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    Design optimization of wind turbine blades for reduction of airfoil self-noise.pdf

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    Design optimization of wind turbine blades for reduction of airfoil self-noise.pdf

    Journal of Mechanical Science and Technology 27 2 2013 413420 www.springerlink.com/content/1738-494x DOI 10.1007/s12206-012-1254-1 Design optimization of wind turbine blades for reduction of airfoil self-noise† Seunghoon Lee1, Soogab Lee2,*, Jaeha Ryi3 and Jong-Soo Choi3 1Department of Mechanical and Aerospace Engineering, Seoul National University, Seoul, 151-744, Korea 2Engineering Research Institute, Department of Mechanical and Aerospace Engineering, Seoul National University, Seoul, 151-744, Korea 3Department of Aerospace Engineering, Chungnam National University, Daejeon, 305-764, Korea Manuscript Received May 31, 2012; Revised September 28, 2012; Accepted October 15, 2012 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Abstract To reduce airfoil self-noise from a 10 kW wind turbine, we modified the airfoil shape and planform of a wind turbine blade. To obtain the optimal blade design, we used optimization techniques based on genetic algorithms. The optimized airfoil was first determined based on a section of the rotor blade, and then the optimized blade was designed with this airfoil. The airfoil self-noise from the rotor blades was predicted by using a semi-empirical model. The numerical analysis indicates that the level of the airfoil self-noise from the optimized blade is 2.3 dB lower than that from the baseline blade at the rated wind speed. A wind tunnel experiment was also performed to validate the design optimization. The baseline and optimized rotors were scaled down by a factor of 5.71 for the wind tunnel test. The experimen-tal results showed that airfoil self-noise is reduced by up to 2.6 dB. Keywords Airfoil self-noise; Blade design; Design optimization; Noise reduction; Wind turbine ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 1. Introduction Wind energy is one of the fastest-growing renewable energy resources. Although most wind turbines installed today are large, small wind turbines are also receiving attention because they can supply electricity in off-grid areas and can be in-stalled close to a residence. However, because small wind turbines are generally installed in the vicinity of a dwelling, the noise from the wind turbine can annoy people who live in the surrounding area. Thus, reducing the noise of small wind turbines is important. The aerodynamic noise generated from wind turbine blades, which is the dominant noise source of a typical wind turbine, is divided into two noise sources turbulence ingestion noise and airfoil self-noise [1]. The turbulence ingestion noise is generated as the result of the interaction between atmospheric turbulence and the wind turbine blades, whereas the airfoil self-noise is generated without the existence of any atmos-pheric turbulence. The airfoil self-noise is composed of turbu-lent-boundary-layer trailing edge noise, laminar-boundary-layer vortex shedding noise, separation noise, and trailing edge bluntness noise [2]. Among these noise sources, the tur-bulent-boundary-layer trailing edge noise is the main noise source in typical operating conditions [3]. Accordingly, wind turbine noise can be reduced by controlling the turbulence ingestion noise and the trailing edge noise. However, because the turbulence ingestion noise has little relation to the shape of the wind turbine blade but is instead dependent on the inflow velocity and the turbulence character-istics, reducing the noise levels associated with it is difficult. On the other hand, the trailing edge noise can be reduced by altering the turbulent boundary layer structure or the trailing edge shape. For this reason, several attempts have been made to reduce the trailing edge noise by modifying the airfoil shape or attaching noise reduction materials to the blades [4-6]. How-ever, most of these studies have focused on two-dimensional flow, and only a few studies have practically applied these techniques to the design of wind turbine blades [7, 8]. The purpose of this study is to reduce the airfoil self-noise generated from a 10 kW wind turbine rotor. In this study, the airfoil self-noise is reduced by modifying the airfoil shape and the blade planform, while the operating schedule and the rotor diameter remain fixed. To obtain the optimal designs of the airfoil shape and the blade planform, we use optimization methods that involve genetic algorithms. In designing our optimal blade, the optimized airfoil is first determined based on a section of the baseline blade. The optimal blade is then designed with this optimized airfoil. 2. Airfoil design optimization 2.1 Baseline wind turbine model A 10 kW wind turbine was selected as the baseline wind *Corresponding author. Tel. 82 2 880 7384, Fax. 82 2 876 4360 E-mail address soleesnu.ac.kr † Recommended by Associate Editor Do Hyung Lee KSME the chord length is identical to that of the blade section at r 0.75R. The observer was located upwards from the trailing edge, and the distance from the trailing edge to the observer was 3 m. A semi-empirical model proposed by Brooks, Pope, and Marcolini [2] was used to predict the overall sound pressure level of the trailing edge noise. They performed extensive wind tunnel experiments to measure airfoil self-noise from NACA0012 airfoil models. The semi-empirical model was developed based on the results of these experiments. Accord-ing to [2], the one-third octave band sound pressure level SPL of trailing edge noise can be described by SPL 10SPL 10 SPL 10TENSPL 10log 10 10 10psα 2 where * 51 121StSPL 10log 3Stp ppeM lD A K Krδ     − ∆     * 5 121StSPL 10log 3Sts sseM lD A Krδ    −        * 5222StSPL 10log .St         s seM lD B Krαδ Fig. 1. Rotational speed and power output with respect to wind speed. Fig. 2. Airfoil shape functions. S. Lee et al. / Journal of Mechanical Science and Technology 27 2 2013 413420 415 In Eq. 2, δ*, St, l, D indicate the boundary layer displace-ment thickness, Strouhal number, wing span, and stream-wise noise directivity, respectively. The subscripts p, s, and α represent the pressure side, suction side, and nonzero angle of the attack effect, respectively. Functions A and B define the spectral shapes of the trailing edge noise. St1 and St2 are the peak Strouhal numbers where the trailing edge noise is maximum. K1 , K2, and ∆K1 are empirical constants to adjust the level of trailing edge noise. The definitions of the spectral curves, the peak Strouhal numbers, and the empirical con-stants are described in Ref. [2]. For the directivity function, this model uses a cardioid-type directivity pattern, which is the theoretical directivity for a semi-infinite flat plate. This directivity is based on the as-sumption that the chord length is much larger than the domi-nant acoustic wavelength, which was not satisfied in the pre-sent calculation. However, in the present case, the noise was predicted for an observer normal to the airfoil chord. Accord-ingly, the results would be unaffected by this directivity; the directivity function simply equals one. The displacement thicknesses of the suction and pressure side boundary layers in Eq. 2 were calculated by using XFOIL code [11]. The angle of attack used for the calculation of boundary layer displacement thickness was based on the aerodynamic angle of attack at a zero lift angle. Although the sound pressure level of the airfoil self-noise was reduced by using the optimization procedure, the aerody-namic performance of the modified blade should not be worse than that of the baseline blade. In this optimization procedure, a constraint condition was chosen to not only maintain but also enhance the aerodynamic performance of the optimized airfoil; this condition is shown in Eq. 3. optimized, 4 baseline, 4 160L D L Dα α 3 where L and D are the lift and drag of the airfoil, respectively. The XFOIL code was again used to calculate aerodynamic properties such as lift and drag coefficients [11]. Moreover, the maximum thickness of the modified airfoil, tmax was also subject to a constraint. If the maximum thickness of the optimized airfoil was thicker than that of the baseline airfoil, the possibility of an increase in the blade weight exists. On the other hand, if the maximum thickness was thinner than the baseline, a structural problem may arise in the inboard region. Thus, the constraint condition in this optimization procedure was chosen, as shown in Eq. 4. max max,baselinemax,baseline5 5t tt−− 7a 4 / 4 / ,baseline 105m s m sP P 7b 7 / 7 / ,baseline 105m s m sP P 7c 10 / 10 / ,baseline 105m s m sP P 7d where P is the rotor power. Furthermore, to avoid increasing the blade weight or applied load to the blade root, the chord length and the solidity were selected as constraints, as shown in Eqs. 8 and 9. root root,baselinec c 8 baseline baseline95σ σ σ 9 3.2 Blade optimization result A total of 20000 runs were carried out. The level differ-ences of trailing edge noise between the baseline and modified blades during the optimization procedure are plotted in Fig. 6. The optimum design was obtained in the 13958th run. Fig. 7 shows the chord and twist distributions for the base-line and optimized blades. The twist angle for the optimized blade was increased from that for the baseline blade. The chord length at the root was slightly longer than that of the baseline blade, whereas the chord length at the blade tip was Fig. 5. Overall sound pressure levels of the airfoil self-noise for the baseline and optimized airfoil. The airfoil self-noise is the sum of the trailing edge noise and trailing edge bluntness noise. S. Lee et al. / Journal of Mechanical Science and Technology 27 2 2013 413420 417 shorter than that of the baseline blade. The numerical predictions of the overall sound pressure level for the baseline and optimized wind turbines are plotted in Fig. 8. These predictions include not only trailing edge noise but also trailing edge bluntness noise. The result indi-cates that the optimized wind turbine generated less noise than the baseline wind turbine at most wind speeds. The airfoil self-noise was reduced by 2.3 dB at a wind speed of 10 m/s. At wind speeds less than 5 m/s, little difference was observed between the noise levels of the baseline and optimized blades. However, in this range of wind speeds, the noise level of the airfoil self-noise is small compared with that of typical back-ground noise. Thus, airfoil self-noise reduction at low wind speeds is unnecessary in most situations. In addition, the prediction results show that the trailing edge bluntness noise is negligible compared with the trailing edge noise. However, for the optimized blade, the contribution of the bluntness noise to the overall noise increased as the wind speed increased. 4. Experiments 4.1 Experiment apparatus A wind tunnel experiment was performed to validate the re-sult of the design optimization. The experiment was carried out in a semi-anechoic wind tunnel at Chungnam National University. Fig. 9 shows a photograph of the wind tunnel test system and the semi-anechoic chamber. The wind tunnel has a cross section of 1.8 m 1.8 m and is capable of generating wind speeds of up to 35 m/s. The anechoic chamber has a total volume of 211.9 m3 and a cut-off frequency of 150 Hz, which is far below the frequency of typical airfoil self-noise. To evaluate the turbulence characteristics of the wind tunnel, the turbulence intensity for the wind tunnel was measured by using hot-wire anemometry. The measurement system was composed of a hot-wire anemometry system A.A.Lab.System AN-1003 with a hot-wire probe Dantec 55R01. The turbu-lence intensity was measured at velocities of up to 30 m/s. The measurement results are presented in Table 1. A test system for measuring wind turbine rotor performance was developed and used in this experiment. The rotor per-Fig. 6. Noise level difference between the baseline and modified blades, baseline,10m/s modified,10m/s baseline,7m/s modified,7m/sSPL SPL SPL SPL ;∆ − −L black indicates runs that satisfy the optimization constraints; gray indicates runs that did not satisfy the optimization constraints. Fig. 7. Chord and twist distributions for the baseline and optimized blades. Fig. 8. Predicted overall sound pressure levels for the baseline and optimized wind turbines. The airfoil self-noise is the sum of the trail-ing edge noise and the trailing edge bluntness noise. Fig. 9. Configuration for the small-scale wind turbine rotor test stand in the anechoic wind tunnel. 418 S. Lee et al. / Journal of Mechanical Science and Technology 27 2 2013 413420 formance was recorded by using a PC-based data acquisition system. The experimental data was measured by using the LabVIEW7.1TM software. In the rotor test stand, a rotating balance that consists of a full-bridge strain gage was installed to measure the thrust and the hub moment. The rotor test stand was overspread with a windshield along the direction of the slipstream to minimize the interaction between the shear layer with the supporting structure. A pitot tube was used to meas-ure the wind tunnel velocity. Air temperature, air pressure, and humidity were also recorded during the experiment. The baseline and optimized rotors were scaled down by a factor of 5.71 for the wind tunnel test. The small-scale rotors had a diameter of 1.4 m, and their rotational speeds ranged from 491 RPM to 1473 RPM. By increasing the rotational speed of the small-scale rotor, the tip speed of the model blades was set to be equal to that of the full-size 10 kW wind turbine blades. Since the disk area of the small-scale rotors was smaller than the cross section of the wind tunnel, the in-teraction between the rotor blades and shear layer turbulence was expected to be negligible. For the measurement of trailing edge noise, the boundary layers were tripped with dotted strips to ensure that the bound-ary layers on the blades were fully turbulent. The height of the dotted strip was determined by using the method proposed by Alfredsson and Dahlberg [14]. The ratio of particle height to the transition position can be described as Eq. 10. 1/23/2Re0.3172kxRkx−    10 where Rk is the particle Reynolds number, and x is the transition position where the dotted strips were attached. The particle Reynolds number of 600 was selected in this experi

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