State estimation accuracy of tuned least measurement rejected estimator

Farhan Ammar Ahmad; Mohammad Shoaib Shahriar; Ibrahim Omar Habiballah; Aun Haider

doi:10.1109/ICEE.2018.8566701

State estimation accuracy of tuned least measurement rejected estimator

Farhan Ammar Ahmad, Mohammad Shoaib Shahriar, Ibrahim Omar Habiballah, Aun Haider

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Weighted Least Square (WLS) and Weighted Least Absolute Value (WLAV) estimators are most commonly employed in electric power industry. WLS fails in the presence of bad data and WLAV estimator has large computational burden. Least Measurement Rejected (LMR) is a robust estimator which can handle bad data efficiently and has lower computational burden. LMR estimator has an important tolerance parameter which is used to reject bad data during estimation process. In this paper, an iterative tuning approach for the tolerance parameter of LMR has been proposed. The accuracy and computational efficiency of the proposed approach have been compared with most commonly used WLS and WLAV estimators. The accuracy has been computed in terms of Cumulative Estimation Error (CEE) indicator for IEEE-30 and IEEE-118 bus systems.

Original language	English
Title of host publication	2018 International Conference on Electrical Engineering, ICEE 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538609224
DOIs	https://doi.org/10.1109/ICEE.2018.8566701
State	Published - 6 Dec 2018

Publication series

Name	2018 International Conference on Electrical Engineering, ICEE 2018

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

Bad Data
Least Measurement Rejected
State Estimation
Weighted Least Absolute Value
Weighted Least Square

ASJC Scopus subject areas

Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering

Access to Document

10.1109/ICEE.2018.8566701

Cite this

Ahmad, F. A., Shahriar, M. S., Habiballah, I. O., & Haider, A. (2018). State estimation accuracy of tuned least measurement rejected estimator. In 2018 International Conference on Electrical Engineering, ICEE 2018 Article 8566701 (2018 International Conference on Electrical Engineering, ICEE 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICEE.2018.8566701

@inproceedings{307917e331e1419b9a46d1c9b64a916d,

title = "State estimation accuracy of tuned least measurement rejected estimator",

abstract = "Weighted Least Square (WLS) and Weighted Least Absolute Value (WLAV) estimators are most commonly employed in electric power industry. WLS fails in the presence of bad data and WLAV estimator has large computational burden. Least Measurement Rejected (LMR) is a robust estimator which can handle bad data efficiently and has lower computational burden. LMR estimator has an important tolerance parameter which is used to reject bad data during estimation process. In this paper, an iterative tuning approach for the tolerance parameter of LMR has been proposed. The accuracy and computational efficiency of the proposed approach have been compared with most commonly used WLS and WLAV estimators. The accuracy has been computed in terms of Cumulative Estimation Error (CEE) indicator for IEEE-30 and IEEE-118 bus systems.",

keywords = "Bad Data, Least Measurement Rejected, State Estimation, Weighted Least Absolute Value, Weighted Least Square",

author = "Ahmad, \{Farhan Ammar\} and Shahriar, \{Mohammad Shoaib\} and Habiballah, \{Ibrahim Omar\} and Aun Haider",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.",

year = "2018",

month = dec,

day = "6",

doi = "10.1109/ICEE.2018.8566701",

language = "English",

series = "2018 International Conference on Electrical Engineering, ICEE 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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address = "United States",

}

Ahmad, FA, Shahriar, MS, Habiballah, IO & Haider, A 2018, State estimation accuracy of tuned least measurement rejected estimator. in 2018 International Conference on Electrical Engineering, ICEE 2018., 8566701, 2018 International Conference on Electrical Engineering, ICEE 2018, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICEE.2018.8566701

State estimation accuracy of tuned least measurement rejected estimator. / Ahmad, Farhan Ammar; Shahriar, Mohammad Shoaib; Habiballah, Ibrahim Omar et al.
2018 International Conference on Electrical Engineering, ICEE 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8566701 (2018 International Conference on Electrical Engineering, ICEE 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - State estimation accuracy of tuned least measurement rejected estimator

AU - Ahmad, Farhan Ammar

AU - Shahriar, Mohammad Shoaib

AU - Habiballah, Ibrahim Omar

AU - Haider, Aun

PY - 2018/12/6

Y1 - 2018/12/6

N2 - Weighted Least Square (WLS) and Weighted Least Absolute Value (WLAV) estimators are most commonly employed in electric power industry. WLS fails in the presence of bad data and WLAV estimator has large computational burden. Least Measurement Rejected (LMR) is a robust estimator which can handle bad data efficiently and has lower computational burden. LMR estimator has an important tolerance parameter which is used to reject bad data during estimation process. In this paper, an iterative tuning approach for the tolerance parameter of LMR has been proposed. The accuracy and computational efficiency of the proposed approach have been compared with most commonly used WLS and WLAV estimators. The accuracy has been computed in terms of Cumulative Estimation Error (CEE) indicator for IEEE-30 and IEEE-118 bus systems.

AB - Weighted Least Square (WLS) and Weighted Least Absolute Value (WLAV) estimators are most commonly employed in electric power industry. WLS fails in the presence of bad data and WLAV estimator has large computational burden. Least Measurement Rejected (LMR) is a robust estimator which can handle bad data efficiently and has lower computational burden. LMR estimator has an important tolerance parameter which is used to reject bad data during estimation process. In this paper, an iterative tuning approach for the tolerance parameter of LMR has been proposed. The accuracy and computational efficiency of the proposed approach have been compared with most commonly used WLS and WLAV estimators. The accuracy has been computed in terms of Cumulative Estimation Error (CEE) indicator for IEEE-30 and IEEE-118 bus systems.

KW - Bad Data

KW - Least Measurement Rejected

KW - State Estimation

KW - Weighted Least Absolute Value

KW - Weighted Least Square

UR - https://www.scopus.com/pages/publications/85060550614

U2 - 10.1109/ICEE.2018.8566701

DO - 10.1109/ICEE.2018.8566701

M3 - Conference contribution

AN - SCOPUS:85060550614

T3 - 2018 International Conference on Electrical Engineering, ICEE 2018

BT - 2018 International Conference on Electrical Engineering, ICEE 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

State estimation accuracy of tuned least measurement rejected estimator

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

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Cite this