Typhoon Damage Assessment of Power Transportation Networks using Bias-corrected Typhoon Wind Field with Dense Wind Measurements
Abstract
Effective preparedness and prompt restoration efforts are crucial to minimize losses in typhoon-prone areas. Achieving this necessitates reliable estimates of structural damage before typhoons make landfall. This paper develops a damage assessment framework for estimating structural damage in power transportation networks. Within this framework, a typhoon wind field model, a reliability-based fragility model, and a procedure to estimate the damaged number of towers or poles are integrated. A key feature of the framework is a proposed scale factor to correct the inherent bias in the wind field model, with its stochastic nature characterized by probabilistic models based on dense typhoon wind observations. The proposed scale factor is then incorporated into the fragility model to address the variability of the fragility model. The developed framework is applied to assess the damage to concrete poles in the 10 kV distribution networks of Zhanjiang, Guangdong Province, China during three typhoon events. For these events, the predicted number of failed poles has a relative mean error of less than 20% compared to actual values, highlighting the effectiveness of the scale factor in improving wind field model accuracy. The variability in the predicted number of failures is also quantified.
Recommended Citation
Y. Tang et al., "Typhoon Damage Assessment of Power Transportation Networks using Bias-corrected Typhoon Wind Field with Dense Wind Measurements," Journal of Wind Engineering and Industrial Aerodynamics, vol. 256, article no. 105959, Elsevier, Jan 2025.
The definitive version is available at https://doi.org/10.1016/j.jweia.2024.105959
Department(s)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Damage assessment; Fragility analysis; Power transportation network; Typhoon wind hazard
International Standard Serial Number (ISSN)
0167-6105
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Elsevier, All rights reserved.
Publication Date
01 Jan 2025
Comments
National Key Research and Development Program of China, Grant 2023YFC3008503