Nocturnal low‐level jet (LLJ) events are commonly observed over the Great Plains region of the USA, thus making this region more favorable for wind energy production. At the same time, the presence of LLJs can significantly modify vertical shear and nocturnal turbulence in the vicinities of wind turbine hub height, and therefore has detrimental effects on turbine rotors. Accurate numerical modeling and forecasting of LLJs are thus needed for precise assessment of wind resources, reliable prediction of power generation and robust design of wind turbines. However, mesoscale numerical weather prediction models face a challenge in precisely forecasting the development, magnitude and location of LLJs. This is due to the fact that LLJs are common in nocturnal stable boundary layers, and there is a general consensus in the literature that our contemporary understanding and modeling capability of this boundary‐layer regime is quite poor. In this paper, we investigate the potential of the Weather Research and Forecasting (WRF) model in forecasting LLJ events over West Texas and southern Kansas. Detailed observational data from both cases were used to assess the performance of the WRF model with different model configurations. Our results indicate that the WRF model can capture some of the essential characteristics of observed LLJs, and thus offers the prospect of improving the accuracy of wind resource estimates and short‐term wind energy forecasts. However, the core of the LLJ tended to be higher as well as slower than what was observed, leaving room for improvement in model performance. Copyright © 2008 John Wiley & Sons, Ltd.

The diurnally varying atmospheric boundary layer observed during the Wangara (Australia) case study is simulated using the recently proposed locally averaged scale-dependent dynamic subgrid-scale (SGS) model. This tuning-free SGS model enables one to dynamically compute the Smagorinsky coefficient and the subgrid-scale Prandtl number based on the local dynamics of the resolved velocity and temperature fields. It is shown that this SGS-model-based large-eddy simulation (LES) has the ability to faithfully reproduce the characteristics of observed atmospheric boundary layers even with relatively coarse resolutions. In particular, the development, magnitude, and location of an observed nocturnal low-level jet are depicted quite well. Some well-established empirical formulations (e.g., mixed layer scaling, spectral scaling) are recovered with good accuracy by this SGS parameterization. The application of this new-generation dynamic SGS modeling approach is also briefly delineated to address several practical wind-energy-related issues.

Numerous previous works have shown that vertical shear in wind speed and wind direction exist in the atmospheric boundary layer. In this work, meteorological forcing mechanisms, such as the Ekman spiral, thermal wind, and inertial oscillation, are discussed as likely drivers of such shears in the statically stable environment. Since the inertial oscillation, the Ekman spiral, and statically stable conditions are independent of geography, potentially significant magnitudes of speed and direction shear are hypothesized to occur to some extent at any inland site in the world. The frequency of occurrence of non-trivial magnitudes of speed and direction shear are analyzed from observation platforms in Lubbock, Texas and Goodland, Indiana. On average, the correlation between speed and direction shear magnitudes and static atmospheric stability are found to be very high. Moreover, large magnitude speed and direction shears are observed in conditions with relatively high hub-height wind speeds. The effects of speed and direction shear on wind turbine power performance are tested by incorporating a simple steady direction shear profile into the fatigue analysis structures and turbulence simulation code from the National Renewable Energy Laboratory. In general, the effect on turbine power production varies with the magnitude of speed and direction shear across the turbine rotor, with the majority of simulated conditions exhibiting power loss relative to a zero shear baseline. When coupled with observational data, the observed power gain is calculated to be as great as 0.5% and depletion as great as 3% relative to a no shear baseline. The average annual power change at Lubbock is estimated to be −0.5%.

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Wind turbine wakes have been recognized as a key issue causing underperformance in existing wind farms. In order to improve the performance and reduce the cost of energy from wind farms, one approach is to develop innovative methods to improve the net capacity factor by reducing wake losses. The output power and characteristics of the wake of a utility-scale wind turbine under yawed flow is studied to explore the possibility of improving the overall performance of wind farms. Preliminary observations show that the power performance of a turbine does not degrade significantly under yaw conditions up to approximately 10°. Additionally, a yawed wind turbine may be able to deflect its wake in the near-wake region, changing the wake trajectory downwind, with the progression of the far wake being dependent on several atmospheric factors such as wind streaks. Changes in the blade pitch angle also affect the characteristics of the turbine wake and are also examined in this paper.