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The helix approach: using dynamic individual pitch control to enhance wake mixing in wind farms
Joeri Alexis Frederik, Bart Matthijs Doekemeijer, Sebastiaan Paul Mulders, Jan-Willem van Wingerden
TL;DR
Dynamic wake-mixing control can increase downstream energy capture, but varying upstream induction or yaw also causes substantial power and thrust fluctuations. The helix approach uses Individual Pitch Control to dynamically vary the thrust direction through rotor tilt and yaw moments, creating a helical wake. The helix approach increases wake energy by up to 47% and two-turbine energy capture by up to 7.5%.
Problem
Dynamic wake-mixing control can increase downstream energy capture, but varying upstream induction or yaw also causes substantial power and thrust fluctuations.
Method
The helix approach uses Individual Pitch Control to dynamically vary the thrust direction through rotor tilt and yaw moments, creating a helical wake.
Results
The helix approach increases wake energy by up to 47% and two-turbine energy capture by up to 7.5%.
Takeaways & Limitations
The simulations provide a proof of concept that helix-based Dynamic IPC can be an effective wind-farm control strategy for enhancing wake recovery.
Takeaways & Limitations
The reported 7.5% energy-capture gain is an indication of potential because optimal helix control settings have not yet been evaluated.
Abstract
from arXiv · showhide
Wind farm control using dynamic concepts is a research topic that is receiving an increasing amount of interest. The main concept of this approach is that dynamic variations of the wind turbine control settings lead to higher wake turbulence, and subsequently faster wake recovery due to increased mixing. As a result, downstream turbines experience higher wind speeds, thus increasing their energy capture. The current state of the art in dynamic wind farm control is to vary the magnitude of the thrust force of an upstream turbine. Although very effective, this approach also leads to increased power and thrust variations, negatively impacting energy quality and fatigue loading. In this paper, a novel approach for the dynamic control of wind turbines in a wind farm is proposed: using individual pitch control, the fixed-frame tilt and yaw moments on the turbine are varied, thus dynamically manipulating the wake. This strategy is named the helix approach since the resulting wake has a helical shape. Large eddy simulations of a two-turbine wind farm show that the helix approach leads to enhanced wake mixing with minimal power and thrust variations.
1 | INTRODUCTION
Dynamic wind-farm control seeks faster wake recovery and higher downstream energy capture, but existing dynamic induction and yaw strategies can cause substantial power and thrust fluctuations. The paper introduces Dynamic Individual Pitch Control and evaluates the helix approach as a lower-variation method for dynamically mixing wakes.
- Motivation: Wake mixing lets the wake interact with faster free-stream flow, recovering energy so downstream turbines experience higher wind velocity.
- Motivation: Existing dynamic induction and yaw approaches enhance wake mixing but vary upstream thrust, causing substantial power and load fluctuations.These fluctuations are disadvantageous for power quality and fatigue loading.
- Approach: The paper combines wake steering through individual pitch control with dynamic wind-farm control to manipulate wake direction over time.Dynamic IPC uses Multi-Blade Coordinate transformations to vary rotor tilt and yaw moments.
- Approach: The helix approach dynamically moves the wake horizontally and vertically, producing a helical wake and aiming for enhanced mixing with minimal rotor-thrust fluctuations.
- Evaluation: High-fidelity LES simulations evaluate the helix approach’s effects on the wake and downstream turbine against existing control strategies.The simulations use SOWFA and compare the proposed strategy with established approaches.
2 | SIMULATION ENVIRONMENT
The study uses SOWFA, a high-fidelity large-eddy simulation environment, to model wind turbines and enable individual blade-pitch setpoints. It examines both uniform-flow demonstrations and more realistic turbulent atmospheric-boundary-layer conditions in single- and two-turbine cases.
- Simulation environment: SOWFA provides a high-fidelity large-eddy solver that models atmospheric flow and turbine interaction using actuator disks or actuator lines.
- Simulation environment: The adapted SOWFA source code assigns different pitch setpoints to individual blades, enabling Individual Pitch Control.
- Simulation cases: Uniform inflow is used to demonstrate Dynamic IPC, although the authors note that these conditions do not represent realistic wind-farm operation.The absence of turbulence simplifies interpretation of the working principles.
- Simulation cases: A second case uses a neutral atmospheric boundary layer with precursor-generated inflow and 5.0% turbulence intensity.
- Simulation cases: The cases investigate a single turbine’s wake and turbine effects before adding a second turbine 5 rotor diameters downstream to assess energy-capture gains.
3 | CONTROL STRATEGY
The paper compares static and dynamic wind-farm control strategies before introducing DIPC, which manipulates wake direction through periodic individual blade pitching. The helix strategy uses sinusoidal tilt and yaw moments to promote wake mixing while avoiding large thrust-magnitude variations.
- 3.1 | Static Induction Control: Greedy control is the industry-standard baseline, while static induction control lowers upstream induction to increase downstream power capture; reported gains over greedy control are minor to non-existent.Periodic DIC instead varies upstream induction sinusoidally to enhance wake mixing and has been shown to increase small-farm power production in simulations and wind-tunnel experiments.
- 3.2 | Periodic Dynamic Induction Control: For DIC, the frequency is parameterized by St = feD/U∞, with prior work identifying St ≈ 0.25 as optimal and the present simulations adopting that frequency.For the DTU 10MW turbine at 9 m/s, St ≈ 0.25 corresponds to fe = 0.0126 Hz; evaluation found the optimum around St = 0.25 at distances ≥5D.
- 3.3 | Dynamic Individual Pitch Control: The DIPC section defines the novel approach as dynamically moving the wake horizontally and vertically through periodic yaw and tilt moments generated by individual pitch control.The paper names it the helix approach because the wake propagates through space in a helical fashion.
- 3.3 | Dynamic Individual Pitch Control: DIPC uses individual blade pitch angles to generate slowly varying directional rotor moments, continuously changing wake direction to enhance mixing without significant thrust-magnitude variations.The approach uses the MBC transformation to project blade loads into a fixed frame and implement collective, tilt, and yaw pitch signals.
- 3.3 | Dynamic Individual Pitch Control: The MBC transformation converts rotating blade measurements into fixed-frame collective, tilt, and yaw moments, then inversely maps fixed-frame pitch signals into implementable blade angles.The collective mode represents cumulative out-of-plane rotor moment, while the tilt and yaw modes represent azimuth-independent fixed-frame moments.
- 3.3 | Dynamic Individual Pitch Control: The helix strategy applies sinusoidal excitation to tilt and yaw pitch signals at St = 0.25, producing a counterclockwise circular wake motion and a helical near wake.The resulting motion is described as forced wake meandering, with an excitation period of approximately 80 s in the presented case.
4 | RESULTS
The helix approach enhances wake mixing and downstream energy capture while keeping upstream power and thrust variations near baseline levels. In two-turbine simulations, the 4° CCW helix produced the strongest reported farm-level gain, whereas its pitch-rate variation was higher than baseline.
- Single turbine: All three dynamic strategies increased average wake velocity, with DIC and CCW helix similarly effective at 3D and helix performing increasingly well farther downstream.Figures 6–8 show mean-wind-speed disparities relative to the baseline for DIC, CCW helix, and CW helix cases.
- Single turbine: At 5D, average wake kinetic energy increased 23.8% with DIC, 36.7% with CCW helix, and 19.3% with CW helix.The CCW helix was more effective further downstream, while CW helix was generally less effective than CCW helix because of lower center-wake velocity.
- Single turbine: The helix approach required higher pitch-rate variance: 12.5°/min for CCW and 8.1°/min for CW, compared with 0.08°/min for the low-frequency reference.The paper notes that this improvement in power and thrust variation does not come without an actuator-related cost.
- Single turbine: The helix approach increased potential wind-farm energy capture more effectively than SIC, whose wake energy gain was lower and weakened at larger downstream distances.Upstream power loss was comparable between SIC and the helix approach.
- Two-turbine wind farm: 7.5% power gain was achieved by the 4° CCW helix in the two-turbine farm, versus 4.6% with DIC.The CCW helix therefore delivered the higher reported farm-level energy increase.
5 | CONCLUSIONS
The helix approach uses individual pitch control to dynamically vary thrust direction, creating a helical wake that enhances mixing and wake recovery. Simulations indicate increased energy capture with lower power and thrust variations than dynamic induction control, but the findings remain a proof of concept.
- 5 | CONCLUSIONS: The helix approach uses Individual Pitch Control to vary thrust direction, producing a helical wake that increases mixing and downstream wind speeds.The strategy dynamically manipulates the wake through fixed-frame tilt and yaw moments.
- 5 | CONCLUSIONS: 47%: wake energy increased by up to 47%, with counterclockwise helixes recovering the wake better than clockwise helixes.These results come from high-fidelity large-eddy simulations.
- 5 | CONCLUSIONS: Up to 7.5%: energy capture increased in the simulated two-turbine wind farm, although the optimal helix settings remain unevaluated.The reported gain indicates potential rather than an upper limit.
- 5 | CONCLUSIONS: The helix approach increased energy capture more effectively than static derating and dynamic induction control, while reducing power and thrust variations by over a factor of 2 versus dynamic induction control.The comparison is based on the current simulations.
- 5 | CONCLUSIONS: Unlike yaw-based wake redirection, the helix strategy remains within the turbine’s designed operating range, potentially easing industrial adaptation.The paper connects this operating condition with avoiding slow certification protocols and fundamental turbine changes.
- 5 | CONCLUSIONS: The study is a proof of concept; further work must examine optimal excitation, loading effects, closed-loop control, larger farms, wind-tunnel experiments, and full-scale tests.The full potential of dynamic IPC and the helix approach has not yet been established.