Assessing the impact of wind profiles at offshore wind farm sites for field data-enabled design

Abstract. As wind turbines grow and wind farms become denser, more insight into real metocean conditions is essential for operational efficiency and load assessment. Light Detection And Ranging LiDAR) technology, which can substitute the use of meteorological masts, has garnered significant attention in the literature. However, it indirectly measures wind parameters, relying on assumptions and built-in algorithms. Wind field reconstruction (WFR) methods offer users greater control over LiDAR measurements, enabling customised flow assumptions and parameter estimation. These measurements were taken during a measurement campaign on a wind turbine in the Belgian offshore zone. The WFR method has detected weather events, such as high shear, during the measurement campaign. These events are also linked to on-site weather conditions by using open-source metocean data. The findings align with the current literature on the correlation between events and weather conditions and the clear difference between wind profiling and a power law wind profile for loads design as proposed by the International Electrotechnical Commission (IEC) standard. The results emphasise the importance of real measurements in understanding wind field characteristics, offering improved accuracy compared to standard assumptions, such as the IEC power law profile used for load design. This work underscores the value of real-life wind profiling for designing and operating wind farms in offshore environments.