Mesh generation, sizing and convergence for onshore and offshore wind farm Atmospheric Boundary Layer flow simulation with actuator discs

Gargallo-Peiró, Abel; Ávila, Matías; Owen, Herbert; Prieto-Godino, Luis; Folch, Arnau

doi:10.1016/j.jcp.2018.08.031

Cited by 22 publications

(32 citation statements)

References 36 publications

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“…The simulation of a DC on complex terrain implies the preprocess, the AlyaCFD‐Wind simulation and the postprocess. A set of preprocessing software tools assimilate terrain information, generate a structured mesh (see Gargallo‐Peiró et al() for details) and impose initial and time‐dependent boundary conditions (IC and Boundary Conditions (BC)). The present work assumes that the computational meshes are composed by hexahedral elements and have three differentiated regions: an external flat buffer (used to accommodate the inflow BCs and to avoid recirculation at the outflow boundary), an adjacent transition zone, and an inner higher‐resolution zone, henceforth called RoI.…”

Section: Simulationmentioning

confidence: 99%

Diurnal cycle RANS simulations applied to wind resource assessment

2018

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Microscale computational fluid dynamics (CFD) models can be used for wind resource assessment on complex terrains. These models generally assume neutral atmospheric stratification, an assumption that can lead to inaccurate modeling results and to large uncertainties at certain sites. We propose a methodology for wind resource evaluation based on unsteady Reynolds averaged Navier‐Stokes (URANS) simulations of diurnal cycles including the effect of thermal stratification. Time‐dependent boundary conditions are generated by a 1D precursor to drive 3D diurnal cycle simulations for a given geostrophic wind direction sector. Time instants of the cycle representative of four thermal stability regimes are sampled within diurnal cycle simulations and combined with masts time series to obtain the wind power density (WPD). The methodology has been validated on a complex site instrumented with seven met masts. The WPD spatial distribution is in good agreement with observations with the mean absolute error improving 17.1% with respect to the neutral stratification assumption.

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Section: Simulationmentioning

confidence: 99%

Diurnal cycle RANS simulations applied to wind resource assessment

2018

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“…Given the above background, the present study investigated the validity of a computational fluid dynamics (CFD)-based method for assessing the risk of wind turbine failures caused by terrain-induced turbulence at the planning stage of wind farm construction. CFD is a numerical simulation technique (software), which can simulate three-dimensional wind flow using computers [1][2][3][4][5][6][7][8][9][10][11][12]. The use of CFD software allows desktop assessment of wind flow for a potential wind farm prior to its actual construction.…”

Section: Introductionmentioning

confidence: 99%

A Large-Eddy Simulation-Based Assessment of the Risk of Wind Turbine Failures Due to Terrain-Induced Turbulence over a Wind Farm in Complex Terrain

Uchida

Takakuwa²

2019

Energies

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The first part of the present study investigated the relationship among the number of yaw gear and motor failures and turbulence intensity (TI) at all the wind turbines under investigation with the use of in situ data. The investigation revealed that wind turbine #7 (T7), which experienced a large number of failures, was affected by terrain-induced turbulence with TI that exceeded the TI presumed for the wind turbine design class to which T7 belongs. Subsequently, a computational fluid dynamics (CFD) simulation was performed to examine if the abovementioned observed wind flow characteristics could be successfully simulated. The CFD software package that was used in the present study was RIAM-COMPACT, which was developed by the first author of the present paper. RIAM-COMPACT is a nonlinear, unsteady wind prediction model that uses large-eddy simulation (LES) for the turbulence model. RIAM-COMPACT is capable of simulating flow collision, separation, and reattachment and also various unsteady turbulence–eddy phenomena that are caused by flow collision, separation, and reattachment. A close examination of computer animations of the streamwise (x) wind velocity revealed the following findings: As we predicted, wind flow that was separated from a micro-topographical feature (micro-scale terrain undulations) upstream of T7 generated large vortices. These vortices were shed downstream in a nearly periodic manner, which in turn generated terrain-induced turbulence, affecting T7 directly. Finally, the temporal change of the streamwise (x) wind velocity (a non-dimensional quantity) at the hub-height of T7 in the period from 600 to 800 in non-dimensional time was re-scaled in such a way that the average value of the streamwise (x) wind velocity for this period was 8.0 m/s, and the results of the analysis of the re-scaled data were discussed. With the re-scaled full-scale streamwise wind velocity (m/s) data (total number of data points: approximately 50,000; time interval: 0.3 s), the time-averaged streamwise (x) wind velocity and TI were evaluated using a common statistical processing procedure adopted for in situ data. Specifically, 10-min moving averaging (number of sample data points: 1932) was performed on the re-scaled data. Comparisons of the evaluated TI values to the TI values from the normal turbulence model in IEC61400-1 Ed.3 (2005) revealed the following: Although the evaluated TI values were not as large as those observed in situ, some of the evaluated TI values exceeded the values for turbulence class A, suggesting that the influence of terrain-induced turbulence on the wind turbine was well simulated.

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“…Utmost caution is required, especially for wind power stations with complicated topography, in planning an optimum arrangement 2 of 27 of wind turbines and controlling both maintenance and management. Diversified tasks are increasingly important to avoid accumulated fatigue of wind load in wind turbines due to terrain-induced turbulence, to reduce malfunctions and accidents inside and outside wind turbines, and to improve the availability of wind turbines [1][2][3][4][5][6][7][8][9][10][11]. Considering social and engineering requests at present, the crucial purpose of the present study is to establish a system with a numerical diagnostic technique for wind status, which contributes to the proper operation of wind farms, an adequate understanding of the indigenous wind environments of each site, including terrain-induced turbulence, and a reduction of malfunctions and accidents associated with wind turbines [12][13][14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

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

Uchida

Kawashima²

2019

Energies

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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.

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Mesh generation, sizing and convergence for onshore and offshore wind farm Atmospheric Boundary Layer flow simulation with actuator discs

Cited by 22 publications

References 36 publications

Diurnal cycle RANS simulations applied to wind resource assessment

Diurnal cycle RANS simulations applied to wind resource assessment

A Large-Eddy Simulation-Based Assessment of the Risk of Wind Turbine Failures Due to Terrain-Induced Turbulence over a Wind Farm in Complex Terrain

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

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