Numerical modelling of neutral atmospheric boundary layer flow through heterogeneous forest canopies in complex terrain (a case study of a Swedish wind farm)

Artikel i vetenskaplig tidskrift, 2021

This paper exposes the risk of generalization of wind conditions from a single met-mast measurement to be representative of the actual flow field in a wind farm situated in complex terrain. As a case study, Large-Eddy Simulation (LES) of the neutral Atmospheric Boundary Layer (ABL) flow for a mid-western Sweden wind farm is performed. The site-specific complex topography and the forest properties like the Plant Area Density and the tree heights are extracted from the Airborne Laser Scanning (ALS) 3D data, thus the forest is heterogeneous. To emphasize the impact of the local topography and surface roughness on the wind field, the wind turbines are not included in the numerical simulations. The predicted wind speeds using LES are compared to wind speed from the nacelle-mounted anemometers taken from the wind farm's turbine SCADA data, focusing on the wake-free turbines. A sufficient degree of match is observed, supporting the accuracy of the numerical simulations. The results show that inflow variables i.e., mean wind speed, shear exponent and turbulence intensity vary at each wind turbine location justifying the need for turbine-specific assessment of the wind resource in a wind farm located in forested complex terrain. The inter-turbine (between turbines in the wind farm) differences in wind resource is quantified in terms of the difference in turbine-specific structural and mechanical loads by running wind turbine mechanical simulations using the extracting the wind fields predicted by the LES. The results show that not only inter-turbine loads varying significantly in the wind farm, but the turbine loads also differ significantly if a homogeneous assumption is made for the forest. Most importantly, it was found that the homogeneous forest assumption predicted a higher turbulence intensity compared to a heterogeneous forest resulting.