Robust active wake control in consideration of wind direction variability and uncertainty

Abstract

Abstract. The prospects of active wake deflection control to mitigate wake-induced power losses in wind farms have been demonstrated by large eddy simulations, wind tunnel experiments, and recent field tests. However, it has not yet been fully understood how the yaw control of wind farms should take into account the variability in current environmental conditions in the field and the uncertainty in their measurements. This research investigated the influence of dynamic wind direction changes on active wake deflection by intended yaw misalignment. For this purpose the wake model FLORIS was used together with wind direction measurements recorded at an onshore meteorological mast in flat terrain. The analysis showed that active wake deflection has a high sensitivity towards short-term wind directional changes. This can lead to an increased yaw activity of the turbines. Fluctuations and uncertainties can cause the attempt to increase the power output to fail. Therefore a methodology to optimize the yaw control algorithm for active wake deflection was introduced, which considers dynamic wind direction changes and inaccuracies in the determination of the wind direction. The evaluation based on real wind direction time series confirmed that the robust control algorithm can be tailored to specific meteorological and wind farm conditions and that it can indeed achieve an overall power increase in realistic inflow conditions. Furthermore recommendations for the implementation are given which could combine the robust behaviour with reduced yaw activity.

Design and Analysis of a Wake Steering Controller with Wind Direction Variability

“…7a, however, exhibits characteristics of both yaw position and wind direction uncertainty. Because the mean yaw positions achieved based on the simulation results are closer to the theoretical mean yaw values with no yaw position uncertainty, most of the yaw error can likely be attributed to wind direction uncertainty, as modeled by Rott et al (2018). The procedure used to quantify the amount of wind direction and yaw position uncertainty, described by σ φ and σ θ , respectively, used in the remainder of this research is explained in Section 3.3.…”

“…As explained by Rott et al (2018), the PDF of the wind direction during a 5-minute time period can be approximated as a normal distribution. Because wind turbines typically yaw every few minutes or so-remaining at fixed yaw positions otherwise (see Fig.…”

“…To optimize a wake steering strategy for energy production, Quick et al (2017) use optimization under uncertainty (OUU) to find yaw offset targets that maximize energy production when there is uncertainty in the achieved yaw position. Rott et al (2018) similarly use an OUU approach to optimize yaw offsets for energy production considering variability and uncertainty in the wind direction during periods of constant yaw position. Using the FLORIS wake model, both Quick et al (2017) and Rott et al (2018) show that robust wake steering strategies accounting for yaw or wind direction uncertainty typically involve lower-magnitude yaw offsets yet outperform "static-optimal" wake steering strategies, which are optimized for fixed wind directions, when uncertainty exists.…”

“…This article builds on the work of Quick et al (2017) and Rott et al (2018) by including both wind direction uncertainty, resulting from wind direction variability, and yaw position uncertainty in the robust yaw offset optimization process. An additional contribution of this work is to quantify wind direction and yaw position uncertainty using realistic yaw and yaw offset control simulations with stochastic wind direction signals based on field measurements.…”

Wake steering optimization under uncertainty

“…Quick et al (2017) formulated the wake steering problem using OUU, assuming large uncertainties in the yaw positions of individual turbines. Subsequently, Rott et al (2018) formulated and solved a wake steering OUU problem for a nine-turbine plant, assuming uncertainty in the measured inflow direction. More recently, Simley et al (2019) formulated an OUU problem taking yaw position uncertainty and inflow direction variability into account.…”