Near-wake behaviour of a utility-scale wind turbine

Abstract

Super-large-scale particle image velocimetry (SLPIV) and the associated flow visualization technique using natural snowfall have been shown to be effective tools to probe the turbulent velocity field and coherent structures around utility-scale wind turbines (Hong et al.Nat. Commun., vol. 5, 2014, article 4216). Here, we present a follow-up study using the data collected during multiple deployments from 2014 to 2016 around the 2.5 MW turbine at the EOLOS field station. These data include SLPIV measurements in the near wake of the turbine in a field of view of 115 m (vertical) $\times$ 66 m (streamwise), and the visualization of tip vortex behaviour near the elevation corresponding to the bottom blade tip over a broad range of turbine operational conditions. The SLPIV measurements provide velocity deficit and turbulent kinetic energy assessments over the entire rotor span. The instantaneous velocity fields from SLPIV indicate the presence of intermittent wake contraction states which are in clear contrast with the expansion states typically associated with wind turbine wakes. These contraction states feature a pronounced upsurge of velocity in the central portion of the wake. The wake velocity ratio $R_{w}$, defined as the ratio of the spatially averaged velocity of the inner wake to that of the outer wake, is introduced to categorize the instantaneous near wake into expansion ($R_{w}<1$) and contraction states ($R_{w}>1$). Based on the $R_{w}$ criterion, the wake contraction occurs 25 % of the time during a 30 min time duration of SLPIV measurements. The contraction states are found to be correlated with the rate of change of blade pitch by examining the distribution and samples of time sequences of wake states with different turbine operation parameters. Moreover, blade pitch change is shown to be strongly correlated to the tower and blade strains measured on the turbine, and the result suggests that the flexing of the turbine tower and the blades could indeed lead to the interaction of the rotor with the turbine wake, causing wake contraction. The visualization of tip vortex behaviour demonstrates the presence of a state of consistent vortex formation as well as various types of disturbed vortex states. The histograms corresponding to the consistent and disturbed states are examined over a number of turbine operation/response parameters, including turbine power and tower strain as well as the fluctuation of these quantities, with different conditional sampling restrictions. This analysis establishes a clear statistical correspondence between these turbine parameters and tip vortex behaviours under different turbine operation conditions, which is further substantiated by examining samples of time series of these turbine parameters and tip vortex patterns. This study not only offers benchmark datasets for comparison with the-state-of-the-art numerical simulation, laboratory and field measurements, but also sheds light on understanding wake characteristics and the downstream development of the wake, turbine performance and regulation, as well as developing novel turbine or wind farm control strategies.

Snow-powered research on utility-scale wind turbine flows

“…Besides providing mean flow and turbulence statistics for validating high-fidelity numerical models, the investigation has discovered several near-wake phenomena that are unique for utility-scale turbines which will be the focus of the review here. For detailed information regarding this study, please check Dasari et al [21]. As shown in Figure 7, an examination of the instantaneous velocity fields revealed two distinct near-wake states, referred to as wake expansion state and contraction state hereafter.…”

“…Here we focus on the significant implications and physical insights obtained from such deployments. For information regarding the technical details and data processing involved in these findings, please refer to our individual research papers [21,[22][23][24][25]. Using the SLPIV technique, we conducted flow measurements in the region within 0.4 upwind of the turbine at the tower plane with a field of view spanning from the ground to the elevation slightly above the hub height of the turbine.…”

“…Note that for a relatively small field of view on the order of 10 m, individual snow particles, distinguishable from the snow particle images, contribute the signal in the SLPIV, and the velocity field around individual tip vortex cores can be resolved as shown in the Figure 4a from Hong et al [16]. For a large field of view on the order of 100 m (Figure 4b), the correlation used in SLPIV relies on the movement of large-scale patterns formed by the voids and clusters of snow particles, rather than individual snow particles, as described in detail by Dasari et al [21]. For the measurements at the plane normal to the flow direction, additional image enhancement techniques are applied to snow particle images for robust extraction of the snow voids associated with helical blade tip vortices ( Figure 3f).…”

“…These four heights were specially selected to match the turbine rotor top, rotor hub, rotor bottom and standard 10 m height. The site and instrumentation are described in more detail in Hong et al [16], Toloui et al [18] and Dasari et al [21].…”

Investigation of the near-wake behaviour of a utility-scale wind turbine

“…Nemes et al [11] and Heisel et al [12] then further applied it to atmospheric boundary layer studies. Dasari et al [13] expanded the capabilities of the technique to a field of view > 120 m to quantify the near-wake velocity deficit and coherent blade tip vortex behaviour. Particularly, the work was the first to observe the occurrence of increased wake velocity indicative of wake contraction behind a field-scale turbine associated with changes in blade pitch.…”