Full-Scale Experimental Validation of Large-Eddy Simulation of Wind Flows over Complex Terrain: The Bolund Hill

Chaudhari, Ashvinkumar; Hellsten, Antti; Hämäläinen, Jari

doi:10.1155/2016/9232759

Cited by 24 publications

(16 citation statements)

References 35 publications

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“…In this study, the so‐called recycling inflow method is employed for generating the fully developed ABL flow profiles before the turbines. Chaudhari et al have studied the applicabilities of the recycling inflow method for ABL flow modeling over complex terrains, and further, they have shown the validation of the method against field measurements. A more detailed description of the recycling method can be found in the previous studies, and only a brief explanation is given further in this section.…”

Section: Methodsmentioning

confidence: 99%

Performance and wake comparison of horizontal and vertical axis wind turbines under varying surface roughness conditions

2018

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A numerical study of both a horizontal axis wind turbine (HAWT) and a vertical axis wind turbine (VAWT) with similar size and power rating is presented. These large scale turbines have been tested when operating stand‐alone at their optimal tip speed ratio (TSR) within a neutrally stratified atmospheric boundary layer (ABL). The impact of three different surface roughness lengths on the turbine performance is studied for the both turbines. The turbines performance, the response to the variation in the surface roughness of terrain, and the most relevant phenomena involved on the resulting wake were investigated. The main goal was to evaluate the differences and similarities of these two different types of turbine when they operate under the same atmospheric flow conditions. An actuator line model (ALM) was used together with the large eddy simulation (LES) approach for predicting wake effects, and it was implemented using the open‐source computational fluid dynamics (CFD) library OpenFOAM to solve the governing equations and to compute the resulting flow fields. This model was first validated using wind tunnel measurements of power coefficients and wake of interacting HAWTs, and then employed to study the wake structure of both full scale turbines. A preliminary study test comparing the forces on a VAWT blades against measurements was also investigated. These obtained results showed a better performance and shorter wake (faster recovery) for an HAWT compared with a VAWT for the same atmospheric conditions.

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Section: Methodsmentioning

confidence: 99%

Performance and wake comparison of horizontal and vertical axis wind turbines under varying surface roughness conditions

2018

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“…Energies 2018, 11,2638 5 of 15 Figure 4 shows the trajectory of Typhoon No. 0918 (Melor), pressure charts from 9:00, 7 October 2009 and 9:00, 8 October 2009, and the number of wind turbine incidents on these two days.…”

Section: Shiratakiyama Wind Farm and Airflow Characteristics From Thementioning

confidence: 99%

“…Finally, stress exerted on the blades was calculated using a finite element method (FEM) with the RANS analysis results as the boundary conditions. Energies 2018, 11,2638 2 of 15 output from wind turbines, and damage to the interior and exterior of wind turbines (e.g., the breakdown of yaw motors and yaw gears), which have become evident issues [2]. Uchida [1] investigated "extraordinary" terrain-induced turbulence.…”

Section: Introductionmentioning

confidence: 99%

“…As a result of this clarification on the use of wind conditions (turbulence) at a wind power generation facility, there is no doubt that the prediction and evaluation of turbulence intensity over complex terrain by computational fluid dynamics (CFD) such as LES and RANS will become increasingly important [3][4][5][6][7][8][9][10][11][12][13]. Generally, in RANS models, such as k-ε models, the standard deviation of the streamwise wind velocity which is attributable to terrain and/or surface roughness, σ Sur f u , is calculated using the values of turbulence kinetic energy, k; then, the standard deviation of the streamwise wind velocity, σ u , is calculated by taking into account the background atmospheric turbulence intensity, I a [14].…”

Section: Introductionmentioning

confidence: 99%

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Numerical Investigation of Terrain-Induced Turbulence in Complex Terrain by Large-Eddy Simulation (LES) Technique

Uchida

2018

Energies

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In the present study, field observation wind data from the time of the wind turbine blade damage accident on Shiratakiyama Wind Farm were analyzed in detail. In parallel, high-resolution large-eddy simulation (LES) turbulence simulations were performed in order to examine the model's ability to numerically reproduce terrain-induced turbulence (turbulence intensity) under strong wind conditions (8.0-9.0 m/s at wind turbine hub height). Since the wind velocity and time acquired from the numerical simulation are dimensionless, they are converted to full scale. As a consequence, both the standard deviation of the horizontal wind speed (m/s) and turbulence intensity evaluated from the field observation and simulated wind data are successfully in close agreement. To investigate the cause of the wind turbine blade damage accident on Shiratakiyama Wind Farm, a power spectral analysis was performed on the fluctuating components of the observed time series data of wind speed (1 s average values) for a 10 min period (total of 600 data) by using a fast Fourier transform (FFT). It was suggested that the terrain-induced turbulence which caused the wind turbine blade damage accident on Shiratakiyama Wind Farm was attributable to rapid wind speed and direction fluctuations which were caused by vortex shedding from Tenjogadake (elevation: 691.1 m) located upstream of the wind farm.

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“…One technical issue which needs to be resolved in the near future in the field of wind power generation is to establish a numerical wind synopsis prediction technique which allows 1) accurate assessment of the local wind synopsis for wind turbines and 2) identification of local wind risks (terrain-induced turbulence) to wind turbines [1][2][3][4][5][6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

Wind Turbine Control Based on Computational Fluid Dynamics (CFD) and Its Economic Effects

Uchida¹

2018

Preprint

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At the Atsumi Wind Farm in Aichi Prefecture, Japan, damage to wind turbines occurred frequently due to terrain-induced turbulence. In the present study, numerical analyses of terraininduced turbulence were conducted by reproducing the topography in the vicinity of the wind turbine sites in high resolution and using RIAM-COMPACT natural terrain version, which is based on large eddy simulation (LES). The results of the diagnoses indicated that, in the case of south-easterly wind, terrain-induced turbulence is generated at a small terrain feature located upstream of Wind Turbine (WT) #2, which serves as the origin of the turbulence. At the Atsumi Wind Farm, a combination of the series of wind diagnoses and on-site operation experience led to a decision to adopt an "automatic shutdown program" for WTs #1 and #2. Here, "automatic shutdown program" refers to the automatic suspension of wind turbine operation upon the wind speed and direction meeting the conditions associated with significant effects of terrain-induced turbulence at a wind turbine site. The adoption of the "automatic shutdown program" has successfully resulted in a large reduction in the number of occurrences of wind turbine damage, thus, creating major positive economic effects. 1) a reduction in the repair costs by 9.322 million yen per year per wind turbine, 2) an increase in the availability factor by 8.05%, and 3) an increase in the capacity factor by 1.7%.

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Full-Scale Experimental Validation of Large-Eddy Simulation of Wind Flows over Complex Terrain: The Bolund Hill

Cited by 24 publications

References 35 publications

Performance and wake comparison of horizontal and vertical axis wind turbines under varying surface roughness conditions

Performance and wake comparison of horizontal and vertical axis wind turbines under varying surface roughness conditions

Numerical Investigation of Terrain-Induced Turbulence in Complex Terrain by Large-Eddy Simulation (LES) Technique

Wind Turbine Control Based on Computational Fluid Dynamics (CFD) and Its Economic Effects

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