# The helix approach: using dynamic individual pitch control to enhance wake mixing in wind farms

arXiv: https://arxiv.org/abs/1912.10025 · HTML: https://mlsanity.com/paper/1912.10025/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Dec 2019.

## Built on by (most cited first, 1 of 1)

- [Reinforcement Learning Increases Wind Farm Power Production by Enabling Closed-Loop Collaborative Control](https://mlsanity.com/paper/2506.20554/) (2025)

## Abstract (arXiv)

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.