Back to the programme printer.gif Print




Delegates are invited to meet and discuss with the poster presenters in this topic directly after the session 'Aerodynamics and rotor design' taking place on Wednesday, 12 March 2014 at 09:00-10:30. The meet-the-authors will take place in the poster area.

Manhae HAN Mie University, Japan
Co-authors:
Manhae HAN (1) F P Takao MAEDA (1) Yasunari KAMADA (1) Junsuke MURATA (1) Masayuki Endo (1) Toyoharu SUGIMORI (2)
(1) Mie University, Kitaku, Nagoya, Aichi, Japan (2) Chubu Electric Power Corporation, Nagoya, Japan

Printer friendly version: printer.gif Print

Presenter's biography

Biographies are supplied directly by presenters at EWEA 2014 and are published here unedited

Mr. Manhae has been studying Mechanical Engineering in Mie University for 6 years. 3 years ago, he started researching wake of wind turbine in Fluid Engineering Laboratory for Energy and Environment. His research is focused on a wake model of wind turbine. To make a precise wake model he realized he should study turbulence more and decided to study turbulence in Dongguk University in Korea. After coming back to Japan, he restarted researching influences of inflow conditions on wake to construct a wake model.

Abstract

Influences of inflow conditions on wake of horizontal axial wind turbine

Introduction

This paper describes the experimental study of the flow downstream a small horizontal axis wind turbine. Experimental investigations were carried out in a wind tunnel with open circuit test section. Flow fields were measured through the simultaneous use of hot-wire and ultrasonic anemometer. The Influences of inflow conditions were investigated. The obtained results are useful for constructing a wake model with reference to the optimization of arrangement of wind turbines in a wind farm.

Approach

In Europe, there have been considerable researches on wind turbine wake especially in offshore wind farms. As a representative, in ENDOW project [1], databases were compiled from observed data in offshore wind farms. However, in offshore wind farms in which most of the observations were performed, operating conditions of wind turbines were variable in time. Furthermore, many conditions that can influence on wake, such as, wind direction, turbulence intensity, wind shear, stability of atmosphere and vortex scales, are not controllable. Therefore, it is impossible to get data directly from measurements and it needs to statistically process data. Thus, it is necessary to measure distributions of wake in wind tunnel for clarifying inflow conditions, respectively which influence on wake.
The purpose of this paper is experimental investigation of influences of inflow conditions on wake for constructing a wake model to be useful as a reference for numerical analysis or for optimization of arrangement of wind turbines in a wind farm. Main flows with different turbulence intensities, which depend on site and wind direction, were generated through the use of active turbulence grids and the flow fields in wake were measured. There are only a few experiments that flow fields in wake are measured with controlled ambient turbulence intensity. Additionally, by rotating a yaw misalignment angle of the test wind turbine and measuring flow fields in wake, the influences of yawed inflow condition were investigated. This is because wind turbines often operate in yawed inflow condition due to fluctuation of wind direction although wind turbines have yawing systems.


Main body of abstract

Figure 1 shows the experimental setup for flow field measurements in wake. In order to consider influences of turbulence intensities in a wind tunnel, the active turbulence grids were installed and flow fields in wake were measured. By setting yaw misalignment angle of 0, 10, 30[°], the influences of yawed inflow conditions were clarified. The wind tunnel has a 3.6m diameter nozzle and 6.2m length open test section. The flow fields behind the test wind turbine were measured by an X-type hot wire anemometer that has high time resolution and ultrasonic anemometer. The coordinate system in measurements is defined as the x-, y- and z-axes set in the main flow, lateral and vertical directions, respectively. The X-type hot wire probe measured x, y components of velocity and ultrasonic anemometer measured x, y, z components of velocity.



Active Turbulence Grids
In order to generate the different turbulence intensities in the main flow, active turbulence grids were installed in the wind tunnel. They were mounted at 6.2m upstream from the wind tunnel outlet. They consist of small square vanes attached on 56 independent shafts. Rotational angles of the vanes were controlled by separate servomotors. By changing moving patterns, various turbulence intensities in the test section were generated.
The measurements were performed in three different turbulence intensities. The averaged spatial values of turbulence intensities were TIamb=1.4, 8.0, 13.5 [%].
Test Wind Turbine
In this experiment, upwind horizontal axis wind turbine with a rotor diameter D=500 [mm] and hub height H=500 [mm] was used. The blade span is 225mm, the chord length is 122.4mm at r/R=0.2 and 70.6mm at r/R=1.0. The rotational direction of the test wind turbine was clockwise as the test wind turbine was looked at from upstream. The yaw misalignment angle is defined as the angle between the longitudinal direction and rotor axis. It is defined as positive when counter clockwise of rotational axis as the test wind turbine was looked at from above. The yaw misalignment angle of the test wind turbine could be changed in the interval -30~30[°] of yaw misalignment by rotating the basement of the test wind turbine. In order to keep higher optimal tip speed ratio, two-bladed rotor was used. Blades have large chord length for preventing the decrease of aerodynamic performance due to low Reynolds number.
To investigate the operating characteristics of the test wind turbine, power coefficient of the test wind turbine was measured in main wind speed of 7m/s and the averaged spatial value of turbulence intensities TIamb=1.4[%] for 0, 10, 20, 30, -30[°] of yaw misalignment angle. Figure 2 shows the relation between power coefficient and tip speed ratio. In this measurement, the optimal pitch angle was set at 4 [˚], which was measured in prior experiment. The horizontal axis and vertical axis represents tip speed ratio and power coefficient, respectively. In the case of 0[°] of yaw misalignment angle, the maximum power coefficient is 0.30 with tip speed ratio 3.2. The power coefficient decreases with the increase of yaw misalignment angle. However, the optimal tip speed ratio didn’t change with the increase of yaw misalignment angleAll the wake flow fields measurement were performed with the optimal pitch angle 4 [˚] and the optimal tip speed ratio 3.2.




Conclusion

Figure 3 shows velocity distributions in wake for various turbulence intensities. The horizontal axis shows the non-dimensional longitudinal position x/D and the non-dimensional longitudinal velocity UN, which is defined as local longitudinal velocity in wake non-dimensionalized by that measured without the test wind turbine. One division of scale corresponds to UN=1. The vertical axis represents the non-dimensional lateral position y/R.
The velocity deficit area in wake expands almost symmetrically with increase of longitudinal position x/D. The velocity distributions at x/D=0.5 shows that velocity distributions for different turbulence intensity are similar at the just behind the rotor. On the other hand, the velocity distributions at x/D=5 shows the expansion of wake diameter and recovery of wind speed are obviously promoted by higher ambient turbulence intensity. It can be considered that high ambient turbulence stimulates mixture between wake and the main flow.



Figure 4 shows velocity distribution in wake for 0, 10, 30[˚] of yaw misalignment angle in TIamb=13.5 [%]. The definitions of the horizontal and the vertical axis are same as in Figure 3. The velocity distribution at x/D=2 shows that velocity deficit area was deflected to –y direction and the values of wind velocity in wake decrease with increasing of yaw misalignment angle. This is because velocity components in the axial direction decreased and thus resulting in decreasing rotor thrust force comparing to non-yawed condition. It was found that with increasing yaw misalignment angle, due to the decrease of the projected width of the rotor rotational plane on the lateral plane, the width of velocity deficit area was contracted.





Learning objectives
It has been extensive research in the same laboratory, considering the effects of the inflow conditions. Therefore, a wake model considering inflow conditions will be built and validated through the use of numerical analysis and experiment investigation in wind tunnel and field.


References
[1] Rebecca Barthelmie, et. al. ENDOW (Efficient Development of Offshore Wind Farms): Modelling Wake and Boundary Layer Interactions, WIND ENERGY, 2004; 7: 225–245