Field experiment for open-loop yaw-based wake steering at a commercial onshore wind farm in Italy

Abstract

Abstract. The concept of wake steering on wind farms for power maximization has gained significant popularity over the last decade. Recent field trials described in the literature not only demonstrate the real potential of wake steering on commercial wind farms but also show that wake steering does not yet consistently lead to an increase in energy production for all inflow conditions. Moreover, a recent survey among experts shows that validation of the concept currently remains the largest barrier to adoption. In response, this article presents the results of a field experiment investigating wake steering in three-turbine arrays at an onshore wind farm in Italy. This experiment was performed as part of the European CL-Windcon project. While important, this experiment excludes an analysis of the structural loads and focuses solely on the effects of wake steering on power production. The measurements show increases in power production of up to 35 % for two-turbine interactions and up to 16 % for three-turbine interactions. However, losses in power production are seen for various regions of wind directions too. In addition to the gains achieved through wake steering at downstream turbines, more interesting to note is that a significant share in gains is from the upstream turbines, showing an increased power production of the yawed turbine itself compared to baseline operation for some wind directions. Furthermore, the surrogate model, while capturing the general trends of wake interaction, lacks the details necessary to accurately represent the measurements. This article supports the notion that further research is necessary, notably on the topics of wind farm modeling and experiment design, before wake steering will lead to consistent energy gains on commercial wind farms.

Dynamic robust active wake control

“…The conventional approach to (nominal) AWC design involves the synthesis of LUT containing yaw misalignment set-points for the wind turbines in the farm, optimized for a range of input conditions. These include at least the wind direction (Kanev et al, 2018), but sometimes also the wind speed or other atmospheric conditions such as the turbulence intensity (Bossanyi, 2018; Doekemeijer et al, 2021). In this work, the yaw set-points will depend only on the wind direction, while the influence of other parameters on their optimal choice will be considered through stochastic uncertainties in a robust design setting.…”

“…(2017) a value ot 1.44 has been fitted to field measurements. Similar value has been derived for another commercial wind turbine, used in the study Doekemeijer et al (2021). For this reason, a skewed PDF is selected here, defined as it becomes equivalent to the inverse Gaussian distribution, and is therefore referred to as "biased inverse Gaussian" in Table 2.…”

Axial induction controller field test at Sedini wind farm

“…Axial induction control has been investigated using large eddy simulation modelling, often without showing any positive gains in power production -see for example Gebraad (2014). It has since been tested in a boundary layer wind tunnel by Campagnolo et al (2016a, b) as well as in an operational wind farm by van der Hoek et al (2019).…”

“…Further details of all the tests can be found in Kern et al (2019). The results of the wake steering field tests during the same measurement campaign are reported in Doekemeijer et al (2021).…”

Experimental results of wake steering using fixed angles

“…Finally, there are tests of wake steering at commercial-scale sites. These include tests made using fixed offsets over a fixed sector of wind directions (Ahmad et al (2019), Howland et al (2019)) (in both cases 40-deg sectors are used), and offsets applied using an optimal schedule based on wind directions (Fleming et al (2017b), Fleming et al (2019), Fleming et al (2020), andDoekemeijer et al (2021)).…”