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Approximate Analysis of Multi-State Weighted k -Out-of- n Systems Applied to Transmission Lines

Author

Listed:
  • Xiaogang Song

    (School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an 710072, China)

  • Zhengjun Zhai

    (School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an 710072, China)

  • Yangming Guo

    (School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an 710072, China)

  • Peican Zhu

    (School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an 710072, China)

  • Jie Han

    (Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada)

Abstract

Multi-state weighted k -out-of- n systems are widely applied in various scenarios, such as multiple line (power/oil transmission line) transmission systems where the capability of fault tolerance is desirable. However, the complex operating environment and the dynamic features of load demands influence the evaluation of system reliability. In this paper, a stochastic multiple-valued (SMV) approach is proposed to efficiently predict the reliability of two models of systems with non-repairable components and dynamically repairable components. The weights/performances and reliabilities of multi-state components (MSCs) are represented by stochastic sequences consisting of a fixed number of multi-state values with the positions being randomly permutated. Using stochastic sequences with L multiple values, linear computational complexities with parameters n and L are required by the SMV approach to compute the reliability of different multi-state k -out-of- n systems at a reasonable accuracy, compared to the complexities of universal generating functions (UGF) and fuzzy universal generating functions (FUGF) that increase exponentially with the value of n . The analysis of two benchmarks shows that the proposed SMV approach is more efficient than the analysis using UGF or FUGF.

Suggested Citation

  • Xiaogang Song & Zhengjun Zhai & Yangming Guo & Peican Zhu & Jie Han, 2017. "Approximate Analysis of Multi-State Weighted k -Out-of- n Systems Applied to Transmission Lines," Energies, MDPI, vol. 10(11), pages 1-16, October.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:11:p:1740-:d:116953
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    References listed on IDEAS

    as
    1. Kołowrocki, K. & Kwiatuszewska-Sarnecka, B., 2008. "Reliability and risk analysis of large systems with ageing components," Reliability Engineering and System Safety, Elsevier, vol. 93(12), pages 1821-1829.
    2. Zhigang Tian & Ming Zuo & Richard Yam, 2009. "Multi-state systems and their performance evaluation," IISE Transactions, Taylor & Francis Journals, vol. 41(1), pages 32-44.
    3. Eryilmaz, Serkan, 2013. "On reliability analysis of a k-out-of-n system with components having random weights," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 41-44.
    4. S K Chaturvedi & S H Basha & S V Amari & M J Zuo, 2012. "Reliability analysis of generalized multi-state k-out-of-n systems," Journal of Risk and Reliability, , vol. 226(3), pages 327-336, June.
    5. Serkan Eryilmaz & Kadir Sarikaya, 2014. "Modeling and analysis of weighted-k-out-of-n: G system consisting of two different types of components," Journal of Risk and Reliability, , vol. 228(3), pages 265-271, June.
    6. Ziqi Wang & Jinghan He & Alexandru Nechifor & Dahai Zhang & Peter Crossley, 2017. "Identification of Critical Transmission Lines in Complex Power Networks," Energies, MDPI, vol. 10(9), pages 1-19, August.
    7. Li, Wei & Zuo, Ming J., 2008. "Reliability evaluation of multi-state weighted k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 93(1), pages 160-167.
    8. Hadi Akbarzade Khorshidi & Indra Gunawan & M. Yousef Ibrahim, 2015. "On Reliability Evaluation of Multistate Weighted -out-of- System Using Present Value," The Engineering Economist, Taylor & Francis Journals, vol. 60(1), pages 22-39, January.
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