In this study, large-eddy simulation is combined with a turbine model to investigate the influence of atmospheric thermal stability on wind-turbine wakes. The simulation results show that atmospheric stability has a significant effect on the spatial distribution of the mean velocity deficit and turbulence statistics in the wake region as well as the wake meandering characteristics downwind of the turbine. In particular, the enhanced turbulence level associated with positive buoyancy under the convective condition leads to a relatively larger flow entrainment and, thus, a faster wake recovery. For the particular cases considered in this study, the growth rate of the wake is about 2.4 times larger for the convective case than for the stable one. Consistent with this result, for a given distance downwind of the turbine, wake meandering is also stronger under the convective condition compared with the neutral and stable cases. It is also shown that, for all the stability cases, the growth rate of the wake and wake meandering in the vertical direction is smaller compared with the ones in the lateral direction. This is mainly related to the different turbulence levels of the incoming wind in the different directions, together with the anisotropy imposed by the presence of the ground. It is also found that the wake velocity deficit is well characterized by a modified version of a recently proposed analytical model that is based on mass and momentum conservation and the assumption of a self-similar Gaussian distribution of the velocity deficit. Specifically, using a two-dimensional elliptical (instead of axisymmetric) Gaussian distribution allows to account for the different lateral and vertical growth rates, particularly in the convective case, where the non-axisymmetry of the wake is stronger. Detailed analysis of the resolved turbulent kinetic energy budget in the wake reveals also that thermal stratification considerably affects the magnitude and spatial distribution of the turbulence production, dissipation, and transport terms.

Influence of atmospheric stability on wind-turbine wakes: A large-eddy simulation study

Abstract Regional meteorological models are becoming a generalized tool for wind resource forecasting, due to their capacity to simulate local flow dynamics impacting wind farm production. This study focuses on the case of production forecast and validation for a real onshore wind farm using high horizontal and vertical resolution WRF (Weather Research and Forecasting) model simulations. The wind farm is located in Galicia, in the northwest of Spain, in a complex region with high wind resource. Utilizing the Fitch scheme, specific for wind farms, a period of one year is simulated with a daily operational forecasting set-up. Power and wind predictions are obtained and compared with real data at each wind turbine hub, provided by the management company. Results show that WRF yields good wind power operational predictions for this kind of wind farms, due to a good representation of the planetary boundary layer behaviour of the region and the good performance of the Fitch scheme under these conditions. The best mean annual error (MAE) obtained is 1.87 m/s for wind speed and 14.75% for wind power. By comparing experiments with and without Fitch scheme, we estimate wind resource losses in the area due to the wake disturbances. The mean annual wake or environmental footprint of the farm extends for several kilometres in the southwest-northeast direction of the prevailing winds, with resource losses of 0.5% even at 17 km from the turbines.

Wind power forecasting for a real onshore wind farm on complex terrain using WRF high resolution simulations.

Optimal design of hydro-wind-PV multi-energy complementary systems considering smooth power output

Sounding out the repowering potential of wind energy – A scenario-based assessment from Germany

Climate change can strongly affect renewable energy production. The state of the art in projecting future renewable energy generation has focused on using regional climate prediction. However, regional climate prediction is characterized by inherent uncertainty due to the complexity of climate models. This work provides a comprehensive study to quantify the impact of climate uncertainties in projecting future renewable energy potential over five climate zones of Europe. Thirteen future climate scenarios, including five global climate models (GCMs) and three representative concentration pathways (RCPs), are downscaled by the RCA4 regional climate model (RCM) over 90 years (2010–2099), divided into three 30-year periods. Solar and wind energy production is projected considering short-/long-term climate variations and uncertainties in seven representative cities (Narvik, Gothenburg, Munich, Antwerp, Salzburg, Valencia, and Athens). The results showed that the uncertainty caused by GCMs has the most substantial impact on projecting renewable energy generation. The variations due to GCM selection can become even larger than long-term climate change variations over time. Climate change uncertainties lead to over 23% and 45% projection differences for solar PV and wind energy potential, respectively. While the signal of climate change in solar radiation is weak between scenarios and over time, wind energy generation is affected by 25%.

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Climate Change and Renewable Energy Generation in Europe—Long-Term Impact Assessment on Solar and Wind Energy Using High-Resolution Future Climate Data and Considering Climate Uncertainties

Partial repowering analysis of a wind farm by turbine hub height variation to mitigate neighboring wind farm wake interference using mesoscale simulations

Optimization of a wind farm by coupled actuator disk and mesoscale models to mitigate neighboring wind farm wake interference from repowering perspective

Abdul Haseeb Syed

Papers

Partial repowering analysis of a wind farm by turbine hub height variation to mitigate neighboring wind farm wake interference using mesoscale simulations

Optimization of a wind farm by coupled actuator disk and mesoscale models to mitigate neighboring wind farm wake interference from repowering perspective

Wind speed and power forecasting of a utility-scale wind farm with inter-farm wake interference and seasonal variation