Data Analytics for Grid Resilience with Early Failures and Wear-out Failures

Robert Ross; Peter A.C. Ypma; Gerben Koopmans

doi:10.1109/SoutheastCon48659.2022.9764082

Data Analytics for Grid Resilience with Early Failures and Wear-out Failures

Robert Ross, Peter A.C. Ypma, Gerben Koopmans

DC systems, Energy conversion & Storage

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

2 Downloads (Pure)

Abstract

The here reported work is part of a project on supporting grid resilience by asset management techniques. The present work focuses on support of decision-making after a few failures occurred that may be the start of many more. Methods are reviewed and new algorithms developed where the present IEEE/IEC standard does not provide. Two cases of early failures and wear-out are analyzed as examples for the data analytics.

Original language	English
Title of host publication	SoutheastCon 2022
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	575-582
Number of pages	8
ISBN (Electronic)	978-1-6654-0652-9
DOIs	https://doi.org/10.1109/SoutheastCon48659.2022.9764082
Publication status	Published - 2022
Event	SoutheastCon 2022 - Mobile, United States Duration: 26 Mar 2022 → 3 Apr 2022

Publication series

Name	Conference Proceedings - IEEE SOUTHEASTCON
Volume	2022-March
ISSN (Print)	0734-7502

Conference

Conference	SoutheastCon 2022
Country/Territory	United States
City	Mobile
Period	26/03/22 → 3/04/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

bathtub curve
censored data
early failures
failure time prediction
hazard rate
performance ratio
redundancy
similarity index
Weibull
weighted linear regression

Access to Document

10.1109/SoutheastCon48659.2022.9764082

Data_Analytics_for_Grid_Resilience_with_Early_Failures_and_Wear-out_FailuresFinal published version, 1.5 MB

Cite this

@inproceedings{e93d9590862146388e0d355b015ca124,

title = "Data Analytics for Grid Resilience with Early Failures and Wear-out Failures",

abstract = "The here reported work is part of a project on supporting grid resilience by asset management techniques. The present work focuses on support of decision-making after a few failures occurred that may be the start of many more. Methods are reviewed and new algorithms developed where the present IEEE/IEC standard does not provide. Two cases of early failures and wear-out are analyzed as examples for the data analytics. ",

keywords = "bathtub curve, censored data, early failures, failure time prediction, hazard rate, performance ratio, redundancy, similarity index, Weibull, weighted linear regression",

author = "Robert Ross and Ypma, {Peter A.C.} and Gerben Koopmans",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; SoutheastCon 2022 ; Conference date: 26-03-2022 Through 03-04-2022",

year = "2022",

doi = "10.1109/SoutheastCon48659.2022.9764082",

language = "English",

series = "Conference Proceedings - IEEE SOUTHEASTCON",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

pages = "575--582",

booktitle = "SoutheastCon 2022",

address = "United States",

}

Ross, R , Ypma, PAC & Koopmans, G 2022, Data Analytics for Grid Resilience with Early Failures and Wear-out Failures. in SoutheastCon 2022. Conference Proceedings - IEEE SOUTHEASTCON, vol. 2022-March, Institute of Electrical and Electronics Engineers (IEEE), pp. 575-582, SoutheastCon 2022, Mobile, United States, 26/03/22. https://doi.org/10.1109/SoutheastCon48659.2022.9764082

Data Analytics for Grid Resilience with Early Failures and Wear-out Failures. / Ross, Robert ; Ypma, Peter A.C.; Koopmans, Gerben.

SoutheastCon 2022. Institute of Electrical and Electronics Engineers (IEEE), 2022. p. 575-582 (Conference Proceedings - IEEE SOUTHEASTCON; Vol. 2022-March).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Data Analytics for Grid Resilience with Early Failures and Wear-out Failures

AU - Ross, Robert

AU - Ypma, Peter A.C.

AU - Koopmans, Gerben

N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2022

Y1 - 2022

N2 - The here reported work is part of a project on supporting grid resilience by asset management techniques. The present work focuses on support of decision-making after a few failures occurred that may be the start of many more. Methods are reviewed and new algorithms developed where the present IEEE/IEC standard does not provide. Two cases of early failures and wear-out are analyzed as examples for the data analytics.

AB - The here reported work is part of a project on supporting grid resilience by asset management techniques. The present work focuses on support of decision-making after a few failures occurred that may be the start of many more. Methods are reviewed and new algorithms developed where the present IEEE/IEC standard does not provide. Two cases of early failures and wear-out are analyzed as examples for the data analytics.

KW - bathtub curve

KW - censored data

KW - early failures

KW - failure time prediction

KW - hazard rate

KW - performance ratio

KW - redundancy

KW - similarity index

KW - Weibull

KW - weighted linear regression

UR - http://www.scopus.com/inward/record.url?scp=85129896785&partnerID=8YFLogxK

U2 - 10.1109/SoutheastCon48659.2022.9764082

DO - 10.1109/SoutheastCon48659.2022.9764082

M3 - Conference contribution

AN - SCOPUS:85129896785

T3 - Conference Proceedings - IEEE SOUTHEASTCON

SP - 575

EP - 582

BT - SoutheastCon 2022

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - SoutheastCon 2022

Y2 - 26 March 2022 through 3 April 2022

ER -

Data Analytics for Grid Resilience with Early Failures and Wear-out Failures

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this