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%.

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.