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Application of fault tree analysis for customer reliability assessment of a distribution power system

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  • Abdul Rahman, Fariz
  • Varuttamaseni, Athi
  • Kintner-Meyer, Michael
  • Lee, John C.

Abstract

A new method is developed for predicting customer reliability of a distribution power system using the fault tree approach with customer weighted values of component failure frequencies and downtimes. Conventional customer reliability prediction of the electric grid employs the system average (SA) component failure frequency and downtime that are weighted by only the quantity of the components in the system. These SA parameters are then used to calculate the reliability and availability of components in the system, and eventually to find the effect on customer reliability. Although this approach is intuitive, information is lost regarding customer disturbance experiences when customer information is not utilized in the SA parameter calculations, contributing to inaccuracies when predicting customer reliability indices in our study. Hence our new approach directly incorporates customer disturbance information in component failure frequency and downtime calculations by weighting these parameters with information of customer interruptions. This customer weighted (CW) approach significantly improves the prediction of customer reliability indices when applied to our reliability model with fault tree and two-state Markov chain formulations. Our method has been successfully applied to an actual distribution power system that serves over 2.1 million customers. Our results show an improved benchmarking performance on the system average interruption frequency index (SAIFI) by 26% between the SA-based and CW-based reliability calculations.

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  • Abdul Rahman, Fariz & Varuttamaseni, Athi & Kintner-Meyer, Michael & Lee, John C., 2013. "Application of fault tree analysis for customer reliability assessment of a distribution power system," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 76-85.
    • Handle: RePEc:eee:reensy:v:111:y:2013:i:c:p:76-85
    DOI: 10.1016/j.ress.2012.10.011
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    1. Haarla, Liisa & Pulkkinen, Urho & Koskinen, Mikko & Jyrinsalo, Jussi, 2008. "A method for analysing the reliability of a transmission grid," Reliability Engineering and System Safety, Elsevier, vol. 93(2), pages 277-287.
    2. Volkanovski, Andrija & ÄŒepin, Marko & Mavko, Borut, 2009. "Application of the fault tree analysis for assessment of power system reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1116-1127.
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    2. Nguyen, T.P. Khanh & Beugin, Julie & Marais, Juliette, 2015. "Method for evaluating an extended Fault Tree to analyse the dependability of complex systems: Application to a satellite-based railway system," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 300-313.
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    6. Nguyen, Hai Tra & Safder, Usman & Nhu Nguyen, X.Q. & Yoo, ChangKyoo, 2020. "Multi-objective decision-making and optimal sizing of a hybrid renewable energy system to meet the dynamic energy demands of a wastewater treatment plant," Energy, Elsevier, vol. 191(C).
    7. Santosh B. Rane & Prathamesh R. Potdar & Suraj Rane, 2019. "Accelerated life testing for reliability improvement: a case study on Moulded Case Circuit Breaker (MCCB) mechanism," 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. 10(6), pages 1668-1690, December.
    8. Cheng, Shikun & Li, Zifu & Mang, Heinz-Peter & Neupane, Kalidas & Wauthelet, Marc & Huba, Elisabeth-Maria, 2014. "Application of fault tree approach for technical assessment of small-sized biogas systems in Nepal," Applied Energy, Elsevier, vol. 113(C), pages 1372-1381.
    9. Hamid Mirshekali & Athila Q. Santos & Hamid Reza Shaker, 2023. "A Survey of Time-Series Prediction for Digitally Enabled Maintenance of Electrical Grids," Energies, MDPI, vol. 16(17), pages 1-29, August.
    10. Mohandes, Baraa & Hammadi, Reem Al & Sanusi, Wasiu & Mezher, Toufic & Khatib, Sameh El, 2018. "Advancing cyber–physical sustainability through integrated analysis of smart power systems: A case study on electric vehicles," International Journal of Critical Infrastructure Protection, Elsevier, vol. 23(C), pages 33-48.
    11. Zheng, Junjun & Okamura, Hiroyuki & Pang, Taoming & Dohi, Tadashi, 2021. "Availability importance measures of components in smart electric power grid systems," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    12. Magoua, Joseph Jonathan & Li, Nan, 2023. "The human factor in the disaster resilience modeling of critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    13. Akgün, İbrahim & Gümüşbuğa, Ferhat & Tansel, Barbaros, 2015. "Risk based facility location by using fault tree analysis in disaster management," Omega, Elsevier, vol. 52(C), pages 168-179.
    14. Zhang, Jintao & Bagtzoglou, Yiannis & Zhu, Jin & Li, Baikun & Zhang, Wei, 2023. "Fragility-based system performance assessment of critical power infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
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