New Assessment Scales for Evaluating the Degree of Risk of Wind Turbine Blade Damage Caused by Terrain-Induced Turbulence

Abstract

The present study scrutinized the impacts of terrain-induced turbulence on wind turbine blades, examining measurement data regarding wind conditions and the strains of wind turbine blades. Furthermore, we performed a high-resolution large-eddy simulation (LES) and identified the three-dimensional airflow structures of terrain-induced turbulence. Based on the LES results, we defined the Uchida-Kawashima Scale_1 (the U-K scale_1), which is a turbulence evaluation index, and clarified the existence of the terrain-induced turbulence quantitatively. The threshold value of the U-K scale_1 was determined as 0.2, and this index was confirmed to not be dependent on the inflow profile, the influence of the horizontal grid resolution, and the influence of the computed azimuth. In addition, we defined the Uchida-Kawashima Scale_2 (the U-K scale_2), which is a fatigue damage evaluation index based on the measurement data and the design value obtained by DNV GL’s Bladed. DNV GL (Det Norske Veritas Germanischer Lloyed) is a third party certification body in Norway, and Bladed has been the industry standard aero-elastic wind turbine modeling software. Using the U-K scale_2, the following results were revealed: the U-K scale_2 was 0.86 < 1.0 (within the designed value) in the case of northerly wind, and the U-K scale_2 was 1.60 > 1.0 (exceeding the designed value) in the case of easterly wind. As a result, it was revealed that the blades of the target wind turbine were directly and strongly affected by terrain-induced turbulence when easterly winds occurred.

Numerical Investigation of Terrain-Induced Turbulence in Complex Terrain Using High-Resolution Elevation Data and Surface Roughness Data Constructed with a Drone

“…The obtained value of U-K scale_1 exceeded the U-K scale_1 threshold of 0.2. From these results, it was revealed that the blades of the target wind turbine were directly and strongly affected by terrain-induced turbulence [11]. This result clarified that due to the shedding of large-scale vortices originating from the hill upstream of the target wind turbine and the generation and suppression of accompanying separated eddies, a terrain-induced turbulence with a 3D structure was formed, and its influence directly extended to near the wind turbine.…”

“…Accompanied by the expansion of the influence range of terrain-induced turbulence in the z direction, the peak value of each standard deviation occurred at a higher position in the z direction in the order of Case2_1, Case3, and Case4. The Uchida-Kawashima scale_1 (U-K scale_1) is a turbulence evaluation index, defined in the literature [11]. The obtained value of U-K scale_1 exceeded the U-K scale_1 threshold of 0.2.…”

“…The obtained value of U-K scale_1 exceeded the U-K scale_1 threshold of 0.2. From these results, it was revealed that the blades of the target wind turbine were directly and strongly affected by terrain-induced turbulence [11]. In Figure 16, Case2, with a smooth surface and without a surface roughness model, is used as an example, and the results of the discussion about a non-dimensional time interval for an estimation of turbulence statistics are shown.…”

“…A wind direction sensor and an anemometer were installed on the nacelle of the wind turbine, and the information from these sensors was used for operation control of the wind turbine. Previous research showed that the irregular winds described above are due to terrain-induced turbulence caused by slight ups and downs in the terrain in the neighborhood of the wind turbine [11][12][13][14]. To precisely reproduce the terrain-induced turbulence on a computer via numerical simulation of the wind conditions, accurately reproducing the terrain condition on site is crucial, including the degrees of ups and downs, the heights of trees covering the surface of terrain, and their spatial distribution.…”

Reproduction of Local Strong Wind Area Induced in the Downstream of Small-Scale Terrain by Computational Fluid Dynamic (CFD) Approach

“…One of the technical problems to be solved in the future in the field of wind power generation is to correctly understand the local wind conditions which are generated around wind turbines and establish a computational wind prospecting technology with higher accuracy than before that can be applied to the survey before the introduction of wind turbines [1][2][3][4][5][6][7][8][9][10][11]. e author's group narrowed the scales down from several m to several km and is developing a computational wind prospecting model that can reproduce local wind conditions with high accuracy (RIAM-COMPACT) [12][13][14][15][16][17][18][19][20][21]. By employing LES (large-eddy simulation) for the turbulence model, it becomes possible to reproduce nonsteady wind conditions that change temporally and spatially.…”