU - Heydt, Gerald T.

N1 - Funding Information: Manuscript received February 26, 2004; revised May 20, 2004. This work was supported in part by the Power Systems Engineering Research Center (PSERC) and by Arizona Public Service (APS). Paper no. PESL-00020-2004. E. Kyriakides is with the University of Cyprus, 1678 Nicosia, Cyprus (e-mail: elias@ucy.ac.cy). G. T. Heydt is with Arizona State University, Tempe, AZ 85287 USA (e-mail: heydt@asu.edu). S. Suryanarayanan is with Florida State University, Tallahassee, FL 32310 USA (e-mail: sid.suryanarayanan@ieee.org). Digital Object Identifier 10.1109/TPWRS.2005.846157

PY - 2005/5

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N2 - The least-squares method has been used extensively for state estimation in electric power engineering. However, this method is not always suitable when the process matrix is characterized by structural defects. This letter demonstrates the Huber function technique in a power engineering application. This technique is a slight departure from the least-squares method and downweighs large residuals. A statistical test to identify possible structural imperfections in the model is introduced.

AB - The least-squares method has been used extensively for state estimation in electric power engineering. However, this method is not always suitable when the process matrix is characterized by structural defects. This letter demonstrates the Huber function technique in a power engineering application. This technique is a slight departure from the least-squares method and downweighs large residuals. A statistical test to identify possible structural imperfections in the model is introduced.

KW - Huber

KW - Least squares

KW - Multicollinearity

KW - Rank

KW - Robust estimation

KW - State estimation

KW - Synchronous generators

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State estimation in power engineering using the Huber robust regression technique

Abstract

Keywords

ASJC Scopus subject areas

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