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Failure Rate Trends in an Aging Population - Monte Carlo Approach
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering. (RCAM)ORCID iD: 0000-0003-1254-1843
(RCAM)ORCID iD: 0000-0003-4021-839X
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.ORCID iD: 0000-0002-2964-7233
2015 (English)In: 23rd International Conference on Electricity Distribution - CIRED 2015, CIRED - Congrès International des Réseaux Electriques de Distribution, 2015Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes a method to make future failure predictions from input data on population age distribution and failure rates, using a Monte Carlo approach. In contrast to many methods used today, the method in this paper is designed to address multiple properties and assumptions simultaneously, which makes the task complicated. For example, the component population is allowed to be divided into both age and different types. The time-dependent failure rates are defined separately for each individual type, can consist of a combination of multiple different failure rates for separate modes, and can be of practically any shape. Furthermore, a volatility measure for the failure rates is introduced and used to model the uncertainties in failure rate estimates. The method handles investment and reinvestment scenarios as well as different restoration models, such as replacing a failed component with a new component of a different type. As a part of the project, a stand-alone software tool was developed and presented in the paper. In the included case study, the method and the tool are shown to be useful when investigating reinvestment strategies to renew the population and decrease the expected number of future failures. The paper gives the reader useful information and understanding on how the problem of predicting the reliability of the future power system can be addressed and solved.

Place, publisher, year, edition, pages
CIRED - Congrès International des Réseaux Electriques de Distribution, 2015.
Keyword [en]
Reliability, Failure Rate, Monte Carlo, Aging Components, Power System
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-171215OAI: oai:DiVA.org:kth-171215DiVA: diva2:842766
Conference
23rd International Conference on Electricity Distribution - CIRED 15-18 June 2015, Lyon, France
Funder
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage
Note

QC 20150812

Available from: 2015-07-22 Created: 2015-07-22 Last updated: 2015-08-12Bibliographically approved

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fulltext(498 kB)139 downloads
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Ekstedt, NiklasBabu, Sajeesh

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CiteExportLink to record
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