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Reliability-Centered Asset Management Using Component Reliability Importance
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.ORCID iD: 0000-0002-2964-7233
2016 (English)In: 2016 INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS), IEEE, 2016Conference paper (Refereed)
Abstract [en]

Asset management is an important topic in all fields especially in power system which has very high investment costs and very expensive elements. Reliability Centered Asset Management (RCAM) is an effective technique to perform the power system asset management with quantitative methods such that, on the one hand, the total cost is minimized and, on the other hand, the reliability of the system is maximized Nevertheless, the need for an appropriate optimization-based algorithm for RCAM implementation in power system is still sensed. This paper proposes an algorithm to fulfil such needs including the following steps. First, the component reliability importance index is calculated for all components of the system. Then, a set of all potential maintenance strategies of each component are defined and together with the component reliability importance indices are used as inputs in the third step. In the third step, an optimization problem is proposed to select the optimum maintenance strategy for each component in the system. The proposed three-step algorithm is tested on a Swedish distribution system. The results highlight the advantages of the proposed method for well-organizing the maintenance strategies for all components of the system.

Place, publisher, year, edition, pages
IEEE, 2016.
Keyword [en]
Asset management, component reliability importance, maintenance optimization, power system maintenance, power system reliability
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-202490DOI: 10.1109/PMAPS.2016.7764173ISI: 000392327900125ISBN: 978-1-5090-1970-0 OAI: oai:DiVA.org:kth-202490DiVA: diva2:1078040
Conference
International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), OCT 16-20, 2016, Beijing, PEOPLES R CHINA
Note

QC 20170302

Available from: 2017-03-02 Created: 2017-03-02 Last updated: 2017-03-02Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
  • html
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  • asciidoc
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