Automatic analysis of Pole Mounted Auto-Recloser data for fault diagnosis and prognosis

X. Wang; S. M. Strachan; S. D. J. McArthur; J. D. Kirkwood

doi:10.1109/ISAP.2015.7325519

Automatic analysis of Pole Mounted Auto-Recloser data for fault diagnosis and prognosis

X. Wang, S. M. Strachan, S. D. J. McArthur, J. D. Kirkwood

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

3 Citations (Scopus)

1435 Downloads (Pure)

Abstract

Fault diagnosis is a key part of a control and protection engineer’s role to ensure the effective and stable performance of electrical power networks. One challenge is to support the analysis and application of expert judgement to the, often, large data sets generated. To assist engineers with this task and improve network reliability, this research focuses on analysing previous fault activity in order to obtain an early-warning report to assist fault diagnosis and fault prognosis.

This paper details the design of an integrated system with a fault diagnosis algorithm utilising available Supervisory Control And Data Acquisition (SCADA) alarm data and 11kV distribution network data captured from Pole Mounted Auto-Reclosers (PMARs) (provided by a leading UK network operator). The developed system will be capable of diagnosing the nature of a circuit’s previous fault activity, underlying circuit activity and evolving fault activity and the risk of future fault activity. This will provide prognostic decision support for network operators and maintenance staff.

Original language	English
Title of host publication	2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015
Place of Publication	Piscataway
Publisher	IEEE
Number of pages	6
ISBN (Print)	9781509001903
DOIs	https://doi.org/10.1109/ISAP.2015.7325519
Publication status	Published - 12 Nov 2015
Event	18th Intelligent Systems Applications to Power Systems (ISAP 2015) - Porto, Portugal Duration: 11 Sept 2015 → 17 Sept 2015

Conference

Conference	18th Intelligent Systems Applications to Power Systems (ISAP 2015)
Country/Territory	Portugal
City	Porto
Period	11/09/15 → 17/09/15

Keywords

decision support
distribution automation
distribution network data
fault activity
fault diagnosis
SCADA alar data

Access to Document

10.1109/ISAP.2015.7325519

Wang-etal-ISAP-2015-Automatic-analysis-of-Pole-Mounted-Auto-Recloser-data-for-fault-diagnosis-and-prognosisAccepted author manuscript, 759 KB

Cite this

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title = "Automatic analysis of Pole Mounted Auto-Recloser data for fault diagnosis and prognosis",

abstract = "Fault diagnosis is a key part of a control and protection engineer{\textquoteright}s role to ensure the effective and stable performance of electrical power networks. One challenge is to support the analysis and application of expert judgement to the, often, large data sets generated. To assist engineers with this task and improve network reliability, this research focuses on analysing previous fault activity in order to obtain an early-warning report to assist fault diagnosis and fault prognosis.This paper details the design of an integrated system with a fault diagnosis algorithm utilising available Supervisory Control And Data Acquisition (SCADA) alarm data and 11kV distribution network data captured from Pole Mounted Auto-Reclosers (PMARs) (provided by a leading UK network operator). The developed system will be capable of diagnosing the nature of a circuit{\textquoteright}s previous fault activity, underlying circuit activity and evolving fault activity and the risk of future fault activity. This will provide prognostic decision support for network operators and maintenance staff.",

keywords = "decision support, distribution automation , distribution network data, fault activity, fault diagnosis, SCADA alar data",

author = "X. Wang and Strachan, {S. M.} and McArthur, {S. D. J.} and Kirkwood, {J. D.}",

note = "{\textcopyright} 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.; 18th Intelligent Systems Applications to Power Systems (ISAP 2015) ; Conference date: 11-09-2015 Through 17-09-2015",

year = "2015",

month = nov,

day = "12",

doi = "10.1109/ISAP.2015.7325519",

language = "English",

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booktitle = "2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015",

publisher = "IEEE",

}

Wang, X, Strachan, SM , McArthur, SDJ & Kirkwood, JD 2015, Automatic analysis of Pole Mounted Auto-Recloser data for fault diagnosis and prognosis. in 2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015. IEEE, Piscataway, 18th Intelligent Systems Applications to Power Systems (ISAP 2015) , Porto, Portugal, 11/09/15. https://doi.org/10.1109/ISAP.2015.7325519

TY - GEN

T1 - Automatic analysis of Pole Mounted Auto-Recloser data for fault diagnosis and prognosis

AU - Wang, X.

AU - Strachan, S. M.

AU - McArthur, S. D. J.

AU - Kirkwood, J. D.

N1 - © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2015/11/12

Y1 - 2015/11/12

N2 - Fault diagnosis is a key part of a control and protection engineer’s role to ensure the effective and stable performance of electrical power networks. One challenge is to support the analysis and application of expert judgement to the, often, large data sets generated. To assist engineers with this task and improve network reliability, this research focuses on analysing previous fault activity in order to obtain an early-warning report to assist fault diagnosis and fault prognosis.This paper details the design of an integrated system with a fault diagnosis algorithm utilising available Supervisory Control And Data Acquisition (SCADA) alarm data and 11kV distribution network data captured from Pole Mounted Auto-Reclosers (PMARs) (provided by a leading UK network operator). The developed system will be capable of diagnosing the nature of a circuit’s previous fault activity, underlying circuit activity and evolving fault activity and the risk of future fault activity. This will provide prognostic decision support for network operators and maintenance staff.

AB - Fault diagnosis is a key part of a control and protection engineer’s role to ensure the effective and stable performance of electrical power networks. One challenge is to support the analysis and application of expert judgement to the, often, large data sets generated. To assist engineers with this task and improve network reliability, this research focuses on analysing previous fault activity in order to obtain an early-warning report to assist fault diagnosis and fault prognosis.This paper details the design of an integrated system with a fault diagnosis algorithm utilising available Supervisory Control And Data Acquisition (SCADA) alarm data and 11kV distribution network data captured from Pole Mounted Auto-Reclosers (PMARs) (provided by a leading UK network operator). The developed system will be capable of diagnosing the nature of a circuit’s previous fault activity, underlying circuit activity and evolving fault activity and the risk of future fault activity. This will provide prognostic decision support for network operators and maintenance staff.

KW - decision support

KW - distribution automation

KW - distribution network data

KW - fault activity

KW - fault diagnosis

KW - SCADA alar data

UR - http://www.isap-power.org/

UR - http://isap2015.inesctec.eu/

U2 - 10.1109/ISAP.2015.7325519

DO - 10.1109/ISAP.2015.7325519

M3 - Conference contribution book

SN - 9781509001903

BT - 2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015

PB - IEEE

CY - Piscataway

T2 - 18th Intelligent Systems Applications to Power Systems (ISAP 2015)

Y2 - 11 September 2015 through 17 September 2015

ER -

Automatic analysis of Pole Mounted Auto-Recloser data for fault diagnosis and prognosis

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