Wind farm flow control: Demonstrating potential at utility-scale

The magnitude of wake interactions between individual wind turbines depends on the atmospheric conditions. Wake interactions are suppressed by mixing in highly turbulent atmospheric flow. For inflow atmospheric conditions with lower ambient turbulence, flow control has demonstrated potential in idealized numerical and wind tunnel experiments to increase wind farm power production. We investigate flow control methodologies to increase utility-scale wind farm energy production in field experiments of turbines of rotor diameter greater than 100 meters. We first characterize the power production of the individual wind turbines and the wind farm depending on the ambient conditions and the turbine control strategy. We then leverage a novel hybrid physics- and data-driven wake modeling framework to optimize the yaw misalignment angles for wake steering control to maximize wind farm power. We impose the yaw misalignment angles at a utility-scale wind farm and measure their impact on the power and energy production of the farm over a period of months. Wake steering control results in a statistically significant increase in wind farm power and energy production.