Posters

Abstract

The offshore environment has been looked at by the wind energy industry as an attractive place to install wind farms due to its abundant wind resources. Due to the challenges related to observational data gathering in offshore, the industry often employs wind-profile models as an alternative to assess the wind resource. Towards this end, the power law is one of the most used models to vertically extrapolate the wind speed. In this work, we assess the uncertainty associated with the power-law-modelled wind-profile in comparison with reference wind profiles measured by the EOLOS floating lidar and fixed lidar. The EOLOS floating lidar system is an autonomous oceanic buoy fully equipped with multiple sensors to measure metocean parameters, such as surface water temperature, wave periods, and current direction. In addition, it hosts a ZX300M continuous-wave lidar, which provides horizontal and vertical wind speed, and wind direction at configurable heights ranging from 10 to 300 m. A total of 25 floating-lidar validation campaigns were considered for analysis. They took place in the Lichteiland Goeree (LEG) platform, North Sea, which hosts a fixed lidar. Modelled and observed wind-speed profiles are compared at five heights: 40, 90, 115, 140, 165, 190, and 240 m. Computing the power-law-derived wind speed by assuming a constant wind-shear exponent of 1/7 is a common practice in the wind industry. However, recent studies have shown that the wind shear exponent greatly varies according to the site location, atmospheric stability, and season [1, 2]. Thus, aimed at obtaining the most accurate predictions, the modelled wind profile was computed as the best fit to the observed one via a least squares procedure. Our results provide the uncertainty quantification of the power-law predicted wind speed as a function of height, which can serve as key information to support further wind resource assessment studies. Moreover, we validate the floating-lidar-derived wind-shear exponent against the reference fixed-lidar estimates. References [1] Lopez-Villalobos, C. A., Martinez-Alvarado, O., Rodriguez-Hernandez, O., & Romero-Centeno, R. (2022). Analysis of the influence of the wind speed profile on wind power production. Energy Reports, 8, 8079-8092. [2] Barthelmie, R. J., Shepherd, T. J., Aird, J. A., & Pryor, S. C. (2020). Power and wind shear implications of large wind turbine scenarios in the US Central Plains. Energies, 13(16), 4269.