**2. Some limitations of the usual prediction methods to represent wind turbines noise generation and propagation**

Environmental sound pressure levels related to stationary sources are usually predicted as prescribed by the ISO Standard 9613-2. It is not only a standardized method of calculation, but it has been for a long time the recommended one in the European Union [2]. This is a strong argument at some developing countries. Convincing the decision-makers about the need of developing another prediction method to achieve more reliable results in the case of wind turbines is not an easy task.

This section aims to point out the main hypothesis of the ISO Standard 9613-2 [3] and to discuss their applicability to wind turbine noise.

#### **2.1 The origin of the calculation method**

In 1981, CONCAWE (a group of oil companies, aiming toward the research on the conservation of water and air quality in Europe) hired C. J. Manning for developing a prediction model of environmental sound pressure levels [4]. Some novel prediction methods were inspired on it, as the ISO Standard 9613-2 was.

According to CONCAWE, the environmental sound pressure levels at remote places due to a noise source can be obtained by solving the following expression:

$$L\_p = L\_W + D - K \tag{1}$$

Where Lp is the sound pressure level in the short time for the octave band *i*, LW is the acoustic power level for the octave band *i*, D is the correction due to directivity of the source, and K is the sum of the attenuation terms.

The ISO Standard 9613-2 general expression is just the same:

$$L\_{p^i} = L\_{Wi} + D - A\_i \tag{2}$$

The definitions of Eq. (1) are valid for Eq. (2). Ai are the attenuation terms (atmosphere absorption, ground absorption, presence of obstacles or noise barriers, etc.). The subscript *i* refers to the values for the octave band *i*.

#### *Prediction of Environmental Sound Pressure Levels from Wind Farms: A Simple but Accurate… DOI: http://dx.doi.org/10.5772/intechopen.103159*

Both calculation methods assume the divergence law to be quadratics, thus the emitter is supposed to be a point source. Also, both calculation methods promote their application by frequency octave bands. Nevertheless, if there is not enough information to work by bands, ISO Standard 9613-2 will accept calculating in A-weighted sound pressure levels using all formulae and coefficients corresponding to the octave band centered at 500 Hz. If the acoustic emissions have high energy content in low frequencies, this way of calculating will cause a great underestimation of immission sound pressure levels.

CONCAWE's model uses the meteorological categories proposed by Parkin and Scholes instead of the currently preferred Pasquill-Gifford ones. ISO Standard 9613-2 does not consider calculating differences due to different meteorological conditions when the main calculation hypothesis is satisfied: wind speed between 1 and 5 m/s at a height between 3 and 11 m above the ground and averaged over a short period of time or moderate temperature inversion with its base at ground level. These conditions are not always met when the source is a wind turbine.

In this century, it has been verified that the differences between environmental sound pressure levels predicted by ISO Standard 9613-2 and those that do occur due to the operation of wind turbines would be very important: underestimations of 15 dB or more have been reported during the occurrence of certain combination of environmental conditions [5, 6].

Then, ISO Standard 9613-2 calculation method has been submitted to a deeper analysis.

#### **2.2 Understanding the ISO Standard 9613-2 limitations**

Aerodynamic noise generation during operation of wind turbines is inherent to them in nature: the major acoustic emissions from large wind turbines are caused by the interaction between the air flow and the blades. The acoustic emissions occur all along each blade, most of them at low frequencies. Then, the height of the noise source is from about 40–130 m above the ground. The incident wind speed largely varies between these two heights, so that the wind turbine becomes a heterogeneous and complex sound emission source.

There are some limitations for the use of ISO Standard 9613-2 to predict environmental sound pressure levels due to large size wind turbines [1]. Some of the general ones are the following:


Some experimental findings also refer to better results when not considering ground attenuation effects during propagation [8].

But there are also two of the major assumptions that are at the very beginning of the conceptual framework of environmental acoustics that are not fulfilled by the physic/fluid mechanic phenomena involved in the aerodynamic sound generation from wind turbines [9]:


These are thought to be the root causes for both CONCAWE and ISO methods not to being appropriate for predicting the environmental sound pressure levels related to wind turbines' operation, as they cannot describe the main involved phenomena on a right way [1, 9–11].

### **3. Improving the prediction method**

In order to improve the current prediction method, we have proposed several modifications. We have focused on the noise generation phenomena, but we have also worked on two other points: the explicit consideration of the atmospheric stability condition and the dissipative nature of the main phenomena during propagation.

#### **3.1 Wind velocity at the hub height: Considering atmospheric stability class**

The wind velocity is usually measured at 10 m height above the ground. One of the main causes of underestimating the environmental sound pressure levels is related to calculating the wind speed at the hub height using a neutral atmospheric profile with basis on its value at 10 m. To avoid this problem, the atmospheric stability class (according to Pasquill-Gifford) has to be explicitly taken into account for this calculation. The atmospheric stability does not only influence the wind speed profile but also the turbulence intensity and, therefore, the acoustic energy depletion law.

If a stable or thermal inversion atmospheric condition occurs, not including it in the prediction method will conduct to:

*Prediction of Environmental Sound Pressure Levels from Wind Farms: A Simple but Accurate… DOI: http://dx.doi.org/10.5772/intechopen.103159*


**Table 1.**

*Values of* m *according to Pasquill-Gifford stability class.*


If the atmospheric thermic profile is not known, the wind speed at the hub height should be obtained by supposing a strong atmospheric stability profile (class F according to Pasquill-Gifford), to be in the most demanding hypothesis for protecting the health of noise receivers.

Then, the wind speed at the hub height should be met by converting the measured wind speed data—that are usually taken at 10 m over the ground—using a proper method.

Using the logarithmic profile approach for wind velocity (Eq. (3)) is better than using the potential profile approach (Eq. (4)), even though there are good experimental values for the potential approach. Indeed, since several authors refer that the usual values of *m* may lead to underestimation of the acoustic power, using the experimental values met by Van den Berg [6] is strongly recommended when using the potential approach, in order to remain on the safe side (see **Table 1**).

*Logarithmic profile approach:*

$$
\mu(h\_{hub}) = \frac{u\_\*}{k} \left[ \ln \left( \frac{h\_{hub}}{z\_0} \right) - \nu\_m \left( \frac{h\_{hub}}{L\_\*} \right) \right] \tag{3}
$$

Where:

u(hhub) wind velocity at hub height u\* friction velocity k von Karman's constant z0 roughness length ψ<sup>m</sup> thermal stratification function L\* Monin-Obukhov length *Potential profile approach:*

$$u(h\_{hub}) = u\_{ref} \left(\frac{h\_{hub}}{h\_{ref}}\right)^m \tag{4}$$

Where:

uhub wind velocity at hub height hhub uref measured wind velocity at a reference height href

m coefficient depending on Pasquill-Gifford class of atmospheric stability (see **Table 1**)

The calculation procedure that we recommend to meet the wind velocity at hhub height, taking into account its value at any other height href, is as follows [10–12]:


Please note:


*Prediction of Environmental Sound Pressure Levels from Wind Farms: A Simple but Accurate… DOI: http://dx.doi.org/10.5772/intechopen.103159*


#### **Table 2.**

*Reference spectrum of acoustic power of 2 MW wind turbines in octave bands (based on [13]).*

Wind turbine manufacturers often provide tables or graphs relating the wind velocity at 10 m in height (u10) to the acoustic power level (in dBA) emitted by the wind turbine in neutral atmosphere conditions. However, providing emission spectra in frequency bands is not so common. If this information is not available, a reference spectrum should be used, e.g., spectrum in **Table 2**.

**Table 2** (based on [13]) presents the values to be added arithmetically to the acoustic power level of the wind turbine (LWA) to obtain the acoustic power levels in each octave band, also in dBA (LW,f,A).

#### **3.2 Modeling noise generation phenomena**

We aim to obtain the sound pressure levels due to the operation of a typical threeblade wind turbine, at a generic receiver point located downwind at a distance *d*.

Aerodynamic noise is generated by the interaction of wind with the blades of the machine. Most of the acoustic emissions occur in low frequencies, so the acoustic print of wind turbines can be found at large distances from the sources, making the problem more complex to manage.

#### *3.2.1 General background*

There are three main processes causing the fluctuation of the pressure field and then the acoustic emissions [14]:


These phenomena are related to three different geometric scales [14, 15]:

1.Macroscale: it is the scale related to the largest eddies. If U, L, and T are the scales of velocity, length, and time associated to these eddies, the Reynolds number of the biggest eddies is the same as for the main flow.


The turbulent cascade hypothesis is then to be considered. According to it, the larger eddies are dissipating into smaller scale eddies with increased kinetic energy. However, there is a length scale at which the power transfer to a smaller eddies scale is not possible. At this point, the turbulent cascade ends and the energy from the last eddies is finally dissipated. The smallest eddies scale is the Kolmogorov scale; the socalled Kolmogorov frequency or dissipation frequency is the generation frequency of these smallest eddies [15]. According to their frequency and energy, the released eddies are able to produce audible phenomena, i.e., they can become noise sources (**Figure 2**).

The passage of the blades ahead the tower imposes a fluctuation of the sound level pressures emitted by the abovementioned phenomena. It results in an amplitudemodulated noise, called the "blade passage noise." It has a double nature, one related to the flow and one related to the geometry of the source. The modulation is the most related process to annoyance in wind turbine noise. This process is not modeled in detail: the informed sound pressure levels are the highest of those corresponding to the fluctuation.

#### *3.2.2 Basic concepts concerning wind turbines*

A first approach to describe the wind turbines operation is to model the rotor as an active disk, which absorbs kinetic energy from the incoming wind, resulting in a reduction in the flow speed downstream of the turbine.

If v1 is the incoming velocity and v2 is the outcoming velocity, the velocity induction coefficient "*a*" is defined according to Eq. (5):

$$v\_2 = v\_1 \ (\text{1-2a})\tag{5}$$

**Figure 2.** *Atmospheric conditions for propagation. From: [15].* *Prediction of Environmental Sound Pressure Levels from Wind Farms: A Simple but Accurate… DOI: http://dx.doi.org/10.5772/intechopen.103159*

**Figure 3.** *Drag FD and lift FL efforts over the blade (from [15]).*

Applying mass and energy balances to the incoming flow, and supposing an adiabatic and incompressible flow, the maximum amount of power absorbed by the disk is:

$$W = \frac{1}{4}\rho A (v\_1 + v\_2) \left(v\_1^2 - v\_2^2\right) \tag{6}$$

In Eq. (6), ρ is the air mass density, and A is the swept area or rotor area.

The power absorbed is maximized when *a* = 1/3. Then, Eq. (7) is the expression of the so-called "Betz power":

$$\mathcal{W}\_{\text{Max}} = \frac{16}{27} \bullet \left(\frac{1}{2} \rho A v\_1^3\right) \tag{7}$$

The wind turbine operates at its maximum power for each wind velocity, while the wind velocity is under the rate value. As consequence of the power exchange process between the wind and the machine, the flow downwind the rotor rotates around the turbine axis.

The force over the blade, consequence of the interaction between the flow and the blade, is split in two components: the drag effort (D) and the lift one (L) (**Figure 3**). The magnitude of these components strongly depends on the angle of attack (α), which is the angle between the chord of the blade and the incoming flow relative to the blade. When the drag component increases, the noise generation increases too. This usually occurs when the angle of attack α increases.

#### *3.2.3 Theory of turbulence*

There are several analytical expressions to describe the universal shape of the turbulence spectrum. One of that, the Von Karman's spectrum, expresses the spectrum as function of a nondimensional ratio built with turbulence integral length scale Lu and the main flow speed *v* (Eq. (8)):

$$X = \frac{L\_u f}{v} \tag{8}$$

According to Von Karman spectrum, we propose to estimate the energy content in a third-octave band centered at a frequency *f* according to Eq. (9), in which σ is the standard deviation of the flow speed:

$$S = 4 \, X \, \frac{\left(2^{1/6} - 2^{-1/6}\right) \sigma^2}{\left(1 + 70, 8 \, X^2\right)^{5/6}} \tag{9}$$

#### *3.2.4 Emitted acoustic power level*

To meet the acoustic power level, we accept that each blade is composed of a group of discrete thin elements or slices. Each one would be sufficiently thin to be thought as a noise point source. Then, the total acoustic power emitted by one blade element should be obtained as the superposition of the acoustic power emitted by the incoming flow (LW,IF) and the trailing edge (LW,TE) as following (Eq. (10)):

$$L\_W = 10\log\left(10^{\frac{L\_{W,W}}{10}} + 10^{\frac{L\_{W,TE}}{10}}\right) \tag{10}$$

The incoming flow noise is the result of the fluctuation of the lift effort on the blade, which makes the drag effort to fluctuate. We propose estimate of the pressure field fluctuation using McLaurin series, where first-order terms are related to the turbulent fluctuation.

The length scale of interest, for the incoming turbulence, is similar to the length of the blade chord, which corresponds to the length scale of the eddies that produce the greatest amplitude fluctuation on the pressure field. Van den Berg proposes to use a length scale equal to 60% of the blade chord for this length [8]. Smaller eddies would produce lower fluctuations on the pressure field. Then, the shape of the spectrum of the incoming edge noise, associated to eddies with length scale larger than the blade chord, will be the same as Von Karman's spectrum.

The trailing edge noise is due to the turbulent boundary layer separation over the blade. The length scale of interest in this case is about the boundary layer thickness.

We built a routine for obtaining the emitted acoustic power level by third-band octave. Its aim is to obtain the predicted sound pressure levels at a point placed at 100 m downwind of the wind turbine tower. We discretize the blade in infinitesimal length blade elements. The coordinates of each slice in every moment could be thought as [x(t), y(t), z (t)]. Then, the propagation into the first 100 m from the tower axis is done assuming that each one of the blade elements is a nonstationary noise point source (**Figure 4**).

For the propagation from each blade element to the receiver location, our routine only considers the geometrical divergence and the atmospheric sound absorption as indicated at ISO Standard 9613-1 [16]. The output of this routine is the input for the propagation module [10, 11].

#### **3.3 Modeling noise propagation**

For computing sound propagation, the input data are the results of the computing at 100 m far from the tower of the wind turbine. Not only geometric divergence but also atmospheric absorption and turbulent dissipation are considered; both phenomena depend on the frequency. The final sound pressure levels at a given reception point are obtained by superposing the sound pressure levels due to different wind

*Prediction of Environmental Sound Pressure Levels from Wind Farms: A Simple but Accurate… DOI: http://dx.doi.org/10.5772/intechopen.103159*

turbines operation. All computations are done in octave bands, and the final results are expressed as LAeq values [11].

#### *3.3.1 Atmospheric conditions and audibility of acoustic emissions*

The analysis of the evolution of eddies generated due to wind turbine operation requires the use of the cascade process as it is usual in turbulent flow studies. According to it, the larger eddies are melting into smaller ones, increasing its kinetic energy. At some point, small eddies cannot continue to transfer power to smaller ones; so, they dissipate their remaining energy, thus ending the cascade process. The scale of these last eddies is the order of the Kolmogorov's scale.

Under atmospheric instability condition, the turbulence is very high and the eddies scale interval is broad; the cascade process is very efficient to dissipate the produced turbulence. For distances greater than the one at which that dissipation occurs, it shall be assumed that the flow conditions are the same as upstream the wind turbine. The ratio between the current wind velocity up and downstream the machine tends to 1 for greater distances, and the difference between them is practically negligible at a distance of about 6 or 7 rotor diameters downstream of the wind turbine (i.e., about 600 m).

In strong atmospheric instability conditions, the prior distance is the shortest one to fully carry out the whole energy cascade process. For any other atmospheric conditions, the dissipation process occurs in greater distances.

Under strong atmospheric stability conditions (i.e., class "F" according to Pasquill-Gilfford stability classes), the effect of turbulence should be negligible. The only mechanism that affects the energy depletion process in any frequency band—in addition to the geometric divergence or attenuation by distance—is the atmospheric absorption.

#### *3.3.2 The atmospheric absorption*

The effect of atmospheric absorption can be considered as the depletion of the acoustic energy of a wave over a given distance, due to energy loss caused by the

viscosity of the propagation medium (currently, the atmosphere). To estimate the effect of the atmospheric absorption, the computation method of the ISO Standard 9613-1 was used [16].

The attenuation due to atmospheric absorption in dB of a pure tone with frequency *f*, from its initial level at a distance *d=0* to its level at *d*, can be obtained according to Eq. (11):

$$Abs = \Gamma\_i(f) \cdot \frac{d}{1000} \tag{11}$$

Where Γ<sup>i</sup> is the atmospheric absorption in the *i*-th frequency band in dB/km, and *d* is the distance from the base in m. The absorption coefficient Γ<sup>i</sup> is a function of the relaxation frequencies from oxygen and nitrogen [16].

The generation and propagation phenomena of eddies can be described from a wave approach. Then, close to the source, the sound pressure levels should be estimated considering energy depletion by geometric divergence (*Div*) and by atmospheric absorption as shown in Eq. (12).

$$L\_p = L\_W - \text{Div} - \Gamma\_i(f) \cdot \frac{d}{1000} \tag{12}$$

The threshold of perception at each frequency band should be another criterion for determining the distance upon which the sound is still audible. Hearing threshold levels were retrieved from ISO Standard 226 [17].

#### *3.3.3 Geometric divergence*

For the depletion of sound pressure levels due to distance, the adjustment is focused on the exponent (*n*) of the divergence law, which is neither squared nor linear as many measured sound pressure levels close to operating wind farms have shown.

As one of the main hypotheses of linear acoustics was broken (nonviscous effect), we intend not to be mandatory for *n* to be constant across every one of the considered third-octave bands: the exponents may be related to the distance scale at which eddies are expected to dissipate all their turbulence energy. Then:

$$Div = 10\log\left(\frac{d}{d\_0}\right)^{n\left(\left.f\_i\right|\right)}\tag{13}$$

Here, *n* = *n*(fi, d, u) depends on the central frequency fi of each octave band.

For the calculations of geometric divergence, the turbulent cascade approach is taken into account (**Figure 2**). The released eddies can propagate along great distances while the turbulent cascade occurs [15]. These distances are related to a certain energy level and a length scale. They are also closely related to atmospheric stability.

We calculated the length scale where the turbulent cascade is expected to end by considering it to depend on the incoming wind velocity and the frequency of the released eddies. This is based on prior consideration of the atmospheric stability during the calculation of noise emissions [10, 11].

Different sets of *n* values were achieved by fitting measured data. At first, we consider only the dependence of *n* related to the frequency. Then, we explored the dependences on the distance *d*, the wind speed *u,* and the atmospheric stability. The

*Prediction of Environmental Sound Pressure Levels from Wind Farms: A Simple but Accurate… DOI: http://dx.doi.org/10.5772/intechopen.103159*


**Table 3.**

*Divergence coefficient "*n*" values for octave bands, according to the wind speed* u *and the distance* d*.*

best set of *n* values was selected by the application of the statistic Friedman test and the comparison of residues (differences) between measured to predicted sound pressure levels expressed as A-weighted broadband levels.

Field data were taken at a height of 1.2 m with class 1 sound pressure meters, close to three different wind farms over plain terrain; the distances of measurements covered from 100 m to about 2000 m.

The best set of values was found to be the one obtained for *n* = *n*(f, d, u). The explicit consideration of atmospheric stability in the propagation term did not result in an improvement in the simulated sound pressure levels.

The values of n(f, d, u) are given in octave bands according to whether the calculation distances are closer or further than 750 m and that the wind speed at the hub height is less or greater or equal to than 6.5 m/s (**Table 3**).

### **4. Validation of the model**

#### **4.1 Field measurements**

Several sound pressure level measurement campaigns were conducted at three different wind farms with large wind turbines (rate power of 1.8 MW), covering several operating conditions.

Sound pressure level records were taken at 1.2 m height, simultaneously with records of wind speed and direction at 10 m height. In addition, the records of wind speed and direction were obtained from the wind farm anemometer, located at 66 m high and close to the turbines. To carry out the measurements, we used two sound level meters class 1 (Brüel and Kjaer 2250 and Casella 633C), an anemometer (Extech EN-300), a GPS, and two computers.

The measurement points covered four different geographical locations:


A set of 59 measurements was used during the calibration and validation processes. The main findings showed that the model gave a good approach for the environmental sound pressure levels related to the operation of wind turbines for wind speeds over 5 m/s at the hub height.

In order to validate the model, another set of field data was used. It was another set of data of 49 cases from 10 wind farms in different locations in Uruguay:


Some adjustments were needed for improving the prediction of noise propagation from wind farms built on uneven terrain.
