Engineering wake models are essential tools in wind farm design and operation. Their computational efficiency enables rapid layout optimization, energy calculation, and turbine control setpoint design. As wind farms grow in scale and density, wake interactions between turbines limit overall energy capture and increase structural loading. Wind Farm Control strategies have become critical for mitigating these effects. While wake steering, the intentional yaw misalignment of upstream turbines, has consistently demonstrated power gains, new dynamic control strategies are emerging. Among these, the Helix approach has shown particular promise in accelerating wake recovery and improving downstream power production. While engineering models for wake steering are well established, dedicated models for the Helix approach remain unavailable. This study presents a novel steady-state engineering model for predicting the velocity deficit and added turbulence of wind turbines operating under Helix actuation. The proposed model extends double-Gaussian velocity deficit and bell-curve– shaped turbulence intensity formulations to account for Helix-specific effects of actuation amplitude and ambient turbulence. Calibration and validation against high-fidelity large-eddy simulations demonstrate strong agreement across a wide range of operating conditions. The model accurately reproduces wake recovery trends, variations in the velocity-deficit profile, turbulence distributions, and the resulting downstream power availability. Finally, a case study on a large offshore wind farm illustrates that, under typical offshore atmospheric conditions, Helix control and wake steering yield individual power gains of up to 2.5% and 6.1%, respectively, while their combined application achieves total power gains of up to 7.1%.

Benchmarking numerical models is essential for validating their accuracy and ensuring consistency across simulation platforms. This study presents a comparative benchmark analysis of two widely used Large Eddy Simulation (LES) codes, AMR-WIND and NREL SOWFA-6, focusing on wind turbine rotor performance, wake dynamics, and atmospheric boundary layer (ABL) representation. The evaluation includes an actuator line model (ALM)-based uniform inflow wind turbine simulation and ABL precursors under neutral and unstable conditions. The uniform inflow wake analysis examined differences in wind turbine induction and wake development between the two codes. Additionally, neutral and unstable atmospheric boundary layer precursors were generated for an offshore environment and compared. Results indicate a difference in wake breakdown location between the codes (one contributing factor was the difference in numerical schemes used for the advection terms.) The number of actuator points required for smooth velocity distribution across the rotor was higher for SOWFA-6 than AMR-WIND. In ABL precursors, time-averaged flow fields showed strong agreement, though minor discrepancies in turbulence were observed, particularly in unstable conditions, affecting coherence analysis. The energy distribution across wavenumbers showed a good match between the codes, with slight discrepancies observed in the large and small wavenumber regions. The cutoff wavenumber was found to be similar for both codes. Lateral and vertical coherence at small and large separations were in close agreement for the neutral ABL. However, in the unstable ABL, notable differences in coherence were observed between the codes for separations greater than 40 m.

Denser turbine spacing in wind farms leads to increased wake interactions, causing power losses when each turbine operates under its own greedy control scheme. To mitigate these effects, research is exploring strategies that consider the entire wind farm rather than singular turbines. The so-called helix approach has recently gotten significant attention from the research community. It aims to reduce wake losses through periodic individual pitch control. Wake steering on the other hand uses yaw actuation to laterally deflect the wake away from downstream turbines. In this paper, we adapt and validate a steady-state surrogate model to compute the time-averaged velocity field behind a wind turbine operating with the helix approach. The model is tuned using data from Large Eddy Simulations. We compare the helix model to wake steering and baseline operation in a wind farm case study, demonstrating that the helix approach offers promising benefits under specific wind conditions.