IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v157y2017icp13-22.html
   My bibliography  Save this article

Modeling reliability of power systems substations by using stochastic automata networks

Author

Listed:
  • Å nipas, Mindaugas
  • Radziukynas, Virginijus
  • ValakeviÄ ius, Eimutis

Abstract

In this paper, stochastic automata networks (SANs) formalism to model reliability of power systems substations is applied. The proposed strategy allows reducing the size of state space of Markov chain model and simplifying system specification. Two case studies of standard configurations of substations are considered in detail. SAN models with different assumptions were created. SAN approach is compared with exact reliability calculation by using a minimal path set method. Modeling results showed that total independence of automata can be assumed for relatively small power systems substations with reliable equipment. In this case, the implementation of Markov chain model by a using SAN method is a relatively easy task.

Suggested Citation

  • Å nipas, Mindaugas & Radziukynas, Virginijus & ValakeviÄ ius, Eimutis, 2017. "Modeling reliability of power systems substations by using stochastic automata networks," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 13-22.
    • Handle: RePEc:eee:reensy:v:157:y:2017:i:c:p:13-22
    DOI: 10.1016/j.ress.2016.08.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832016303659
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2016.08.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Huang, Chin-Yu & Chang, Yung-Ruei, 2007. "An improved decomposition scheme for assessing the reliability of embedded systems by using dynamic fault trees," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1403-1412.
    2. Stewart, William J. & Atif, Karim & Plateau, Brigette, 1995. "The numerical solution of stochastic automata networks," European Journal of Operational Research, Elsevier, vol. 86(3), pages 503-525, November.
    3. Guo, Haitao & Yang, Xianhui, 2008. "Automatic creation of Markov models for reliability assessment of safety instrumented systems," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 829-837.
    4. Son, Kwang Seop & Kim, Dong Hoon & Kim, Chang Hwoi & Kang, Hyun Gook, 2016. "Study on the systematic approach of Markov modeling for dependability analysis of complex fault-tolerant features with voting logics," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 44-57.
    5. Sbeity, I. & Brenner, L. & Plateau, B. & Stewart, W.J., 2008. "Phase-type distributions in stochastic automata networks," European Journal of Operational Research, Elsevier, vol. 186(3), pages 1008-1028, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ariannik, Mohamadreza & Razi-Kazemi, Ali A. & Lehtonen, Matti, 2020. "An approach on lifetime estimation of distribution transformers based on degree of polymerization," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    2. Å nipas, Mindaugas & Radziukynas, Virginijus & ValakeviÄ ius, Eimutis, 2018. "Numerical solution of reliability models described by stochastic automata networks," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 570-578.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Å nipas, Mindaugas & Radziukynas, Virginijus & ValakeviÄ ius, Eimutis, 2018. "Numerical solution of reliability models described by stochastic automata networks," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 570-578.
    2. Oliveira, Fernando S., 2010. "Limitations of learning in automata-based systems," European Journal of Operational Research, Elsevier, vol. 203(3), pages 684-691, June.
    3. Liang, Qingzhu & Yang, Yinghao & Zhang, Hang & Peng, Changhong & Lu, Jianchao, 2022. "Analysis of simplification in Markov state-based models for reliability assessment of complex safety systems," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    4. Lijie, Chen & Tao, Tang & Xianqiong, Zhao & Schnieder, Eckehard, 2012. "Verification of the safety communication protocol in train control system using colored Petri net," Reliability Engineering and System Safety, Elsevier, vol. 100(C), pages 8-18.
    5. Yan-Feng Li & Jinhua Mi & Yu Liu & Yuan-Jian Yang & Hong-Zhong Huang, 2015. "Dynamic fault tree analysis based on continuous-time Bayesian networks under fuzzy numbers," Journal of Risk and Reliability, , vol. 229(6), pages 530-541, December.
    6. Zhang, Cai Wen & Zhang, Tieling & Chen, Nan & Jin, Tongdan, 2013. "Reliability modeling and analysis for a novel design of modular converter system of wind turbines," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 86-94.
    7. Lindhe, Andreas & Norberg, Tommy & Rosén, Lars, 2012. "Approximate dynamic fault tree calculations for modelling water supply risks," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 61-71.
    8. Jon T Selvik & Eirik B Abrahamsen, 2017. "On the meaning of accuracy and precision in a risk analysis context," Journal of Risk and Reliability, , vol. 231(2), pages 91-100, April.
    9. Uysal, Ertugrul & Dayar, Tugrul, 1998. "Iterative methods based on splittings for stochastic automata networks," European Journal of Operational Research, Elsevier, vol. 110(1), pages 166-186, October.
    10. Gascard, Eric & Simeu-Abazi, Zineb, 2018. "Quantitative Analysis of Dynamic Fault Trees by means of Monte Carlo Simulations: Event-Driven Simulation Approach," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 487-504.
    11. Durga Rao, K. & Gopika, V. & Sanyasi Rao, V.V.S. & Kushwaha, H.S. & Verma, A.K. & Srividya, A., 2009. "Dynamic fault tree analysis using Monte Carlo simulation in probabilistic safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 94(4), pages 872-883.
    12. Cui, Lin & Shu, Yidan & Wang, Zhaohui & Zhao, Jinsong & Qiu, Tong & Sun, Wenyong & Wei, Zhenqiang, 2012. "HASILT: An intelligent software platform for HAZOP, LOPA, SRS and SIL verification," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 56-64.
    13. Peter Buchholz & Gianfranco Ciardo & Susanna Donatelli & Peter Kemper, 2000. "Complexity of Memory-Efficient Kronecker Operations with Applications to the Solution of Markov Models," INFORMS Journal on Computing, INFORMS, vol. 12(3), pages 203-222, August.
    14. Sejin Baek & Gyunyoung Heo, 2021. "Application of Dynamic Fault Tree Analysis to Prioritize Electric Power Systems in Nuclear Power Plants," Energies, MDPI, vol. 14(14), pages 1-17, July.
    15. Azizpour, Hooshyar & Lundteigen, Mary Ann, 2019. "Analysis of simplification in Markov-based models for performance assessment of Safety Instrumented System," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 252-260.
    16. Cai, Baoping & Li, Wenchao & Liu, Yiliu & Shao, Xiaoyan & Zhang, Yanping & Zhao, Yi & Liu, Zengkai & Ji, Renjie & Liu, Yonghong, 2021. "Modeling for evaluation of safety instrumented systems with heterogeneous components," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    17. Mohammad Nadjafi & Mohammad Ali Farsi & Hossein Jabbari, 2017. "Reliability analysis of multi-state emergency detection system using simulation approach based on fuzzy failure rate," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(3), pages 532-541, September.
    18. Peter Buchholz & Miklós Telek, 2013. "Rational Automata Networks: A Non-Markovian Modeling Approach," INFORMS Journal on Computing, INFORMS, vol. 25(1), pages 87-101, February.
    19. Tyrväinen, T., 2013. "Risk importance measures in the dynamic flowgraph methodology," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 35-50.
    20. Cai, Baoping & Liu, Yu & Fan, Qian, 2016. "A multiphase dynamic Bayesian networks methodology for the determination of safety integrity levels," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 105-115.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:157:y:2017:i:c:p:13-22. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.