LR warns of wind turbine fatigue risks
The report found that some offshore wind turbine support structures may fall short of required fatigue life expectations (Source: Lloyd’s Register)
Research by classification society Lloyd’s Register (LR) has revealed that some offshore wind turbine support structures may not meet fatigue life design expectations. The investigation demonstrated that reliability-based inspections can help manage component fatigue risks.
The classification society assessed a North Atlantic wind farm with 60-70 turbines and a capacity of most than 500 MW. Turbines are typically designed for a service life of 25 years and a fatigue design factor of three, resulting in a minimum required fatigue life of 75 years. However, the LR study revealed that a critical joint in the jacket foundation would reach the end of its fatigue life at 52 years of operation.
LR used a S-N model – stress versus number of cycles – to estimate when structural safety might drop below acceptable thresholds. The classification society also used fracture mechanics crack growth analysis to predict the probability of failure over time and therefore the required frequency for inspections. This analysis generates Probability of Detection curves to enable inspection schedules to be dynamically updated.
The results indicated that the first inspection should take place around year nine. After that, further inspections could be required every year to maintain acceptable safety margins.
The study revealed the limitations of current inspection methods, LR said. Visual and ultrasonic inspections were found to be less effective for fatigue-critical components. Other techniques such as Eddy Current or Alternating Current Field Measurement were found to be more reliable thereby enabling longer inspection intervals, but only when operators were prepared to accept slightly lower safety thresholds, LR said.
LR’s global head of technology – Offshore and Subsea, Kourosh Parsa, commented: “Many offshore wind assets are designed to a standard fatigue factor, but real-world conditions often expose critical vulnerabilities. Our findings show that using reliability-based methods allows operators to focus inspections where the risks are greatest. By integrating sophisticated models and real-world inspection data, we can extend asset life, reduce costs and, most importantly, maintain safety.”
