Ultra-high voltage (UHV) long-span (LS) transmission lines, characterized by large tower heights and long spans, are highly susceptible to wind loads. Wind fragility analysis is an essential method to assess their reliability under wind-induced actions. Using an UHV-LS transmission tower in Anhui Province as a case study, this research applies random wind vibration response theory and China’s current overhead transmission line loading specifications to determine the structural response distribution under wind loads. The analysis incorporates uncertainties in structural material properties to establish the probabilistic distribution of wind load-carrying capacity. Performance levels are quantitatively evaluated using tower-top displacement and corrected inter-segment displacement angles as indicators, leading to the development of wind fragility curves. The results indicate that the quasi-static wind effect distribution of the transmission tower-line system can be obtained using probability-based methods for the first time. The fragility assessment shows that performance levels based on tower-top displacement are more conservative than those based on modified inter-segment displacement angles. Additionally, as structural damage intensifies, the influence of material uncertainty on load-bearing capacity becomes more pronounced. Overall, wind fragility analysis shows that UHV towers exhibit good wind reliability under design wind loads, although their wind-induced failure shows brittle characteristics.

Conventional reliability assessments of transmission towers using standard calculation formulas usually neglect corrosion-induced performance degradation, and the recommended range of wind load effect ratios is typically subjective. To address these limitations, this study focuses on service towers and proposes a timedependent reliability analysis method under wind load within the framework of the standard formula. First, a resistance degradation model considering corrosion effects is developed by integrating environmental conditions and material type into the corrosion rate. Second, the wind load effect ratio is used as a random variable and its statistical characteristics are obtained by distribution fitting using real tower monitoring data. Third, the equivalent normalization (JC) method is used to calculate the reliability index of the service tower based on the standard formula. Finally, the sensitivity of the reliability index to key parameters in the standard formula is quantitatively evaluated. Results show that the wind load effect ratio approximately obeys a generalized extreme value distribution and exhibits strong correlation with tower reliability. Moreover, member initial thickness, atmospheric corrosivity and wind load adjustment coefficients all significantly influence reliability evolution. Specifically, higher atmospheric corrosivity accelerates reliability degradation, while the influence of corrosion decreases as member initial thickness increases. Additionally, a higher wind load adjustment coefficient corresponds to a higher reliability index.