Wake Control Strategies for a Large-Scale Offshore Wind Turbine: A Comparative CFD Study of Axial Induction & Yaw Control on the IEA 15MW Reference Turbine

Abstract

As offshore wind farms continue to grow in scale and number, wake interaction between turbines represents a significant source of power loss and increased fatigue risk. Consequently, there has been an increased interest in wake control strategies. Wake control strategies aim to mitigate these effects but
their comparative effectiveness across power, wake velocity and turbulence intensity is not well established for large offshore turbines. Thus, a computational fluid dynamic (CFD) study comparing three wake control strategies: Axial induction control (AIC) via pitch and, via derating and yaw control, is conducted for a three-turbine inline offshore wind farm using the IEA 15MW reference turbine. This was conducted using OpenFOAM with turbinesFoam actuator line model (ALM) implementation and RANS k − ϵ turbulence modeling. The metrics evaluated for this study are: total farm power output, normalized streamwise velocity, and turbulence intensity along the farm centerline. Each strategy’s control parameters were selected based on ranges reported in existing literature. AIC via pitch tested at −5.0◦, −2.5◦, +2.5◦ and +5.0◦, AIC via derating at 90%, 75% and 60%, and yaw control at 10◦, 20◦ and 30◦. The findings of this study revealed that AIC via negative pitch achieved the highest total farm power (+1.37%) for pitch −2.5◦. However, as turbine 1, T1, operates below its optimal tip speed ratio (TSR), negative pitch increases Ct rather than reducing it, deepening the downstream wake and reducing T2 and T3 power output. AIC via derating produced net negative farm power across all cases but achieved the greatest velocity improvement and turbulence intensity (TI) reduction behind T1, with a TI difference of -5.3% to -18% at T2 and -0.71% to -3.2% at T3, where TI decreased with higher derating levels. Yaw control produced the most balanced results, with a net farm gain of +0.32% for
yaw 10◦ with meaningful downstream improvements, with a TI reduction of -1.15% at T2 and -0.48% at T3. All strategies showed limited benefit to T3 due to dominant wake formation behind T2. These results demonstrate that no single wake control strategy dominates across all performance metrics simultaneously. The decision of which strategy to choose is thus dependent on whether power maximization or fatigue risk reduction is the primary operating objective.

Popular Abstract

As countries shift away from fossil fuels, making wind energy as efficient as possible becomes increasingly important. Today’s offshore turbines are enormous, some taller than the Eiffel Tower, yet almost no research has examined whether wake control strategies work the same way for large turbines as they do for smaller ones. That is exactly the gap this thesis set out to fill.

Wind turbines are built both onshore and offshore in arrangements or farms that are planned to get the most possible energy output from the limited area available for construction. When the wind comes at a turbine, the turbine’s blades rotate, using that rotation to produce energy. In the air directly after the turbine, there is still wind, but it has different properties. For example, the wind after the turbine is slower and choppier, like the flow of water after a boat, but with the wind turbine and air. Despite the previously mentioned planned arrangements of turbines for certain areas, the turbines are still close enough together that the changed wind after one turbine interacts with and affects the second turbine that is behind the first. When the second turbine experiences this affected wind it performs worse in the ways of less energy production, and the blades can experience more harmful strains due to the choppiness of the flow.

This thesis researches how the affected airflow behind an offshore turbine can be improved for the second turbine experiencing this flow behind the first. This improvement comes from changing aspects of the first turbine, such as adjusting the angles of the blades to the incoming wind, slowing down the speed of the blades, and tilting the whole turbine sideways. These adjustments decrease the amount of energy the first turbine takes from the wind so that the turbine after has more available energy to take from in the wind. This may decrease the energy output for the first turbine, but increases the energy produced from the turbine after it. Therefore, it is important to look at the total energy production which adds up the energy from every turbine in the farm. The goal is to increase total energy production and decrease the damaging strains on the blades of the latter turbines.

A key result from this research is that there in an undeniable tradeoff between energy production and the risk of damage from the strain on the turbine. This means that most methods follow the trend of increasing energy production but also increase the risk of damage, or vice versa. More results show that the strategy of tilting the whole turbine sideways by 10 degrees is the best option, since it leads to an increase in the total farm power while also decreasing the risk of damage to the turbine. Slowing down the speed of the blades of the first turbine best decreases the risk of damage to the turbine after it, but the decrease in energy production is too significant to be a realistic option.

A surprising detail that was found is that the turbine model used for reference is not actually designed to operate at optimal conditions. This leads to the conclusion that changing the angles of the blades to the incoming wind for the first turbine increases its energy production, because it is closer to operating at optimal conditions. This increases the total power output for the whole farm more than any other option, but it is not due to helping the latter turbines. This only benefits the first turbine, so it is not a relevant result to what this research is focusing on. Therefore, the energy production results
for this method are not considered in the comparative analysis.

Now, the main benefit of this thesis is that it is a comparative study of large wind turbines. This study gives wind farm operators a clear picture of the tradeoffs when choosing how to control their turbines. If maximizing power is the goal, tilting it slightly sideways offers the most promising balance. If reducing maintenance costs is the priority, slowing the first turbine down is the best option. Thus, the natural next step for this study would be to put a price tag on these tradeoffs, which can be done by calculating exactly how much money is saved by reducing turbine wear against how much revenue is gained from extra power. That calculation would give operators the economic tools to make the best decision for their specific farm, bringing wind energy one step closer to being not just cleaner, but smarter.

• author: Holz, Julia and Aradóttir, Birta
• supervisor: Johan Revstedt; Jens Klingmann
• organization: Department of Energy Sciences
• course: MVKM05 20261
• year: 2026
• type: H2 - Master's Degree (Two Years)
• subject: Technology and Engineering
• keywords: Offshore Wind Farm, Wake Control, Axial Induction Control, Yaw Control, Computational Fluid Dynamics, Actuator Line Method, RANS, Turbulence Intensity, IEA 15MW Reference Turbine
• report number: ISRN: LUTMDN/TMHP-26/5675-SE
• ISSN: 0282-1990
• language: English
• id: 9232801
• date added to LUP: 2026-06-11 09:57:20
• date last changed: 2026-06-11 12:03:36