Session: 01-06-01CFD & Numerical Methods - I

Submission Number: 155486

A Numerical Investigation of the Impact of Waves on a Large Floating Wind Farm in Northwest Atlantic 

This study investigated the combined effects of waves and atmospheric turbulence on the power output of a deep-water floating offshore wind farm in the Northwest Atlantic of Canada. A scale-adaptive large-eddy simulation (LES) framework was used to model a 50-turbine wind farm featuring 15 MW turbines with 240-meter rotor diameters. The marine atmospheric boundary layer (MABL) was simulated using wave drag parameterization via the Charnock method, Monin-Obukhov similarity theory, and stochastic turbulence forcing. The simulations assumed the rated wind speed, stochastically varying wind directions, and wave amplitudes between 0.2 m and 2 m. The scale-adaptive LES employed 107 million grid points within a high-performance computing framework to resolve energy-containing turbulence structures, while a vortex stretching-based subgrid model accounted for small-scale turbulence. A Gaussian actuator disk model simulated turbine wakes, incorporating wake interactions and wave effects. Additionally, a mathematical model was developed to explore the aerodynamic response of turbines to large-amplitude wave motions, providing insights into turbine performance in complex marine environments.

The data analysis was conducted in two stages. First, standard vertical profiles of the marine atmospheric boundary layer were evaluated to validate the LES framework against a realistic met-ocean environment. The full-scale LES data were compared with findings from past studies that used wind tunnel experiments and field measurements from offshore wind farms. Second, Proper Orthogonal Decomposition (POD) and Stein's Unbiased Risk Estimate with Wavelet Transforms (SURE-WT) were applied to identify the dominant frequency ranges influenced by waves.

The results indicate that atmospheric turbulence is the primary driver of power fluctuations, while also enhancing overall power output via vertical flux entrainment. Large-amplitude waves contributed to frequency ranges beyond the turbine's natural frequency, which can improve turbine performance under certain conditions. The findings emphasize that marine atmospheric turbulence and wave drag collectively enhance the energy production of large floating wind farms. For turbines of this scale, adopting a pitch control strategy that accounts for Ekman spiral effects and wind-wave misalignment is critical, especially when using spar technology as the floating base for the turbine.

Presenting Author: Jahrul Alam Memorial University of Newfoundland

Presenting Author Biography: Dr. Jahrul Alam earned his Ph.D. in Applied Mathematics, specializing in turbulence, from McMaster University in 2006. He subsequently worked as a SHARCNET postdoctoral fellow in atmospheric modeling at the Department of Earth and Environmental Sciences, University of Waterloo, and was a visiting scholar at the Department of Atmospheric Science, National Taiwan University. In 2008, he joined Memorial University as an Assistant Professor in the Department of Mathematics and Statistics, where he is now a full Professor, cross-appointed to the Department of Physics and Physical Oceanography. He also served as Chair of the Scientific Computing Program at Memorial. Dr. Alam's research focuses on the application of wavelet transforms in turbulent flows and large eddy simulations, with contributions to wind energy and atmospheric boundary layer studies. His recent work includes advancements in deep learning-based scale-adaptive large eddy simulation of floating wind farms, wavelet-based adaptive mesh generation, canopy-based immersed boundary methods, and phase-field modeling of multiphase flows