A LEAST SQUARE REGRESSION BASED FAULT LOCATOR FOR UNBALANCED FAULTS ON A TRANSMISSION LINE

Shuo Zhang; Emma Robinson; Malabika Basu

doi:10.1049/icp.2022.0980

A LEAST SQUARE REGRESSION BASED FAULT LOCATOR FOR UNBALANCED FAULTS ON A TRANSMISSION LINE

Shuo Zhang, Emma Robinson, Malabika Basu

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

Abstract

Associated with the sequence analysis of voltage measurement at one end of a transmission line, least square regression (LSR) is applied to determine the fault locations of this line under unbalanced faults in a non-radial wind power integrated electrical grid. Under this approach, the data-driven models illustrating fault characteristics are built in MATLAB/Simulink, so the fault locations can be accurately estimated for the facilitation of relevant protection schemes in real time. The effectiveness of LSR estimating fault locations is validated through a stochastic Monte Carlo simulation (MCS) with the involvement of noise.

Original language	English
Title of host publication	IET Conference Proceedings
Publisher	Institution of Engineering and Technology
Pages	444-449
Number of pages	6
Volume	2022
Edition	2
ISBN (Electronic)	9781839537042, 9781839537059, 9781839537196
DOIs	https://doi.org/10.1049/icp.2022.0980
Publication status	Published - 2022
Event	16th International Conference on Developments in Power System Protection, DPSP 2022 - Newcastle, Virtual, United Kingdom Duration: 7 Mar 2022 → 10 Mar 2022

Conference

Conference	16th International Conference on Developments in Power System Protection, DPSP 2022
Country/Territory	United Kingdom
City	Newcastle, Virtual
Period	7/03/22 → 10/03/22

Keywords

LEAST SQUARE REGRESSION
MONTE CARLO SIMULATION
SEQUENCE ANALYSIS

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10.1049/icp.2022.0980Licence: Unspecified

Cite this

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title = "A LEAST SQUARE REGRESSION BASED FAULT LOCATOR FOR UNBALANCED FAULTS ON A TRANSMISSION LINE",

abstract = "Associated with the sequence analysis of voltage measurement at one end of a transmission line, least square regression (LSR) is applied to determine the fault locations of this line under unbalanced faults in a non-radial wind power integrated electrical grid. Under this approach, the data-driven models illustrating fault characteristics are built in MATLAB/Simulink, so the fault locations can be accurately estimated for the facilitation of relevant protection schemes in real time. The effectiveness of LSR estimating fault locations is validated through a stochastic Monte Carlo simulation (MCS) with the involvement of noise.",

keywords = "LEAST SQUARE REGRESSION, MONTE CARLO SIMULATION, SEQUENCE ANALYSIS",

author = "Shuo Zhang and Emma Robinson and Malabika Basu",

note = "Publisher Copyright: {\textcopyright} 2022 IET Conference Proceedings. All rights reserved.; 16th International Conference on Developments in Power System Protection, DPSP 2022 ; Conference date: 07-03-2022 Through 10-03-2022",

year = "2022",

doi = "10.1049/icp.2022.0980",

language = "English",

volume = "2022",

pages = "444--449",

booktitle = "IET Conference Proceedings",

publisher = "Institution of Engineering and Technology",

address = "United Kingdom",

edition = "2",

}

Zhang, S, Robinson, E & Basu, M 2022, A LEAST SQUARE REGRESSION BASED FAULT LOCATOR FOR UNBALANCED FAULTS ON A TRANSMISSION LINE. in IET Conference Proceedings. 2 edn, vol. 2022, Institution of Engineering and Technology, pp. 444-449, 16th International Conference on Developments in Power System Protection, DPSP 2022, Newcastle, Virtual, United Kingdom, 7/03/22. https://doi.org/10.1049/icp.2022.0980

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AU - Zhang, Shuo

AU - Robinson, Emma

AU - Basu, Malabika

PY - 2022

Y1 - 2022

N2 - Associated with the sequence analysis of voltage measurement at one end of a transmission line, least square regression (LSR) is applied to determine the fault locations of this line under unbalanced faults in a non-radial wind power integrated electrical grid. Under this approach, the data-driven models illustrating fault characteristics are built in MATLAB/Simulink, so the fault locations can be accurately estimated for the facilitation of relevant protection schemes in real time. The effectiveness of LSR estimating fault locations is validated through a stochastic Monte Carlo simulation (MCS) with the involvement of noise.

AB - Associated with the sequence analysis of voltage measurement at one end of a transmission line, least square regression (LSR) is applied to determine the fault locations of this line under unbalanced faults in a non-radial wind power integrated electrical grid. Under this approach, the data-driven models illustrating fault characteristics are built in MATLAB/Simulink, so the fault locations can be accurately estimated for the facilitation of relevant protection schemes in real time. The effectiveness of LSR estimating fault locations is validated through a stochastic Monte Carlo simulation (MCS) with the involvement of noise.

KW - LEAST SQUARE REGRESSION

KW - MONTE CARLO SIMULATION

KW - SEQUENCE ANALYSIS

UR - https://www.scopus.com/pages/publications/85174652249

U2 - 10.1049/icp.2022.0980

DO - 10.1049/icp.2022.0980

M3 - Conference contribution

AN - SCOPUS:85174652249

VL - 2022

SP - 444

EP - 449

BT - IET Conference Proceedings

PB - Institution of Engineering and Technology

T2 - 16th International Conference on Developments in Power System Protection, DPSP 2022

Y2 - 7 March 2022 through 10 March 2022

ER -

A LEAST SQUARE REGRESSION BASED FAULT LOCATOR FOR UNBALANCED FAULTS ON A TRANSMISSION LINE

Abstract

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Keywords

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