1. Introduction
The use of wind power has been developing rapidly all over the world during the past few decades. The aerodynamic performance of wind turbines is a key element in wind power production. Power prediction and operation monitoring of wind turbines require accurate prediction of wind speed in front of wind turbines. Usually, met mast or ground LIDAR is used to measure the wind speed. However, the number of met masts in a wind farm is limited due to high installation costs. Normally, only one or two met masts are built for one wind farm, which is not enough for accurate wind prediction of every wind turbine present in the wind farm. Nacelle LIDAR has been proposed for power measurement in recent years [
1,
2]. This technology is still under development and not widely applied. In practical engineering scenarios, an anemometer mounted on the wind turbine nacelle, i.e., a nacelle anemometer, is still the most often used instrument for wind prediction as it is cheap and easy to setup.
For an upwind horizontal axis wind turbine (HAWT), which at present is the main type of wind turbine in large-scale wind farms, the nacelle anemometer is located downstream of the wind turbine rotor. The flow measured by the anemometer is usually different from the flow in front of the wind turbine due to the disturbance and obstruction caused by blade rotation and nacelle geometry, respectively. Thus, the wind speed measured by the nacelle anemometer has to be adjusted according to the upstream wind speed. In other words, a transfer function between the nacelle wind speed and the incoming wind speed, i.e., a nacelle transfer function (NTF), is needed. At present, the most commonly used adjustment method uses curve fitting of average wind speed based on met mast measurements. According to the International Electrotechnical Commission (IEC) standard 61400-12-2:2013 [
3], the NTF can be generated by curve fitting between the averaged wind speeds measured by a met mast and a nacelle anemometer. This method is widely used since it is simple and easy to implement in practical engineering applications. One of its drawback is the self-consistency check criterion of IEC standard 61400-12-2, which is difficult to satisfy. Low quality measurements often result in failure to meet this criterion, which occurs frequently according to Kirshna et al. [
4]. Another drawback of this method is that the time scale is usually too large to be used in wind turbine control because the physical correlation between the nacelle wind and the freestream wind cannot be obtained using this data-driven NTF method. Significant challenges still exist in understanding the underlying physics using the available data [
5].
The NTF is strongly related to the wake flow of wind turbine, which has been investigated extensively during the past decades. Vermeer et al. [
6] presented a detailed review of research carried out on wind turbine wake aerodynamics during the last century. Usually, the wake flow can be divided into near wake region and far wake region. According to Vermeer and Sørensen [
6], the former region is the area just behind the rotor, approximately up to one rotor diameter (D). In this region, the influence of rotor geometry, stalled flow, three dimensional (three-dimensional) effects, as well as the tip and root vortices, are significantly high. The far wake region is beyond the near wake, where the effects of these factors are less significant. Far wake has been modeled successfully using wake models, such as Jensen model [
7], Larsen model [
8], Ainslie model [
9], etc., which are usually simple and fast. On the other hand, it is difficult to build simplified models for the near wake, as it is strongly related to the blade aerodynamics. Most of the existing research on near wake focused on the tip and root vortices, as well as the stalled flow. Whale et al. [
10] investigated the vortex wake of a two-blade model wind turbine using particle image velocimetry (PIV) measurements and free-wake modeling. The tip vortex pitch is modelled accurately in the simulations. It was found that the helical vortex wake was insensitive to blade chord Reynolds number when the tip speed ratio was kept constant. Massouh and Dovrev [
11] also investigated the near wake of a small model wind turbine with three blades using both PIV and hot wire anemometry (HWA) measurements. The results revealed the expansion of tip vortices in a radial direction. The tip vortices are the only vortices that can be observed farther than 2D distance downstream. Micallef et al. [
12] investigated the tip vortex of the MEXICO rotor in both axial and yaw cases. The experimental results established the generation mechanisms of the tip vorticity and showed three-dimensional flow behavior under yaw, which was not fully captured by the previously mentioned free-wake vortex models.
Compared to the tip vortices, the root flow did not receive significant research attention due to lower power production in the blade root region. However, the root flow is important as it affects the near wake and nacelle wind speed measurement. Several experiments have been performed to study the root flow in scaled wind turbine models. In Whale’s experiments [
10], it was found that the root vortex had the same sign as the tip vortex, and it merged with the tip vortex at an approximate distance of 1.0D behind the rotor plane. As the rotor diameter of the model was small (175 mm), it is possible that the interaction between the tip vortex and root vortex may not be the same for large-scale wind turbines. Ebert and Wood [
13,
14] performed a series of wind tunnel measurements on the near wake of a model-scale wind turbine. For high tip velocity ratios, the hub vortex became a cylindrical vortex sheet over a short distance downstream. The downstream axial vorticity was supposed to be formed from the circumferential vorticity in the boundary layer upstream of the blades. In experiments presented by Massouh and Dovrev [
11], the reversal zone behind the hub was significantly expanded due to the interaction between rotor and the hub boundary layer. There was an increase of circulation near the hub over a smaller range of
r, indicating a compact hub vortex. Hu et al. [
15,
16] investigated the near wake characteristics of wind turbine models in an atmospheric boundary layer using PIV measurements. The evolution of vortex structure in the near wake was correlated to the dynamic load variation of wind turbine. Zhang et al. [
17] measured the structure of near wake flow downwind of a model wind turbine in a neutral boundary layer using PIV. It was found that the hubroot vortices were significant within 1.5D distance downstream, and dissipated faster than the tip vortices. Several experiments using PIV measurements to investigate the near wake flow properties were presented in [
18,
19,
20,
21]. However, the wind tunnel experiments suffered from scaling issues.
Numerical simulations have been employed to study the near wake flow. In Blade Element Momentum (BEM) methods, a loss factor is added to consider the influence of root vortex. However, the flow in the root region is fully three-dimensional and viscous, which cannot be effectively modelled with the BEM methods. Advanced methods with high credibility, such as computational fluid dynamic (CFD), are needed. Sanderse et al. [
22] reviewed the state-of-the-art numerical calculation of wind turbine wake aerodynamics. They pointed out that the actuator approach seems more suitable for the far wake modelling. For the near wake, more validations of the actuator methods to model the effect of the blade geometry are required. Porté-Agel et al. [
23,
24] investigated the wake flow after a miniature wind turbine in a neutral turbulent boundary-layer, using large-eddy simulation (LES) coupled with actuator–disk (AD) model with rotation (ADM-R) and without rotation (ADM-NR). The ADM-R results showed better agreement with the experimental data than the ADM-NR results in the near-wake region. Lignarolo et al. [
25] validated the AD method using wind tunnel experiments. It was found that the AD type methods often failed at modeling the effects of flow turbulence due to the absence of blade tip vortices and their breakdown. Sorensen et al. [
26] simulated the flow around the MEXICO wind turbine using Reynolds-averaged Navier–Stokes (RANS) simulations. Excellent agreement between computational results and experimental data for three velocity components were obtained within one rotor diameter downstream of the rotor. Nacelle was not modelled, which was found to have substantial influence under yaw conditions. O’Brien et al. [
27] compared the performance of three turbulence models using simulations of the near wake of a three-bladed HAWT model. The wind turbine was modeled with full geometry. The highest velocity deficit was consistently located behind the nacelle and tower which introduced considerable recirculating flow into the near wake.
Most of the above-mentioned literature focused on flow structure of the tip and root vortices in near wake. Only a few papers investigated the flow around the nacelle that is very close to the rotor. Masson and Ameur studied the nacelle flow. Masson and Smaïli [
28] studied the turbulent flow around a wind turbine nacelle using RANS simulations. The AD method was used to approximately model the wind turbine rotor. It was shown that the numerical method was useful for placing nacelle anemometers to reduce the influence of high spatial variation and fluctuations in atmospheric turbulence on the nacelle wind speed. Ameur et al. [
29] investigated the wind-rotor/nacelle interaction using both two-dimensional (two-dimensional) and three-dimensional RANS simulations. The three-dimensional simulation results showed better agreement with the measurement data than the two-dimensional results. Ameur and Masson [
30] compared three types of AD methods. The actuator line approach provided the best results compared to the actuator disk considering the NTF curve. As the wind turbine was simulated by an AD type method, and steady simulations were performed, only an average wind speed was obtained. Zahle and Sørensen [
31] investigated the nacelle wind speed for a small-scale wind turbine using RANS simulations. Full geometry of the wind turbine rotor was modeled. The authors observed that, at low wind speeds, steady simulations overestimated the wind speed reduction on the nacelle compared to the unsteady simulations. At high wind speeds, the situation was reversed. The inflow velocity was constant during the simulations.
Based on the literature survey, it can be concluded that a comprehensive analysis of the characteristics of the nacelle wind speed, especially for unstable inflow, is needed. Enhanced understanding of the time-varying characteristics of nacelle wind speed and correlation with the unsteady inflow are very critical for construction of an accurate NTF. In order to address these points, this paper investigates the flow around the nacelle region of a HAWT using CFD simulations with the rotor geometry fully modeled. Both stable inflow and dynamic inflow varying in the form of simplified functions are investigated. The paper is organized as follows:
Section 2 describes the geometry model and computational methods. In
Section 3, the characteristics of nacelle wind speed are analyzed in both time and frequency domains.
Section 4 presents the conclusions drawn in this paper.