Large-Eddy Simulations of Helix Active Wake Control

Abstract

The current change of the Earth's climate necessitates actions to strongly reduce the human carbon footprint. For the energy sector, this implies moving to renewable energy sources like wind. The wind resource is spatially heterogeneous, where wind speeds and power densities are particularly favourable offshore. The favourable offshore wind resource, together with the limited availability of onshore land area for wind energy, motivates the move to offshore wind energy generation. Economic, spatial and environmental considerations suggest clustering wind turbines offshore into wind farms.
Wind turbines clustered in a wind farm operate on average at a lower efficiency than they would achieve in isolation. One major source of this efficiency loss is wake interaction. As wind turbines extract kinetic energy from the wind, they leave behind a region of low wind speed, the so-called wake. When wakes generated by upstream turbines impinge on downstream turbines in the farm, they reduce their power output and thus the overall farm efficiency. In the design phase, the wind farm layout is optimised to minimise wake losses; however, even in an optimal layout wake losses are significant. From the desire to further mitigate the remaining wake losses, the field of wind farm flow control (WFFC) arose, which aims to reduce wake losses by farm-wide coordinated control of the wind turbines.
Wind farm flow control strategies differ based on their working mechanism, e.g. control strategies aim to either reduce the initial wake deficit of upstream turbines by reducing the turbine thrust or redirecting wakes past downstream turbines by intentionally misaligning upstream turbines with the incoming wind direction. A newer category of strategies for WFFC is active wake control (AWC). Compared to the former quasi-steady strategies, AWC strategies are inherently dynamic as their working mechanism relies on unsteady actuation, which aims to trigger underlying instability modes of the wake flow. One of the most recently developed AWC strategies is helix active wake control. It makes use of the individual pitch control capabilities (IPC) of modern wind turbines in order to intentionally force the first instability mode of the wake.
This thesis is concerned with high-fidelity modelling of helix active wake control using large-eddy simulation (LES) of the atmospheric flow, where the effect of IPC is captured by representing the turbine in the LES by means of the actuator line model (ALM). Judging the potential of helix active wake control requires (i) quantifying the arising power-load trade-off, (ii) comparing it to established WFFC strategies like wake steering, and (iii) ultimately testing it in realistic transient atmospheric boundary layers. To this end, the overall objective of this thesis is to
"Assess the performance of helix active wake control in quasi-steady atmospheric boundary layers and develop actuator line model capabilities for its study in coarse grid real weather large-eddy simulations."

In a first step, the sensitivity of helix active wake control to the amplitude of the pitch actuation is quantified for a full wake overlap scenario. It is found that the activation of the control leads to a trade-off between power gain and additional turbine loading in terms of the incurred damage equivalent loads (DEL). While the power gain monotonically increases for pitch amplitudes between one and six degrees, the same trend is observed for the DELs of the actuated turbine. Hence, the value of activating the control and selecting its pitch amplitude setpoint will need to be determined based on a higher-level metric like the current electricity price. 
In a second step, the sensitivity of the power gain achieved with helix active wake control to varying degrees of wake overlap and turbine spacing is compared to wake steering. It is found that wake steering outperforms the helix except for dense spacing combined with full wake overlap. However, when considering a varying wind direction around full wake overlap without an immediate control response, the results suggest that the power gain achieved by the helix control setpoint is more robust.
The previous finding suggests that time-varying wind directions are important for selecting the best control strategy. Hence, in a third step, an actuator line model is implemented into an atmospheric LES code, which allows for driving microscale LES with mesoscale forcing derived from numerical weather prediction models in order to include additional time scales in the problem. The correctness of the ALM implementation is verified with reference to results from four other research LES codes. Additionally, the emphasis is on ensuring accurate thrust and power predictions on coarser LES grids. To this end, the filtered lifting line correction is included in the ALM implementation.
Current corrections for coarse grid ALM-LES, e.g. the filtered lifting line correction, do not consider the complete unsteady problem. Thus, as a last step, we take the IPC actuation underlying helix active wake control as an opportunity to formally investigate unsteadiness in the ALM for scenarios corresponding to unsteady attached flow below stall. By deriving a semi-analytical solution for the two-dimensional "ALM'' its connection to Theodorsen theory is established. Further, this solution allows for determining the optimal kernel width for the unsteady ALM, which is approximately 40% of the chord length and determining bounds of its validity. Importantly, we find that even when using the optimal kernel width, the magnitude of the unsteady force cannot be accurately captured anymore by the ALM if the reduced frequency exceeds k>0.2.
In summary, this thesis contributed to the understanding of under which circumstances the application of helix active wake control for the mitigation of wake effects might be a viable option. Given that the benefits and drawbacks of the helix are at least partially complementary with wake steering control, both control strategies could be seen as pieces of a more comprehensive toolbox of wind farm flow control strategies. The activation of a respective control strategy would then happen only during periods corresponding to its identified favourable conditions. Hence, the model development conducted in the second part of this thesis aims towards building a simulation environment - spanning from mesoscale effects down to airfoil aerodynamics - within which such a selection process of WFFC strategies can be studied in realistic weather conditions.