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A new multiattribute decision making support tool for identifying critical components in power transmission systems

Gharakheili, M. A ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1109/JSYST.2015.2500262
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2018
  4. Abstract:
  5. The present context of the electric industry, characterized by competitive markets, privatization, and regulatory of technical requirements forces the power utilities to optimize their asset management practices and develop the requisite decision plans techno-economically. Practically approaching, this paper devises a new support tool based on a multiattribute decision making (MADM) framework in combination with analytical hierarchical process (AHP) to determine the most critical components of power transmission systems. Measure of system-wide reliability performance, outage cost, marginal clearing prices demonstrative of market fairness, and network losses are among the attributes considered in this paper for component criticality assessment. With the frequent existence of qualitative and quantitative attributes, the proposed approach can effectively help to deal with the existent uncertainty and conventional judgment vagueness. As verified in a case study on the IEEE Reliability Test System (IEEE-RTS), the proposed framework introduces its applicability and efficiency for the practical asset management optimizations in electric utilities. © 2007-2012 IEEE
  6. Keywords:
  7. Analytical hierarchical process (AHP) ; Reliability-centered maintenance (RCM) ; Transmission system ; Asset management ; Commerce ; Electric industry ; Electric power transmission ; Electric power transmission networks ; Electric utilities ; Hierarchical systems ; Power transmission ; Privatization ; Reliability ; Transmissions ; Analytical hierarchical process ; Critical component ; IEEE-reliability test system ; Multi attribute decision making ; Power transmission systems ; Reliability centered maintenance ; Reliability performance ; Transmission systems ; Decision making
  8. Source: IEEE Systems Journal ; Volume 12, Issue 1 , 2018 , Pages 316-327 ; 19328184 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/7368085