Wakes of Wind Turbines in Yaw for Wind Farm Power Optimization (original) (raw)
Energies
https://doi.org/10.3390/EN15186553
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Abstract
The application of wind-generated energy is increasing at a great rate, about 11% per year, with an installed capacity of 837 GW in 2021, and it is the primary non-hydro renewable technology; in many countries, it is the main source of electric energy [...]
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Wake steering has an impact on both the wind farm energy yield and turbine loads. We evaluate these effects based on yaw-corrected power and thrust curves and tabulated turbine load simulation results. In a first step, wind direction and wind speed dependent yaw angles were determined by maximization of the wind farm power for an example wind farm. Secondly, the optimizations were repeated for the objective of minimal flapwise blade fatigue loads. The results were then combined such that the power optimized yaw angles dominate the partial load region while the load optimized results were chosen for higher wind speeds. We find that this combination increases the annual energy production in an example wind rose while simultaneously reducing the lifetime damage equivalent loads. The analysis was repeated including wind direction uncertainty into the optimization. This significantly reduced the benefit of wake steering on AEP but caused only a mild decrease of the overall load reduction.
Wind Energy Science
Wake steering is a wind farm control strategy in which upstream wind turbines are misaligned with the wind to redirect their wakes away from downstream turbines, thereby increasing the net wind plant power production and reducing fatigue loads generated by wake turbulence. In this paper, we present results from a wake-steering experiment at a commercial wind plant involving two wind turbines spaced 3.7 rotor diameters apart. During the 3-month experiment period, we estimate that wake steering reduced wake losses by 5.6 % for the wind direction sector investigated. After applying a long-term correction based on the site wind rose, the reduction in wake losses increases to 9.3 %. As a function of wind speed, we find large energy improvements near cut-in wind speed, where wake steering can prevent the downstream wind turbine from shutting down. Yet for wind speeds between 6-8 m/s, we observe little change in performance with wake steering. However, wake steering was found to improve energy production significantly for below-rated wind speeds from 8-12 m/s. By measuring the relationship between yaw misalignment and power production using a nacelle lidar, we attribute much of the improvement in wake-steering performance at higher wind speeds to a significant reduction in the power loss of the upstream turbine as wind speed increases. Additionally, we find higher wind direction variability at lower wind speeds, which contributes to poor performance in the 6-8 m/s wind speed bin because of slow yaw controller dynamics. Further, we compare the measured performance of wake steering to predictions using the FLORIS (FLOw Redirection and Induction in Steady State) wind farm control tool coupled with a wind direction variability model. Although the achieved yaw offsets at the upstream wind turbine fall short of the intended yaw offsets, we find that they are predicted well by the wind direction variability model. When incorporating the expected yaw offsets, estimates of the energy improvement from wake steering using FLORIS closely match the experimental results.
Modeling Wind Turbine Wakes for Wind Farms
Lehr/Alternative, 2016
The simulation of the wakes behind wind turbines is important in predicting energy yields in wind farms, and so plays a role in planning the layout of these farms. As both wind turbines and farms increase in size, wind farm modellers have faced challenges as previously-held assumptions and parameterisations become inadequate -requiring more detailed, less parameterised methods such as those available through computational fluid dynamics. In this article the authors chart the progress of wind turbine wake modelling from analytical methods towards computational fluid dynamics, discussing approaches such as Reynolds-averaged Navier-Stokes and Large Eddy Simulation.
Modelling wind turbine wakes for wind farms
The simulation of the wakes behind wind turbines is important in predicting energy yields in wind farms, and so plays a role in planning the layout of these farms. As both wind turbines and farms increase in size, wind farm modellers have faced challenges as previously-held assumptions and parameterisations become inadequate – requiring more detailed, less parameterised methods such as those available through computational fluid dynamics. In this article the authors chart the progress of wind turbine wake modelling from analytical methods towards computational fluid dynamics, discussing approaches such as Reynolds-averaged Navier-Stokes and Large Eddy Simulation.
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References (10)
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- Wei, D.Z.; Wang, N.N.; Wan, D.C. Modelling Yawed Wind Turbine Wakes: Extension of a Gaussian-Based Wake Model. Energies 2021, 14, 4494. [CrossRef]
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