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Wind-induced failure analysis of a transmission tower-line system with long-term measured data and orientation effect

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  • Bi, Wenzhe
  • Tian, Li
  • Li, Chao
  • Ma, Zhen
  • Pan, Haiyang

Abstract

This paper proposes a comprehensive wind-induced performance evaluation framework for transmission tower-line systems (TTLSs) from both structural safety and normal operation dimensions, incorporating the joint effect of wind speed and direction, as well as the line orientation. Based on the field wind data recorded in Weifang, China during 1971–2020, the actual failure probability of a local TTLS is calculated considering the joint probability distribution (JPD) of wind speed and direction, and the optimal layout of the transmission line is provided. The results show that the developed QS copula model can not only account for the continuity and cyclicity of wind direction but also have a fine goodness-of-fit. The wind direction with a relatively lower occurrence probability does not necessarily yield smaller failure probability of the TTLS, thereby the JPD of wind speed and direction should be incorporated to achieve reliable performance assessment. For the failure analysis with respect to structural damage, the most favorable layout of the exemplar TTLS is the orientation of 265°; while the most advantageous layout is the orientation of 38° in terms of flashover risk. The presented framework is conducive to performance assessment and optimization design of TTLSs subjected to wind hazards.

Suggested Citation

  • Bi, Wenzhe & Tian, Li & Li, Chao & Ma, Zhen & Pan, Haiyang, 2023. "Wind-induced failure analysis of a transmission tower-line system with long-term measured data and orientation effect," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    • Handle: RePEc:eee:reensy:v:229:y:2023:i:c:s0951832022004926
    DOI: 10.1016/j.ress.2022.108875
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    References listed on IDEAS

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    1. Cadini, F. & Zio, E. & Petrescu, C.A., 2010. "Optimal expansion of an existing electrical power transmission network by multi-objective genetic algorithms," Reliability Engineering and System Safety, Elsevier, vol. 95(3), pages 173-181.
    2. Stuart G. Coles & David Walshaw, 1994. "Directional Modelling of Extreme Wind Speeds," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 43(1), pages 139-157, March.
    3. Lu, Qin & Zhang, Wei, 2022. "Integrating dynamic Bayesian network and physics-based modeling for risk analysis of a time-dependent power distribution system during hurricanes," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    4. Salman, Abdullahi M. & Li, Yue & Stewart, Mark G., 2015. "Evaluating system reliability and targeted hardening strategies of power distribution systems subjected to hurricanes," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 319-333.
    5. Xue, Jiayue & Mohammadi, Farshad & Li, Xin & Sahraei-Ardakani, Mostafa & Ou, Ge & Pu, Zhaoxia, 2020. "Impact of transmission tower-line interaction to the bulk power system during hurricane," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    6. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
    7. Winkler, James & Dueñas-Osorio, Leonardo & Stein, Robert & Subramanian, Devika, 2010. "Performance assessment of topologically diverse power systems subjected to hurricane events," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 323-336.
    8. Scherb, Anke & Garrè, Luca & Straub, Daniel, 2019. "Evaluating component importance and reliability of power transmission networks subject to windstorms: methodology and application to the nordic grid," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    9. Ma, Liyang & Christou, Vasileios & Bocchini, Paolo, 2022. "Framework for probabilistic simulation of power transmission network performance under hurricanes," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
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    Cited by:

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