1. sports
2. wakeboarding

Project Report
EFP07-II
Noise emission from wind turbines in wake
Performed for Danish Energy Authority
AV 110/11
Project no.: A580841
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31 March 2011
DELTA
Venlighedsvej 4
2970 Hørsholm
Denmark
Tel. +45 72 19 40 00
Fax +45 72 19 40 01
www.delta.dk
VAT No. 12275110
The report must not be reproduced, except in full, without the written approval of DELTA.
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Title
EFP07-II
Noise emission from wind turbines in wake
Journal no.
AV 110/11
Project no.
A580841
Our ref.
KDM/ilk
Client
Danish Energy Authority
Amaliegade 44
1256 Copenhagen K
Client ref.
Contract no.: 33033-0191
Preface
This report concludes the EFP07-II project “Noise emission from wind turbines in wake”. The
project is funded by the Danish Energy Authority under contract number 33033-0191. Supplementary funding to the project is given by Siemens Wind Power, Vestas Wind Systems, LM
Glasfiber, Statkraft, Statoil Hydro and Vattenfall.
The project has been carried out in cooperation between DELTA, Risø DTU, DONG Energy
and EMD International.
This report is prepared by Kaj Dam Madsen (DELTA) with Birger Plovsing (DELTA),
Thomas Sørensen (EMD International), Helge Aagaard Madsen and Franck Bertagnolio (Risø
DTU) as contributing authors.
DELTA, 31 March 2011
Kaj Dam Madsen
Acoustics
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Contents
1.
Summary.......................................................................................................................4
1.1 Resumé (in Danish) ................................................................................................6
2.
Introduction ..................................................................................................................8
3.
Wake and noise generation from wind turbines .......................................................9
4.
DAN AERO MW experiments ..................................................................................13
5.
Measurement system for acoustic far field measurements.....................................15
5.1 Directional characteristics for the parabolic measurement system.......................16
5.2 PMMS gain characterisation.................................................................................20
5.3 Measurement control and analysis........................................................................22
5.4 Focussing the PMMS on different blade sections.................................................23
5.5 General data presentation......................................................................................25
6.
Measurement campaigns and results .......................................................................29
6.1 Results from surface pressure microphones for different inflow angles ..............30
6.2 Results from measurements with and without wake ............................................33
6.2.1 Results from surface pressure microphones with and without wake ..........33
6.2.2 Results from far field measurements with and without wake.....................40
6.2.3 Conclusions on wake influence on noise emission.....................................46
6.3 Results for up- and downwards movement of blade.............................................47
7.
Investigation of WAKE effects for wind farms .......................................................54
7.1 Introduction...........................................................................................................54
7.2 Theoretical background ........................................................................................54
7.3 Methodology.........................................................................................................55
7.4 Wake model ..........................................................................................................55
7.5 Noise propagation model ......................................................................................56
7.6 Wind turbine characteristics .................................................................................57
7.7 Calculation principle and limitations....................................................................58
7.8 Calculation setup...................................................................................................59
7.9 Calculations ..........................................................................................................61
7.10Results...................................................................................................................62
7.10.1
The row scenario ..........................................................................62
7.10.2
Square layout................................................................................73
7.11Conclusion on the model study.............................................................................81
8.
Conclusions .................................................................................................................83
9.
References ...................................................................................................................85
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1.
Summary
When installing wind turbines in clusters or wind farms the inflow conditions to the wind
turbines can be disturbed due to wake effects from other wind turbines. The effect of wake
on noise generation from wind turbines are described in this report.
The work is based on measurements carried out on a M80 2 MW wind turbine. To investigate the relationship between the far field noise levels and the surface pressure and inflow
angles measured by sensors on an instrumented wind turbine blade, a parabolic measurement system (PMMS) was designed and tested as part of this project.
Based on the measurement results obtained with surface pressure sensors and results from
the far field measurements using the PMMS it is concluded that:
The variance of surface pressure at the trailing edge (TE) agrees with the theory with regard to variation of pressure spectra with varying inflow angle (AoA) to the blade. Low
frequency TE surface pressure increases with increased AoA and high frequency surface
pressure decreases with increased AoA.
It seems that the TE surface pressure remains almost unaltered during wake operation
Results from the surface transducers at the leading edge (LE) and the inflow angles determined from the pitot tube indicates that the inflow at LE is more turbulent in wake for the
same AoA and with a low frequency characteristic, thereby giving rise to more low frequency noise generated during wake operation.
The far field measurements supports that on one hand there will be produced relative more
low frequency noise due to a turbulent inflow to the blade and on the other hand there will
be produced less noise in the broader frequency range/high frequency range due to a lower
inflow angle caused by the wind deficit in the wake. The net effect of wake on the total
noise level is unresolved
As a secondary result it is seen that noise observed from a position on the ground is related
to directional effects of the noise radiated from the wind turbine blade. For an observer
position close to the ground directly downwind of the wind turbine the major part of the
noise is received from the part of the rotor plane with downwards movement of the blades.
Although it has not been possible to get a precise estimation of the effect on the noise generation for a given wake degree, a study of wake effects for different layout of wind farms
due to the general wind speed reduction in wake has been made using the WindPRO
Nord2000 program. The basic assumption for this study has been that a turbine operating
in wake radiates the same noise as a turbine with free inflow at the same power output.
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From this study it is seen the largest reduction of noise at the receptors is when the closest
turbines are in a deep wake, whereas if the deep wake is elsewhere in the wind farm the
noise reduction is less. For different wind farm layout it is concluded that the combined
wake influence on the noise impact is a complex function of wind direction, wind speed
and wind farm geometry. It may cause deviations from the undisturbed noise impact of
several dB, both up and down, and the effect may change rapidly with small changes in
wind direction.
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1.1
Resumé (in Danish)
Ved opsætning af vindmøller i grupper eller i vindmølleparker kan vindens inflow til
vindmøllerne blive forstyrret på grund af wake fra andre vindmøller. I denne rapport undersøges betydningen af wake for støjgenereringen fra vindmøller på baggrund af feltmålinger.
Det præsenterede arbejde er baseret på målinger foretaget på en M80 2 MW vindmølle.
For at undersøge sammenhængen mellem støjen i fjernfeltet fra vindmøllen og fladetryk
og inflowvinkler målt med sensorer monteret på én af testmøllens vinger, er der opbygget
et parabolmålesystem (PMMS) som en del af dette projekt.
Ud fra målingerne foretaget på den instrumenterede vinge og fjernfeltsmålingerne foretaget med parabolmålesystemet er følgende konkluderet:

De variationer af fladetryk, der er målt på vingens bagkant stemmer overens med teorien med hensyn til variation i forhold til inflow vinkel på vingen (AoA). Den
lavfrekvente del af fladetrykket på bagkanten stiger ved øget AoA og den højfrekvente
del falder med øget AoA.

Tilsyneladende er fladetrykket på vingens bagkant ikke påvirket væsentligt af wake.

Målinger af fladetryk på vingens forkant sammenholdt med pitotrørsmålinger af inflowvinkel indikerer, at inflow til vingens forkant er mere turbulent i wake for den
samme inflowvinkel og desuden har en lavfrekvent karakteristik med deraf følgende
udvikling af mere lavfrekvent støj under drift i wake.

Fjernfeltsmålingerne understøtter, at der på den ene side genereres relativ mere
lavfrekvent støj som følge af turbulent inflow til vingen i wake og på den anden side
genereres mindre støj i et bredere frekvensområde som følge af den lavere inflowvinkel forårsaget af det vind-deficit, der er i wake. Nettoeffekten af wake på det totale
støjniveau er ikke bestemt.
Som et sekundært resultat af målingerne ses, at direktivitetseffekter for den støj, der udsendes fra vindmøllens vinger har betydning for støjen målt ved jorden. F.eks. vil den
væsentligste del af støjen for et observationspunkt 2 m over jorden i medvindsretningen fra
vindmøllen blive modtaget fra den del af rotorplanet, hvor vingerne bevæger sig nedad.
På trods af, at det ikke på baggrund af fjernfeltsmålingerne har været muligt at foretage en
præcis estimering af ændringer i støjgenerering for en given grad af wake, er der foretaget
et studie af betydningen af wake effekter for forskellige layout af vindmølleparker. Studiet
er baseret på den generelle vindreduktion som følge af wake og som forudsætning antages,
at en vindmølle i wake udsender den samme støj som en vindmølle i frit inflow ved den
samme effektproduktion. Beregningerne er baseret på WindPRO Nord2000.
Ud fra dette studie ses, at den største støjreduktion ved modtagerpositioner omkring
vindmølleparken fås når de nærmeste vindmøller er i dyb wake, mens dyb wake andre
steder i vindmølleparken har mindre betydning. For forskellige layout af vindmølleparker
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konkluderes, at betydningen af wake i forhold til ændringer i støjbilledet i typiske modtagerpositioner omkring vindmølleparkerne er en kompleks funktion af vindretning,
vindhastighed og park layout. I forhold til støj beregnet for uforstyrret inflow til vindmøllerne kan variationen i wake være flere dB og effekten kan ændres hurtigt selv for en lille
ændring i vindretning.
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2.
Introduction
Noise from wind turbines is often considered as a major factor when planning new wind
farms to ensure that complaints from people living at residents close to the wind farms can
be avoided. To help this, noise planning tools based on advanced noise propagation models are now available and validated [9], [10].
The noise source descriptions for these predictions are often based on standardized measurement results from free standing wind turbines with regular and unhindered inflow conditions. In a wind farm where the turbines influence each others through the turbulent
wake downwind of the wind turbines these source descriptions are expected to be inadequate. This motivates the full scale measurement setup that is described in this report
where investigation of the influence of wake effects on noise emission from the wind turbines is made.
The presented work was carried out as a supplement to the research project “Experimental
Rotor- and Airfoil Aerodynamics on MW Wind Turbines” (DAN-AERO MW), lead by
Risø DTU [1]. In the main project an extensive experimental work has been carried out to
provide full scale results for validation of advanced numerical models used for prediction
of noise radiation from wind turbine blades under different inflow conditions
The aim of the WAKE project “Noise from wind turbines in wake” is:

Correlation of the surface pressure variation measured on a fully instrumented wind
turbine blade with far field acoustic noise measurements for the wind turbine in operation.

Design of an acoustic parabola measurement system for measurements in the far field
of the wind turbine and evaluation of its usability compared to more expensive microphone array systems.

Gain of improved knowledge of the noise emission at low, medium and high frequencies from wind turbines in wake, with the objective to improve noise prediction and
optimization of wind farms.

Demonstration of the effect of wake in WindPRO and eventual implementation of improved wake models in the software.
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3.
Wake and noise generation from wind turbines
When installing wind turbines in clusters or wind farms several considerations with regard
to the difference in loading of the turbine and turbine blades and reduction in power production due to wake from nearby wind turbines are made. In [2] the most important wake
mechanisms are treated with the aim of improvement of the theoretical models used for
simulation of wind turbine loads and operation. Most of the mechanisms important for
loads and power production also have an impact on the noise generation from wind turbines in wake. The most important flow mechanisms of the wake from an upstream operating turbine are as described in [2]:

Wind velocity deficit due to extraction of power by the upstream turbine

Meandering of the velocity deficit due to the big scales in the ambient turbulence causing apparent turbulence
Increased turbulence (added turbulence) inside the wake is due to brake down of tip vortices and the increased turbulence mixing due to the velocity gradient from the velocity deficit. Important parameters for the depth of the velocity deficit and the increased turbulence
level inside the wake is the turbine spacing, the ambient turbulence and the mean wind
speed. The influence of the first two parameters is illustrated in Figure 1 and Figure 2. Decreasing the spacing between the turbines increases the velocity deficit and the turbulence
level whereas increased ambient turbulence has the opposite influence.
To investigate experimentally these flow mechanisms in details a test turbine in a small
wind farm has been selected for a measurement campaign. The test turbine used for this
project is situated in a small wind farm at Tjæreborg close to the west coast of Jutland
about 1 km from the North Sea; see Figure 3. In total the wind farm has 8 turbines placed
in two rows which give different single and multiple wake situations with the closest spacing about 3.5 turbine rotor diameters. In Figure 4 a model calculating wake situations for
different wind directions is shown.
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Figure 1
Comparison of non-dimensional axial velocity results for the NM80 turbine at 8 m/s,
downstream positions of 3D, 6D and 10D (from left to right in the figure) and for 5%, 10%
and 15% ambient turbulence (from top to bottom). Computations with the engineering
model DWM and the CFD code ACL. Figure is taken from [2].
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Figure 2
Comparison of the total turbulence intensity for the NM80 turbine at 8 m/s, downstream
positions of 3D, 6D and 10D (from left to right in the figure) and for 5%, 10% and 15%
ambient turbulence (from top to bottom). Computations with the engineering model DWM
and the CFD code ACL. Figure is taken from [2].
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Figure 3
Map of the test site. The position of the NM80 used for the test shown 85.
(Google maps).
Figure 4
Wake model predicting grade of wake for the wind turbine with instrumentation. This example shows a wake of 66.5 % for a wind direction at 195 degree.
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4.
DAN AERO MW experiments
As part of the DAN AERO MW project [1] pressure and inflow measurements were made
on one of the blades on the NM80 2 MW wind turbine.
For the experiment a new blade was manufactured for the NM80 80 m diameter turbine
and during the production process, equipment for measuring surface pressure profiles and
inflow at four radial stations was placed inside the blade, see Figure 5. Additionally, the
most outboard blade section was instrumented with around 50 microphones to measure
high frequency surface pressure spectra, Figure 6. The data from these sensors are used for
determination of position of transition and for aeroacoustic characterization if inflow noise
and trailing edge noise from the turbulent boundary layer. Local inflow was measured at
four radial positions with five hole pitot tubes.
Figure 5
Sketch of the instrumented LM38.8 blade [1].
Besides the pressure, inflow and microphone sensors a considerable number of strain
gauges and accelerometers mounted on the blades, the shaft and the tower were monitored.
The inflow angle measurements describing the wake from the other turbines are of particular interest for this project and comparison with the far field acoustic measurements and
also the high frequency pressure fluctuations measured using surface microphones.
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Figure 6
Photo of microphones installed about 1 mm below the blade surface at the outboard section at radius 37 m for high frequency surface pressure measurements. [1]
In the project Risø DTU developed a software tool making it possible to get an overview
of the large amount of data from all the sensors and sort them appropriately for specific
analysis purposes. In Figure 7 the principle behind the tool is illustrated. As an example
the raw data can be analysed so that the pressure spectra can be calculated for a specific
part of the rotor or time window (as an example for the rotor in a horizontal position) making it possible to cut the part of the data corresponding to the area that is covered by the
acoustic far field measurements using the parabolic system. Also the data can be sorted by
the measured inflow angle (Angle of Attack, AoA) locally on the blade as this is one of the
main parameters of importance for the noise radiation.
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Figure 7
An illustration of the principle for the analysis tool developed to sort and analyse the data
from the sensors installed in the blade during the measurement campaign. This makes it
possible to cut the part of the data that corresponds to the area that is covered by the
acoustic far field measurements using the parabolic system.
5.
Measurement system for acoustic far field measurements
The far field noise measurements are based on a parabolic microphone measurement system (PMMS) shown in Figure 8. This measurement system was chosen for this project
from time- and economical considerations as an appropriate alternative to a more extensive measurement system based on microphone array techniques [4].
The parabolic reflector with diameter 2.4 m is mounted on a trailer with hydraulic height
and position adjustments making it easy and fast to set up the PMMS and change the focus
point. The PMMS is equipped with a telescopic sight which is used to locate the desired
measurement spots on the wind turbine blade. The sight is adjusted for the present measurement situation and used together with an acoustic sight facility.
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Figure 8
Parabolic Microphone Measurement System (PMMS) used for the far field noise measurements on the wind turbine (Pictures from the test site in Tjæreborg).
5.1
Directional characteristics for the parabolic measurement system
The parabolic microphone measurement system is based on the properties of a parabolic
reflector. The parabolic reflector amplifies the sound coming at normal incidence thus
suppressing the sound coming from the sides. This makes the PMMS useful where directivity for focused measurements is needed.
The directivity of a parabola is dependent on its physical size. Generally a parabola has a
small aperture angle at high frequencies while it becomes larger with decreasing frequency. The lower frequency limit is set by the diameter of the dish relative to a desired aperture angle. In this project, it was chosen to try out a larger dish having a diameter of 2.4 m
instead of a present dish of 1.8 m available from previous experiments. Figure 9 shows the
directivity of each dish size when simulated as circular plane pistons. The magnitudes are
scaled to the same level at 0°.
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400 Hz
90
D 1.8m
D 2.4m
85
Magnitude [dB]
80
75
70
65
60
55
-50
-40
-30
-20
-10
0
10
Angle []
20
30
40
50
Figure 9
Simulated directivity of parabolic dish with diameter 1.8 m and 2.4 m at 400 Hz.
The parabola is simplified to a plane circular piston in this simulation. Therefore the separate curves are not fully representative of the true directivity, but the difference between
the two curves is expected to be valid. It can be seen, that the directivity becomes better at
low frequencies (400 Hz) when using the larger dish meaning that the PMMS with the
larger dish will be able to focus more precise at the desired point at the wind turbine blade.
An enhancement to the PMMS is made by using a cardioid microphone placed in the focus
point of the parabolic reflector pointing towards the dish. The cardioid microphone that is
of the type DPA 4011-TL suppresses the direct sound on the PMMS and ensures that
mainly the normal incidence reflections on the dish will be measured thereby minimizing
interference patterns.
A test of the PMMS directionality characteristics were made using a loudspeaker as the
noise source and adjusting the parabolic dish from on axis at 0° to 45° off axis in steps 5°.
The setup used is similar to the setup shown in Figure 13. The measured directivity is
shown in Figure 10 and illustrates that the useful frequency range for the PMMS is from
approx. 400 Hz and upwards in frequency. Directivity increases with frequency.
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Directivity of Parabolic Measurement System - Normalized to On-axis Response
On-axis
10
1°
2°
3°
0
4°
Magnitude [dB]
5°
6°
-10
8°
10°
15°
-20
20°
25°
30°
-30
35°
40°
45°
-40
50°
55°
60°
-50
100
125
160
200
250
315
400
500
630
800
1000 1250 1600 2000 2500 3150 4000 5000 6300 8000 10000
Frequency [Hz] - 1/3 octave
Figure 10
Directivity for the PMMS with a 2.4 m dish and a cardioid microphone type DPA 4011TL.
Figure 11 shows the aperture angles of the PMMS related to the 1/3-octave filter band
damping. The aperture angle equals two times the off-axis angle from Figure 10 and is
used to determine the lower frequency limit for a given measurement situation. For example, the PMMS has an average aperture angle of ~ 3° related to a 3 dB damping if the frequency range of the blade noise is expected to reach from 1 kHz-4 kHz. The diameter of
the measurement area for the PMMS will then with an aperture angle of 3° be approximately 5 m at a distance of 100 m as illustrated in Figure 12.
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Aperture Angles Related to the 1/3-octave Filter Band Damping
20
18
Aperture Angle [deg.]
16
14
12
-1 dB
-3 dB
-5 dB
-10 dB
10
8
6
4
2
0
400
500
630
800
1000
1250
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6300
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Frequency [Hz] - 1/3 octave
Figure 11
Aperture angles of the PMMS.
Ø5m
-3 dB
3°
100 m
Figure 12
Focus area of the PMMS with an aperture angle of 3° for the frequency range 1 kHz-4 kHz
and a distance of 100 m.
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5.2
PMMS gain characterisation
Another relevant characteristic value for the PMMS is the gain of the measurement system. A calibration of the PMMS with regard to gain has been carried out using a normal
“plate measurement” procedure according to [5]. Two setups were used to test the gain.
One setup was with a loudspeaker as the noise source as seen in Figure 13 and one setup
was in the field during measurements on the actual wind turbine as seen in Figure 14.
Figure 13
Gain test setup for short range test on loudspeaker. Microphone on plate used for reference is seen to the right of the parabolic system.
Figure 14
Test setup at the turbine in Tjæreborg. The ground plate with the microphone used as reference is shown to the right of the parabolic system.
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The gain was determined as the difference between the measured signals on the parabolic
microphone and the microphone on the ground board where the ground board signal was
subtracted 6 dB due to the total reflection on the board. In Figure 15 the two determined
gain-curves are shown.
Gain determined for the PPMS
40
35
30
Gain [dB]
25
20
Loudspeaker test
Wind turbine test
15
10
5
10000
8000
6300
5000
4000
3150
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1250
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500
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315
250
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0
Frequency [Hz] - 1/3-octave
Figure 15
Gain determined for the PMMS from a short range loudspeaker test and a field test at the
wind turbine.
The loudspeaker gain curve is similar to the wind turbine gain curve below 2500 Hz. The
difference below 300 Hz is related to higher wind noise in the DPA microphone during the
measurements at the wind turbine compared to the loudspeaker test.
The loudspeaker curve has a roll off at high frequencies above 2500 Hz compared to the
wind turbine gain curve, which is related to the measurement setup where the limited distance from the loudspeaker to the PMMS makes it impossible to generate an ideal plane
wave on the reflector. This will cause phase differences at high frequencies from different
parts of the reflector at high frequencies.
The measurements are also affected by the directivity of the loudspeaker used for the test.
The crossover point between the two drivers in the applied loudspeaker is placed at
~5300 Hz. At this frequency and neighbour frequencies the directivity will be especially
pronounced. This probably causes the small dip at 5 kHz at the DPA curve.
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5.3
Measurement control and analysis
The measured acoustic signal from the PMMS has to be synchronized with blade positions
and turbine operation. To do this a LabVIEW based multi channel system has been build
for this project. The system is capable of measuring 4 acoustic inputs (parabolic microphone, +6 dB ground board measurement and 2 optional acoustic inputs), 3 trigger inputs
(one trigger for each blade passage to define the relevant time analysis window for a blade
passage) and 5 additional inputs with wind turbine parameters (power, wind speed etc.)
In Figure 16 a screenshot from the system is shown. The time signal with analysis time
windows (in colour) for each blade passage is shown in the upper right part of the screen.
Below this the different blade passages for the specific measurement is presented separately for each blade cut from the trigger selections.
Figure 16
Screenshot of program used to control the measurements and perform the analysis. Coloured trigger windows for each blade passage of the parabolic focus area are shown together with corresponding 1/3-octave spectra for a number of passages.
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The program facilitates both on line analysis with audio playback and reanalysis from data
streamed to disk. The latter makes it possible to reanalyze measurements with different
trigger parameters and time windows.
All measurement data from the campaign are available as on line processed 1/3-octave
spectra and as raw data
5.4
Focussing the PMMS on different blade sections
For each measurement in the far field both a measurement with a fixed focus of the parabolic system as well as a plate measurement according to [8] was made. In Figure 17 the
different focus areas for the PMMS are shown with used nomenclature.
The focus area for the PMMS always has its centre on the blade in its horizontal position
as illustrated in Figure 18 with the focus areas shown on the blade during upwards movement.
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Area between the two outer pitot tubes
OT – Upwards movement of blade
NT – Downwards movement of blade
Area with pitot tube
(close to microphones)
OT – Upwards movement of blade
NT – Downwards movement of blade
Tip
OT – Upwards movement of blade
NT – Downwards movement of blade
Figure 17
The different focus areas for the PMMS during measurement.
The focus area always has its centre on the blade in its horizontal position either during
downwards or upwards movement.
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Tdown
Tup
OP
OT
OM
Figure 18
Sketch showing the focus areas OT, OP and OM for the PMMS and the time windows used
for analysis of each blade passage – Tdown amd Tup.
5.5
General data presentation
To get an impression of the character of data available from the far field measurements
some examples of data are presented below.
In Figure 19 the acoustic signal for the PMMS is shown for a 30 sec period. The trigger
signal from blade 1 is seen marked as red vertical lines.
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Figure 19
Acoustic signal from the PMMS for a 30 sec period with the trigger signal from blade 1
marked with vertical red lines.
The analysis is made for each blade passage using a time window defined from trigger 1 as
illustrated in Figure 18. The turbine rotates with a period of approximately 3.75 sec per
rotation and the analysis time window is chosen from 0.9 to 1 second for the individual
analysis. Based on the trigger signal the analysis time window is chosen and defined for
the three blades as seen in Figure 20 with one colour for each blade analysis time window.
Figure 20
Analysis time windows defined for each blade passage based on trigger signals. Red is
blade 1, yellow is blade 2 and green is blade 3.
In Figure 21 the selected cuts in the recordings are shown sorted for each blade before
elimination of measurement periods disturbed due to background noise or stopping of the
turbine. In Figure 22 the corresponding average 1/3-octave spectra is shown for each blade
with the indication of +/- one standard deviation. It is seen that fair measurements are
achieved above 100 Hz for this situation.
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72.5
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Time
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0.95
45
0
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0.5
Time
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0
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Time
0.75
0.95
Figure 21
Time traces for the chosen time window sorted for each blade. Blade 1 is to the left,
blade 2 in the middle and blade 3 is to the right.
Average spectra per blade
Sound pressure level, dB re. 20 uPa
90
Blade 1
Blade 2
Blade 3
80
70
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50
40
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12500
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Frequency, Hz
Figure 22
Third octave frequency spectra shown separately for the 3 blades. +/- one standard deviation is marked with vertical bars.
For synchronization of the PMMS measurements with the measurements carried out by
Risø DTU using the surface microphones, a trigger signal from the Risø DTU measurement system was recorded by one of the PMMS trigger channels. In Figure 23 the PMMS
signal, the trigger signal for blade 1 (red) and the trigger signal from the surface microphones (green) are shown. The measurements from the surface microphones were record-
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ed by the Risø system in 10 sec periods corresponding to approx. 2.6 rotations of the
blade.
Figure 23
Plot of PMMS acoustic signal, trigger signal from blade 1 passage (red) and signal from
the Risø DTU system (green) indicating the periods with recording of signals from the surface transducers on the blade.
Besides the acoustic signal from the PMMS the acoustic signal from the microphone
placed on the plate (used for calibration and check of the measurements) was recorded. In
Figure 24 both acoustic signals are shown with the signal from the plate microphone
shown in red. It is clearly seen that the plate measurement does not separate the contributions from the different blades or the contributions from different parts of the blades. Also
it is seen that the PMMS amplifies the acoustic signal considerably.
Figure 24
Acoustic signals from PMMS(white) and the plate microphone (red).
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6.
Measurement campaigns and results
In the main DAN AERO MW project a very extensive measurement program was carried
out. In total 11 measurement campaigns were carried out covering many different wind
conditions such as free inflow or wake operation.
The acoustic far field measurements were carried out as an add-on to the main measurement campaign and took part on selected measurement days where operating settings of
the wind turbine facilitated far field noise measurements.
The far field measurements were made on the dates listed below:
16 July 2009
14 August 2009
1 September 2009
11 September 2009
22 measurement sessions
4 measurement sessions
28 measurement sessions
11 measurement sessions
A total of 55 measurement sessions were carried out during these days.
The acoustic far field measurements included measurements with the variation of the following parameters related to operation of the wind turbine, meteorological conditions and
focussing of the parabola:
-
Wind speed
-
Wind direction; from no to partial and full wake over the rotor plane
-
Pitch angle of blade
-
Yaw of the turbine relative to wind direction
-
Focus area for the parabola on the blade (different positions in up- and downside
of the blade plane)
Some of the parameters mentioned were controllable but important parameters as wind
speed and direction obviously were not. Especially the wind direction governing the wake
situation was challenging for the recording of data for comparison of results for situations
with and without wake.
From the variety of different measurement situations a number of cases are presented in
the following. It is chosen to present analysis of:

Situations with and without wake

Comparison of measurement for upwards and downwards movement of the blade
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6.1
Results from surface pressure microphones for different inflow angles
Before any comparison of results with and without wake are carried out a study of the surface pressure on the blade for different inflow angles to the blade is made to illustrate general frequency characteristics. In general all frequency plots based on surface pressure
measurements are in the following plotted as Power Spectral Density (PSD) frequency
spectra.
In Figure 25 the inflow angle also denoted AoA (Angle of Attack) is illustrated. For investigation of differences at different azimuth sections the rotor plane data are for some of the
following analysis averaged for 6 evenly distributed azimuth sections of the rotor plane as
illustrated in Figure 25. Using these section average values comparison can be made with
the far field measurements.
AoA
Figure 25
Illustration of inflow angle and sectioning of the rotor plane in 6 evenly distributed azimuth sections. The inflow angle is denoted AoA (Angle of Attack).
In Figure 26 calculated trailing edge (TE) surface pressure spectra for different inflow angles (Angle of attack; AoA) are shown based on a CFD/TNO model [1], [3]. It is seen that
the low frequency pressure (below 400-900 Hz) is increased by increased AoA (wind
speed) and the high frequency pressure is decreased by increased AoA.
In Figure 27 comparable spectra are shown for experiments performed on a blade section
in a wind tunnel and the same characteristics are seen except that the crossover frequency
is higher (about 1000 Hz) in the wind tunnel experiments.
In Figure 28 TE surface pressure spectra from measurements on the blade at site in Tjæreborg for a period without wake are shown as a function of AoA. The field results are very
similar to the predicted results except that the crossover frequency is at about 300 Hz
where the theoretical frequency is between 400 and 900 Hz. This is probably due to the
inflow turbulence to the rotor.
In Figure 29 leading edge (LE) surface pressure spectra from measurements on the blade
at site in Tjæreborg for a period without wake are shown as function of AoA. The frequen-
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cy characteristic for the LE pressure spectra is exact opposite to the TE surface pressure.
The low frequency LE pressure (below 600 Hz) decreases with increased AoA and the
high frequency pressure increases by increased AoA.
Figure 26
Theoretical spectra for blade surface pressure at trailing edge (TE) as a function of inflow
angle of attack (AoA).
Figure 27
Spectra for surface pressure at trailing edge (TE) as function of inflow angle of attack
(AoA) measured on a blade section in a wind tunnel [1].
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Figure 28
Spectra for surface pressure on blade in situ at trailing edge (TE) as function of inflow
angle of attack (AoA) for a period without wake.
Figure 29
Spectra for surface pressure on blade in situ at leading edge (LE) as function of inflow
angle of attack (AoA) for a period without wake.
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6.2
Results from measurements with and without wake
From the measurement database periods with and without wake have been investigated
with regard to the blade surface pressures and the far field acoustic noise. To make a proper comparison it is important that the other variables influencing the noise generation are
the same for the periods of comparison. The accomplishment of this has not been easy due
the tight measurement campaign where different parameters are varied also due to the lack
of controllability of the wind speed and wind direction.
6.2.1
Results from surface pressure microphones with and without wake
On 1 September a period without wake was followed by a period with partial and full
wake on the rotor plane and results from the surface microphones are available for the full
period. The wind speed at hub height during these measurements was approx. 13 m/s.
The data are analyzed separate for the different azimuth angles of the blade position in the
rotor plane as illustrated in Figure 25.
In Figure 30 surface pressure spectra for TE are shown for the 6 azimuth sections for the
period without wake. In Figure 31 the corresponding spectra are shown for a period with
half wake (Wake on the part of the rotor plane in the upside). Both situations are for data
obtained with an AoA between 0 and 3°.
A tendency is seen that for the no wake situation the high frequency TE pressure is higher
during downwards movement. Also it is seen that the TE high frequency pressure during
upwards movement is increased in the wake situation compared to the no wake situation
(red, yellow and turquoise). The TE high frequency pressure on the downside is unaltered
between the wake and no wake situation. This indicates that the high frequency TE pressure is increased slightly in wake for the same AoA.
In Figure 32 and Figure 33 spectra for LE surface pressure for the no wake and half wake
situation are shown for comparable AoA. The major difference is seen in the low frequency range below 1000 Hz where the wake situation raises the pressure for the upwards
movement (red, yellow and turquoise) probably due to the higher degree of inflow turbulence. The pressure at higher frequencies is almost unaltered.
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Figure 30
TE surface spectra for period without wake averaged separately for 6 azimuth sections on
rotor plane.
Figure 31
TE surface spectra for period with half wake (wake on up side) averaged separately for 6
azimuth sections on rotor plane.
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Figure 32
LE surface spectra for period with no wake averaged separately for 6 azimuth sections on
rotor plane.
Figure 33
LE surface spectra for period with half wake (wake on up side) averaged separately for 6
azimuth sections on rotor plane.
In Figure 34 and Figure 35 the measured LE and TE surface pressure spectra are binned
together for different inflow angles, AoA, instead of the azimuth averaging. Lines represent the no wake situations and circles wake situations. Line and circle colours relate to the
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same scale for AoA. In Figure 36 and Figure 37 similar spectra are shown plotted for different classes of wind turbine power production.
Figure 34
LE surface pressure spectra for period without wake and with half wake (wake on up side)
averaged separately for different inflow angles.
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Figure 35
TE surface pressure spectra for period without wake and with half wake (wake on up side)
averaged separately for different inflow angles.
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Figure 36
LE surface pressure spectra for period without wake and with half wake (wake on up side)
averaged separately for different classes of wind turbine power production.
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Figure 37
TE surface pressure spectra for period without wake and with half wake (wake on up side)
averaged separately for different classes of wind turbine power production.
From Figure 34 and Figure 36 it is seen that the leading edge pressure energy is higher for
the wake situation probably related to inflow turbulence. It is also seen that the spectra only varies little with varying power and more with AoA. From Figure 35 and Figure 37 it is
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seen that the trailing edge pressure hardly varies with wake or power but is dependent of
the inflow angle, AoA. The latter is according to the theory.
Another representation of differences in the low frequency range regarding noise generation parameters for wake and no wake situations is given in Figure 38 where the PSD frequency spectra of inflow angle are shown for a wake and a no wake situation. It is seen
that the turbulence in the flow direction (variations of inflow angle mainly influenced by
the turbulence component in the wind direction) is considerably larger in the wake situation compared to the no wake situation.
Figure 38
PSD frequency spectra of inflow angle during wake and no wake operation.
6.2.2
Results from far field measurements with and without wake
Far field measurements on 1 September at high wind speeds were made during a period
with half wake (wake on rotor upwards side). On the 11 September comparable measurements without wake were made at lower wind speeds. The wind speed for the wake measurements was approx. 14 m/s at hub height and for the no wake measurements approx. 7
m/s at hub height.
Apart from the wind speed difference there was also a difference in configuration of the
instrumented blade (Blade 1) on the two measurement days. On the 1 September a special
high speed pitot tube was mounted near the tip region causing a lot of excessive noise. The
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frequency spectra for measurements on the 1 September with focus on the NT region are
shown in Figure 39 where blade 1 is seen to generate excessive noise due to the pitot tube
compared to blade 2 and 3. On 11 September this pitot tube was dismounted but experiments with tape on the leading edge were taking place still giving some raise in noise from
blade 1. The NT frequency spectra for the 11 September are seen in Figure 40.
To overcome the differences in configuration on the instrumented blade (Blade 1) the
comparisons were made for blade 2 instead.
Focus on blade tip mowind downwards - NT
1/9 at 13.44 - pitch minus 1 - wind speed 13 m/s
Blade 1
Blade 2
Blade 3
Sound pressure level, dB 20 uPa
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Frequency, Hz
Figure 39
Frequency spectra for the 3 blades during measurements on 1 September with focus NT.
Excessive noise from special pitot tube mounted on blade 1 this day is seen. Vertical bars
indicating +/- one standard deviation.
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Focus on blade tip mowind downwards - NT
11/9 at 14.07 - pitch minus 1 - wind speed 7 m/s
Sound pressure level, dB 20 uPa
80
1.blade
2.blade
3.blade
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Frequency, Hz
Figure 40
Frequency spectra for the three blades during measurements on 11 September with focus
NT. Vertical bars indicating +/- one standard deviation.
In Figure 41 to Figure 44 the comparisons for the focus areas OM, OT, NT and OP on
blade 2 are shown.
From Figure 41 it is seen that the spectra for the “wake” and “no wake” situations are almost identical for the frequency range 400-4000 Hz although the wind speed for the two
situations are differing with highest wind speeds during measurements with wake. It is also seen that the low frequency noise is higher for the wake situation compared to the no
wake situation.
The same picture is seen for the other focus areas presented in Figure 42 to Figure 44. This
supports the expected effect of wake which on the one hand will produce relative more
low frequency noise due to a turbulent inflow to the blade and on the other hand will produce less noise in the broader frequency range/high frequency range due to a lower inflow
angle caused by the lower wind speed in the wake.
It should be emphasized though that the PMMS only gives precise precision/focus above
approx. 300 Hz and has better and better precision/focus with increasing frequency.
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OM Blade 2
Wake at 14 m/s (1/9 13.37) and no wake at 7 m/s (11/9 14.35) - pitch minus 1
80
70
Leq (dB) re 20 uPa
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Frequency, Hz
Blade 2 no wake
Blade 2 wake
Figure 41
Plot of wake/no wake situations for OM pitch -1 (wake at 14 m/s and no wake at 7 m/s).
OT Blade 2
Wake at 14 m/s (1/9 13.25) and no wake at 7 m/s (11/9 14.25) - pitch minus1
80
70
Leq (dB) re 20 uPa
60
50
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Frequency, Hz
Blade 2 no wake
Blade 2 wake
Figure 42
Plot of wake/no wake situations for OT pitch -1(wake at 14 m/s and no wake at 7 m/s).
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NT Blade 2
Wake at 14 m/s (1/9 13.44) and no wake at 7 m/s (11/9 14.07) - pitch minus -1
80
70
Leq (dB) re 20 uPa
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Frequency, Hz
Blade 2 no wake
Blade 2 wake
Figure 43
Plot of wake/no wake situations for NT pitch -1 (wake at 14 m/s and no wake at 7 m/s).
OP Blade 2
Wake at 13 m/s (1/9 13.32) and no wake at 7 m/s (11/9 14.30) - pitch minus 1
80
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Leq (dB) re 20 uPa
60
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Frequency
Blade 2 no wake
Blade 2 wake
Figure 44
Plot of wake/no wake situations for OP pitch -1 (wake at 14 m/s and no wake at 7 m/s).
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The previous plots from the far field measurements are representative for a full passage of
the blade through the focus area of the PMMS taken as an average of 0.95-1 sec. To see if
it is possible to evaluate the frequency characteristics of leading edge noise (LE) and trailing edge noise (TE) from the PMMS far field measurements, additional analysis have been
made using another gating of the analysis window and shorter time window. In this way
the assumed TE and LE noise spectra have been made for the wake and no wake situation
and the results are shown in Figure 45 and Figure 46. The vertical bars represent +/- one
standard deviation.
Blade 2 -Average spectra OP - 11 September 14.30 no Wake
Sound pressure level, dB re 20 uPa
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0 - 0.25 sec
0.7 - 0.95 sec
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Frequency, Hz
Figure 45
Frequency spectra for a no wake situation representing noise from leading edge (black)
and trailing edge (green) as observed from the PMMS far field measurement. The vertical
bars represent +/- one standard deviation
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Blade 2 - Average spectra OP - 1 September 13.32 in Wake
Sound pressure level, dB re 20 uPa
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0 - 0.25 sec
0.7 - 0.95 sec
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Frequency, Hz
Figure 46
Frequency spectra for a wake situation representing noise from leading edge (black) and
trailing edge (green) as observed from the PMMS far field measurement. The vertical bars
represent +/- one standard deviation.
Due to the limited focus of the PMMS at lower frequencies it is seen that below 400 Hz no
differences are seen in the spectra. Above this frequency it is seen that the assumed inlet
spectra for both wake and no wake situations have higher values than the outlet spectra.
6.2.3
Conclusions on wake influence on noise emission
Based on the measurement results obtained with surface pressure sensors and results from
the far field measurements using the PMMS the following conclusions can be made:

The variance of surface pressure at the trailing edge (TE) agrees with the theory with
regard to variation of pressure spectra with varying inflow angle (AoA) to the blade.
Low frequency TE surface pressure increases with increased AoA and high frequency
surface pressure decreases with increased AoA.

It seems that the TE surface pressure remains almost unaltered during wake operation

Results from the surface transducers at the leading edge (LE) and the inflow angles
determined from the pitot tubes indicates that the inflow at LE is more turbulent in
wake for the same AoA and with a low frequency characteristic, thereby giving rise to
more low frequency noise generated during wake operation..
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6.3

The trailing edge surface pressure hardly varies with wake or power but is dependent
of the inflow angle, AoA.

The far field measurements supports that on one hand there will be produced relative
more low frequency noise due to a turbulent inflow to the blade and on the other hand
there will be produced less noise in the broader frequency range/high frequency range
due to a lower inflow angle caused by the wind deficit in the wake. The net effect of
wake on the total noise level is unresolved

It has not been possible to get a precise estimation of the effect on the noise generation
for a given wake degree based on the far field noise measurements. This was not possible due to limited recordings for situations with wake and without wake at comparable situations regarding wind speed and blade configuration.
Results for up- and downwards movement of blade
In the WAKE project Risoe DTU has carried out calculations of expected directivity characteristics associated with the trailing edge noise according to the theory summarized by
Howe [11]. In this theory, the actual noise generated at the trailing edge is perceived differently by the observer depending on the observer location relatively to the trailing edge
of the local blade sections. As a result, the actual sound pressure spectrum at the observer
location has to be multiplied by a directivity factor ranging from 0 to 1 to get the representative emitted sound spectrum from the blade. In the present calculation, the turbine
geometry including pitch and twist of the blades, tilt and yaw of the rotor, as well as the
location of the observer relative to the rotor are taken into account to calculate the directivity factor for each position of the blade sections on the rotor disk, i.e. as a function of radius and azimuth angle.
In Figure 47 the calculated directivity for an observer position at Hub height 100 m down
stream of the wind turbine is shown and in Figure 48 the calculated directivity for an observer position at height 2 m above ground level 100 m down stream of the wind turbine
(corresponding to the PMMS position) is shown. It is clearly seen that for the observer
point at hub height no major variation is seen between up- and downside of the rotor plane
where the picture for the observation point at 2 m above ground level indicates that from
this point most noise is received from the downwards movement of the blade.
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Figure 47
Directivity calculated according to [11] for an observation point at hub height 100 m
downstream of the rotor.
Highest directivity
Figure 48
Directivity calculated according to [11] for an observation point at height 2 m above the
ground (corresponding to the PMMS) 100 m downstream of the rotor.
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From other studies [4] it is also seen that the downwards movement of the blade is usually
more noisy than the upwards movement when observed from a position on the ground.
This is illustrated in Figure 49 where contour plots obtained from measurements carried
out using a microphone array [4] .
It is seen that the major part of downward radiated noise is produced during the downwards movement of the blades. The effect was observed for all frequencies and is attributed to a combination of convective amplification and directivity of trailing edge noise. Also
it is seen that the major part of the noise is radiated from the outer part of the blade.
Figure 49
Example of noise source locations in the rotor plane, as a function of frequency obtained
using a microphone array measurement system. The colour scale is 12 dB with red as the
highest value [4].
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It is therefore important to notice that the pattern observed using the PMMS may be different from a different observation point as illustrated above.
From the measurements with the PMMS some situations where a shift of the PMMS focus
has been moved from the downside to the upside within a short time period with comparable weather conditions and turbine configuration are chosen for analysis.
In Figure 50 and Figure 51 frequency spectra obtained with focus on NM/OM and NT/OT
are shown. For both focus areas it is seen that higher noise values are measured during
downwards movement than during upwards movement as it is also seen in Figure 49.
Up- and downwards movement of blade 1
NM (16/7 14.16) and OM (16/7 14.36) - pitch minus 1 - wind speed 6 m/s
80
70
Leq (dB) re 20 uPa
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Frequency, Hz
Blade 1 Up
Blade 1 Down
Figure 50
Spectra obtained with focus on NM and OM for blade 1 on 16 July; pitch angle minus 1.
Wind speed approx. 6 m/s at hub height.
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Up- and downwards movement of blade 1
NT (16/7 13.58) and OT (16/7 14.29) - pitch minus 1 - wind speed 6 m/s
80
70
Leq (dB) re 20 uPa
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Frequency, Hz
Blade 1 Up
Blade 1 Down
Figure 51
Spectra obtained with focus on NT and OT for blade 1 on 16 July; pitch angle minus 1.
Wind speed approx. 6 m/s at hub height.
In Figure 52 frequency spectra obtained with focus on NM/OM, NT/OT and NP/OP are
shown. For all situations it is seen that higher noise values are measured during focus on
the downwards movement compared to focus on the upwards movement.
Blade 2 - 11/9 at 14 m/s
Different positions on blade and upwards and downwards movement
80
70
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Frequency, Hz
OT
OP
OM
NT
NM
NP
NP
Figure 52
Spectra obtained with focus on NT, OT, NP, OP, NM and OM for blade 2 on 11 September; pitch angle minus 1. Wind speed approx. 7 m/s at hub height.
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When looking at the results from the surface pressure transducers averaged in azimuth sections as shown in Figure 53 and Figure 54 it is seen that a consistent variation with higher
surface pressure levels during downwards compared to upwards movement can not be
seen.
This supports the observation made earlier that this difference in the noise during upwards
and downwards movement when observed from a position on the ground is related to directional effects of the noise radiated from the wind turbine blade.
Figure 53
TE surface pressure spectra for period with no wake averaged separately for 6 azimuth
sections on rotor plane.
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Figure 54
LE surface pressure spectra for period with no wake averaged separately for 6 azimuth
sections on rotor plane.
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7.
Investigation of WAKE effects for wind farms
7.1
Introduction
From the results of the measurement campaign it was seen that wake does influence the
noise generation from wind turbines in wake both with regard to frequency content and
overall reduction due to the wind deficit in wake. However it has not been possible to
make an explicit characterisation of this influence to such a degree that it has been possible
to implement a new wake model in the WindPRO program code.
Therefore the model study presented here was made to investigate the influence of the
wake effect on the noise impact on receptors around the wind farm based solely on the
wind deficit due to wake.
The wake of the turbines causes the turbines downstream to experience a lower wind
speed compared to turbines upstream. With lower wind speed the source noise level will
be lower and thus the total noise level from the wind farm.
A complication is where the reference wind speed is measured. If measured at the receptor
the receptor may also be in the wake of the turbines and experience reduced wind speed,
which in turn corresponds to a higher wind speed at the turbines.
The objective of the model study is to use the standard model tool available to qualify and
quantify the influence of these wakes on the noise impact. The basic assumption for this
study has been that a turbine operating in wake radiates the same noise as a turbine with
free inflow at the same power output.
7.2
Theoretical background
Wind turbines produce noise according to their noise curve. This gives the noise level at
the hub of the turbine at different wind speed in either hub height or a reference height of
10 m above ground.
Wind turbines are generating power by converting the kinetic energy from the wind to
electric energy. This leaves behind a wake with reduced wind speed downstream of the
turbine rotor. This reduced wind speed space is commonly referred to as the wake. Turbines located in a wind farm will at times find themselves in the wake of their neighbouring turbines and therefore experience a different wind speed than they would have undisturbed. Since the source noise level is a function of wind speed at hub height, the source
noise level for a turbine in a wake will therefore be different than from an undisturbed turbine.
In Denmark the critical noise level at a neighbour (receptor) in the open land is 42 dB(A)
at 6 m/s and 44 dB(A) at 8 m/s, both at the reference height of 10 m above ground level.
The relation between wind speed at 10 m height and at 80 m height is a function of the ter-
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rain of the site and the hub height of the turbine, but a standardized relation is found in the
IEC profile [5], which assumes the logarithmic wind profile:
Where U(z) is the wind speed in height z, U* is the friction velocity, k is von Karmans
constant: 0.4 and z0 is the roughness length, which for the standard IEC case is 0.05 m.
Under these conditions 6 m/s at 10 m height correspond to 8.35 m/s at 80 m height and
8 m/s at 10 m height correspond to 11.14 m/s at 80 m height.
In a noise calculation the location of the reference point is not necessarily well defined.
One interpretation can be the undisturbed wind speed upwind from the first turbine. Another could be at each turbine, but then a study on individual wind speed at turbines becomes meaningless. A third interpretation is at each individual receptor.
If the third interpretation is used and wakes are included in the noise calculation then it
must also be assumed that the receptor could be influenced by wakes from turbines. In the
situation where the wind speed at the receptor is reduced due to wakes, the corresponding
free wind speed at hub height must be increased when relating it to a specific wind speed
at 10 m above ground level. Fortunately a relative change in wind speed at 10 m height
corresponds to the same relative change in wind speed at hub height when assuming the
logarithmic wind profile.
In this situation the wind speed at hub height and thus the source noise level for a turbine
might therefore both be modified directly by the wake effect and by the wake effect at the
receptor.
7.3
Methodology
In order to limit the study to examine the core issue the study was reduced to a minimum
of variables. We have not covered all the possible outcomes and variables, but reduced the
problem to show results from some typical scenarios.
7.4
Wake model
We have used a wake model, the N.O. Jensen model [6], which is a relatively simple model, but a model which has proved quite durable in wind energy production assessments [7].
More advanced models exist, but in tests performed by EMD they have not improved the
calculation of wake losses.
The wake calculated by the N.O. Jensen model is a simple fan behind the rotor with a
wake wind speed that recovers downstream, Figure 55.
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Single w ake w ind speeds [m/s]
300
250
200
150
Radial distance [m]
100
50
0
-50
-100
-150
-200
-250
-300
0
200
400
600
Dow nstream distance [m]
800
1 000
1 200
10
9.834
9.669
9.503
9.338
9.172
9.006
8.841
8.675
8.509
8.344
8.178
8.013
7.847
7.681
7.516
7.35
7.185
7.019
6.853
6.688
6.522
6.356
6.191
6.025
5.86
5.694
5.528
5.363
5.197
5.032
4.866
4.7
Figure 55
The wake calculated by the N.O. Jensen model is a simple wake where the rate of expansion is a function of turbulence intensity. The red colour is the free wind speed upwind
from the rotor.
7.5
Noise propagation model
The noise propagation model used was the NORD2000 model.
The model used for noise propagation calculation in Denmark is defined by the “Bekendtgørelse nr.1518 af 14. dec. 2006” from the Danish Environmental agency [8]. It is a
model that in the average situation gets quite close to the actual noise level, but it is also a
relatively simple model that does not take into account the wind direction.
The more advanced Nord2000 model takes wind direction into account in addition to a
host of other variables irrelevant to this study, such as temperature, thermal stability, humidity, terrain surface properties and topography [9]. In this study all these parameters
have been set to standard values (Table 1), which are unchanged throughout the study.
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Terrain
Elevation
Roughness
Terrain type
Wind profile
Height above ground for receiver wind speed
Wind shear extrapolation
Climatic parameters
Relative humidity
Temperature
Turbulence strength (wind)
Turbulence strength (temperature)
StDev wind fluctuations
Inverse Moinin Obukov length
Temperature scale, T*
0 m, flat terrain
0,03 m
Normal (Crop field spring, autumn, grass)
1,5 m
IEC profile (z0 = 0,05 m)
50%
15 deg. C at 0 m a.g.l.
0,12
0,008
0 m/s
0m
0
Table 1
Parameters for the Nord2000 calculations.
As part of the project “Noise and energy optimization of wind farms” [10] EMD implemented a prototype of the Nord2000 model in the commercial software package
WindPRO. For the present project EMD has extended that implementation to include differentiation of wind speed at hub height for each of the involved turbines. This makes it
possible to combine a wake model with the Nord2000 model to find the reduced wind
speeds in the wind farm and thus the reduced source noise levels to use for the noise calculation.
7.6
Wind turbine characteristics
The turbines used for the calculation must have a noise curve giving the source noise level
as a function of wind speed. In addition all values on this noise curve must be available as
octave band distributions for Nord2000 to do a proper calculation with it. EMD found such
complete data for a Vestas V90-3.0 MW turbine. The particular make of the turbine is not
relevant, but each turbine type has an individual noise curve and had we chosen a different
turbine type the calculation results might have been slightly different. The noise curve for
the Vestas V90-3.0 MW turbine is shown in Figure 56.
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LW(A)
Noise curve for the Vestas V90-3 MW
108
106
104
102
100
98
96
94
92
Vestas V90-3 MW
13 - (18,1)
12 - (16,7)
11 - (15,3)
10 - (13,9)
9 - (12,5)
8 - (11,1)
7 - (9,7)
6 - (8,4)
5 - (7)
4 - (5,6)
3 - (4,2)
Wind speed at 10 m (in brackets: wind speed at hub height)
Figure 56
Noise curve for the Vestas V90-3.0 MW turbine type. The wind speed is given at 10 m
a.g.l. and in brackets wind speed at hub height.
7.7
Calculation principle and limitations
Instead of using an actual site generic setups where used with simple geometry and uniform terrain so as not to pollute the result with influences irrelevant to the study. This
makes it possible to calculate the consequences of the reduction of wind speed in the wake
on noise impact.
The calculations do not take into account other potential wind farm influences on the noise
such as turbulence and modified wind shear in the wake of turbines. Also the particular
models and turbine characteristic used have limitations, which make the calculations case
studies rather than complete documentation of the issue.
In the case of the wake model, it is a simplified description of the wake which particularly
near the ground (eg. 10 m a.g.l.) may cause a deviation from reality. However, it was
found that the scale of the wake found by the model is reasonably correct for the purpose.
In the case of the Nord2000 model there is the limitation beside the common model limitations, that only a specific climatic and terrain condition was examined.
Finally the calculations do not take into account directivity in the source noise level. The
source noise level used is the downstream noise level. At other angles to the wind direction the noise level of the turbine might be different.
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7.8
Calculation setup
The calculations were run in the WindPRO software environment using the above mentioned wake model and noise propagation model.
Two layout setups were investigated:
1. A row of 5 turbines placed with a spacing of 3 times rotor diameter.
2. A square layout with 5 rows and 5 columns and a spacing of 5 times rotor diameter.
The row is a typical layout for Danish wind farms, which typically consists of a row from
3 to 8 turbines. The spacing is the minimum spacing allowed when the orientation of the
wind farm is perpendicular to the main wind direction. Choosing the tightest possible layout we can expect the largest impact of the wake effect.
The square layout is less common. Offshore wind farms will typically be larger and wind
farms of this size on land are more common outside Denmark and will then typically have
a more random (less geometric) layout. However, the square layout will represent the situation of a larger wind farm with a more complex layout where wake effect is not limited to
only two wind directions. For a wind farm of this size the typical spacing is 5 time rotor
diameter.
The turbine type used is the before mentioned Vestas V90-3.0 MW turbine. With a 90 m
rotor diameter an appropriate hub height is 80 m. Taller hub heights have the effect of reducing the ground absorption and thus increase the noise impact. Also the corresponding
wind speed in hub height when calculating for a specific height at 10 m height will be
higher leading (usually) to higher source noise levels of the turbine. On the other hand a
taller tower will remove the hub from the ground and at least near the turbine reduce the
noise impact. However, these consequences are of less interest and will not influence the
relative impact of the wake significantly, so only 80 m hub height has been used for the
calculations.
The calculation points (the “neighbours”) are arranged in rows radiating out from the wind
farm layout. There are 25 m between each row and the distance from the wind farm is
sought to match the distance where the critical noise limit 6 and 8 m/s at 10 m height is
reached with the Danish noise codes (42 and 44 dB(A)). For the row layout the distance to
the first point is 400 m (450 m at 90o angle while for the square layout the distance is
600 m.
For the row layout the receptors are arranged in three rows:
1. Same direction as the wind farm (0 degrees)
2. 45 degree angle from the last turbine in the row
3. 90 degrees from the last turbine in the row
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The setup is shown in Figure 57.
Figure 57
The row layout. The angles refer to alignment with the turbine layout orientation. Rotor
symbols are wind turbines, orange dots are receptors.
For the square layout two rows of receptors was investigated:
1. A row extending from the side of the square along the axis of the central row of the
layout (0 degrees)
2. A row extending from the corner turbine along the diagonal of the wind farm (45 degrees).
The setup is shown in Figure 58.
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Figure 58
The square layout. The angles refer to alignment with the turbine layout orientation. Rotor
symbols are wind turbines, orange dots are receptors.
7.9
Calculations
For each layout calculations were run to calculate the reduced wind speed at each turbine
location. This was done for free wind speed at hub height 6.5 m/s to 16.5 m/s in steps of
1 m/s and all wind directions in steps of 5 degrees. This produced a matrix of free wind
speed and wind direction for each turbine. The matrix was fed to the Nord2000 calculation
module which calculated the same matrix for each receptor. Basically the noise contribution for each turbine was calculated and added to the result from the other turbines for
each situation in the matrix. In the case of the row layout this is 71280 Nord2000 calculations. Because of the very large calculation the calculation was split in 2; a calculation run
with full number of receptors but limited number of wind speeds and one with a reduced
number of receptors and full range of wind speeds.
As a baseline calculation the Nord2000 calculation runs were also calculated with a fixed
free wind speed at all turbines, meaning no account of wake loss, a simulation of the assumption used today where wake loss is not taken into account in noise calculations.
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A second round of calculations was made including the wake effect at the receptor. This
required a new set of reduced wind speed calculations where the reduced wind speed due
to wake effect was calculated at 10 m height at each receptor. The relative reduction in
wind speed for a particular receptor for each wind speed and wind direction was found and
used to modify the free wind speed at hub height. The proper wake effect at each turbine
was then found by interpolating between the free wind speed scenarios calculated.
7.10
7.10.1
Results
The row scenario
The amount of data produced gives a number of ways to present the data. An overview can
be found by looking at the influence of wakes at the turbines (but not at the receptors) on
the noise impact on the closest of the receptors as a function of wind direction and wind
speed.
The plots for the closest receptor at 400 m distance in each row (450 m at 90o angle) are
presented in Figure 59 to Figure 61.
Noise as a function of wind direction. All wind
speeds, angle 0 degrees. Reference: free wind
speed
330,5
300,5
270,5
46
44
42
40
38
36
34
32
30
0,5
30,5
60,5
6,5 m/s
7,5 m/s
90,5
8,5 m/s
9,5 m/s
10,5 m/s
240,5
120,5
210,5
150,5
180,5
Figure 59
11,5 m/s
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Noise as a function of wind direction. All wind
speeds, angle 45 degrees. Reference: free wind
speed
330,5
300,5
270,5
46
44
42
40
38
36
34
32
30
0,5
30,5
60,5
6,5 m/s
7,5 m/s
90,5
8,5 m/s
9,5 m/s
10,5 m/s
240,5
120,5
210,5
11,5 m/s
150,5
180,5
Figure 60
Noise as a function of wind direction. All wind
speeds, angle 90 degrees. Reference: free wind
speed
330,5
300,5
270,5
46
44
42
40
38
36
34
32
30
0,5
30,5
60,5
6,5 m/s
7,5 m/s
90,5
8,5 m/s
9,5 m/s
10,5 m/s
240,5
120,5
210,5
11,5 m/s
150,5
180,5
Figure 61
As the row is oriented along an east-west axis the turbines will stand in wakes when the
wind is coming from east and west. The angle range is 65 degrees wide in the downwind
direction and 40 degrees wide in the upwind direction. The downwind reduction is deeper
than the upwind reduction because the closest turbine is reduced the most in the downwind
situation but undisturbed in the upwind situation. Qualitatively there is very little difference between the results of the three plots. In all three directions the resulting noise impact
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is reduced to the same extent when the turbines are standing in wakes. The difference between the plots is in absolute noise level.
The impact of the wake at different wind speeds is illustrated in Figure 62 where the noise
at the closest receptor in the 0o row is plotted against wind speed in the directions most and
least impacted by the wake. The difference is small at 6.5 m/s at 1.7 dB, increases to
5.1 dB at 8.5 m/s and is then reduced to 3.2 dB at 11.5 m/s.
Noise as a function of free wind speed.
Inside wake and across from wake
50
LW(A)
40
30
20
WD 0,5
10
WD 270,5
0
6,5 m/s
7,5 m/s
8,5 m/s
9,5 m/s
10,5 m/s 11,5 m/s
Free wind speed at hub height
Figure 62
If the reference location for wind speed at 10 m height is changed from the free wind
speed to the wind speed at the receptor the picture changes. Figure 63 shows all wind
speeds at the first receptor in row angle 0o. The wind speeds are again the wind speeds at
hub height.
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Noise as a function of wind direction. All wind
speeds, angle 0 degrees. Reference: at receptor
330,5
300,5
270,5
46
44
42
40
38
36
34
32
30
0,5
30,5
60,5
6,5 m/s
7,5 m/s
90,5
8,5 m/s
9,5 m/s
10,5 m/s
11,5 m/s
240,5
120,5
210,5
150,5
180,5
Figure 63
With wind coming along the axis of the wind farm this receptor is located in the maximum
wake of the wind farm. That means that the wind speed at 10 m height at the receptor is
reduced. To find the hub height equivalent to a specific wind speed at the receptor in wake
the hub height wind speed must be increased accordingly. At this particular receptor the
relative increase of wind speed necessary is in the scale of 30 %. With two adjustments at
work in the same direction the result is more complex. In general the two effects counter
each other so the resulting change in noise impact is minimal.
At the receptors at 45o angle and 90o angle however the result is different (Figure 64 and
Figure 65). Now the wind directions where the turbines stand in wake and the receptors
are in wakes are different and they work unopposed.
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Noise as a function of wind direction. All wind
speeds, angle 45 degrees. Reference: at
receptor
330,5
300,5
270,5
0,5
46
44
42
40
38
36
34
32
30
30,5
60,5
6,5 m/s
7,5 m/s
90,5
8,5 m/s
9,5 m/s
10,5 m/s
240,5
120,5
210,5
11,5 m/s
150,5
180,5
Figure 64
Noise as a function of wind direction. All wind
speeds, angle 90 degrees. Reference: at
receptor
330,5
300,5
270,5
46
44
42
40
38
36
34
32
30
0,5
30,5
60,5
6,5 m/s
7,5 m/s
90,5
8,5 m/s
9,5 m/s
10,5 m/s
240,5
120,5
210,5
11,5 m/s
150,5
180,5
Figure 65
The wind directions with wakes lead to a reduced noise impact at the receptor, while some
of the wind speeds result in increase in noise while others result in decrease in noise when
the receptors are in wakes. At low wind speeds, 6.5 to 9.5 m/s, noise is increased, at
10.5 m/s it is basically unchanged and at 11.5 m/s it leads to reduced noise.
The explanation can be found in the noise curve for the specific turbine type used (Figure
56). The source noise level is increasing with wind speed up to 8 m/s (11 m/s at hub
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height), then it decreases. So, if the receptor is located in a wake the corresponding increase in wind speed at hub height at the turbines increase the source noise level at low
wind speed but decreases it at high wind speed.
It is worthwhile to look at the specific hub height wind speeds of 8.5 and 11.5 m/s, which
roughly corresponds to 6 and 8 m/s at 10 m height.
The results for 8.5 m/s at hub height and the first (400 m distance) receptor in the 0o row
are shown in Figure 66 and Figure 67.
Noise as a function of wind direction. 8,5 m/s,
angle 0 degrees.
330,5
46
0,5
30,5
44
42
300,5
60,5
40
Incl. wake reduction
38
Excl. wake reduction at turbines
36
270,5
90,5
34
Excl. wake reduction at
receptors
No wake reduction
240,5
120,5
210,5
150,5
180,5
Figure 66
Change in noise due to wakes. 8,5 m/s, angle 0
degrees.
330,5
4
0,5
2
30,5
0
300,5
60,5
-2
Incl. wake reduction
-4
-6
270,5
90,5
-8
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
240,5
120,5
210,5
150,5
180,5
Figure 67
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In these plots it is clear that the wake reduction at the turbines lead to a reduction in noise
at the receptor of up to 5 dB. However the wake at the receptor causes an increase in noise
at the receptor of up to 2.4 dB. As the two opposite adjustments affects the same wind direction interval the effects are largely cancelled out.
Changing to 11.5 m/s at hub height there is still a reduction in noise due to the wake at the
turbines, but the wake at the receptor also cause a reduction in noise. Combining the two
does not result in an increased reduction but instead cancels the noise reduction. The noise
level at 11.5 m/s at hub height is near the maximum noise level. Any adjustment away
from this wind speed will reduce the source noise level.
Noise as a function of wind direction. 11,5 m/s,
angle 0 degrees.
330,5
48
0,5
30,5
46
44
300,5
60,5
42
Incl. wake reduction
40
Excl. wake reduction at turbines
38
270,5
90,5
36
Excl. wake reduction at
receptors
No wake reduction
240,5
120,5
210,5
150,5
180,5
Figure 68
Change in noise due to wakes. 11,5 m/s, angle
0 degrees.
330,5
4
0,5
2
30,5
0
300,5
60,5
-2
Incl. wake reduction
-4
-6
270,5
90,5
-8
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
240,5
120,5
210,5
150,5
180,5
Figure 69
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In Figure 70 to Figure 73 we can see how the internal wake in the wind farm and the wake
at the receptor affect different wind directions at the 45o and 90o receptors (8.5 m/s). Unopposed the influence from the turbine wake results in noise reductions of up to 5 dB and
an increase of noise up to 2.5 dB.
Noise as a function of wind direction. 8,5 m/s,
angle 45 degrees.
330,5
46
0,5
30,5
44
42
300,5
60,5
40
Incl. wake reduction
38
Excl. wake reduction at turbines
36
270,5
90,5
34
Excl. wake reduction at
receptors
No wake reduction
240,5
120,5
210,5
150,5
180,5
Figure 70
Change in noise due to wakes. 8,5 m/s, angle
45 degrees.
330,5
4
0,5
2
30,5
0
300,5
60,5
-2
Incl. wake reduction
-4
-6
270,5
90,5
-8
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
240,5
120,5
210,5
150,5
180,5
Figure 71
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Noise as a function of wind direction. 8,5 m/s,
angle 90 degrees.
330,5
46
0,5
30,5
44
42
300,5
60,5
40
Incl. wake reduction
38
Excl. wake reduction at turbines
36
270,5
90,5
34
Excl. wake reduction at
receptors
No wake reduction
240,5
120,5
210,5
150,5
180,5
Figure 72
Change in noise due to wakes. 8,5 m/s, angle
90 degrees.
330,5
4
0,5
2
30,5
0
300,5
60,5
-2
Incl. wake reduction
-4
-6
270,5
90,5
-8
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
240,5
120,5
210,5
150,5
180,5
Figure 73
The same figures for the hub height wind speed of 11.5 m/s are shown below. As both
wake in wind farm and wake at receptor reduces the noise level and the effects are not coinciding the reduced noise level extend to a wide range of wind directions.
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Noise as a function of wind direction. 11,5 m/s,
angle 45 degrees.
330,5
48
0,5
30,5
46
44
300,5
60,5
42
Incl. wake reduction
40
Excl. wake reduction at turbines
38
270,5
90,5
36
Excl. wake reduction at
receptors
No wake reduction
240,5
120,5
210,5
150,5
180,5
Figure 74
Change in noise due to wakes. 11,5 m/s, angle
45 degrees.
330,5
4
0,5
2
30,5
0
300,5
60,5
-2
Incl. wake reduction
-4
-6
270,5
90,5
-8
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
240,5
120,5
210,5
150,5
180,5
Figure 75
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Noise as a function of wind direction. 11,5 m/s,
angle 90 degrees.
330,5
48
0,5
30,5
46
44
300,5
60,5
42
Incl. wake reduction
40
Excl. wake reduction at turbines
38
270,5
90,5
36
Excl. wake reduction at
receptors
No wake reduction
240,5
120,5
210,5
150,5
180,5
Figure 76
Change in noise due to wakes. 11,5 m/s, angle
90 degrees.
330,5
4
0,5
2
30,5
0
300,5
60,5
-2
Incl. wake reduction
-4
-6
270,5
90,5
-8
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
240,5
120,5
210,5
150,5
180,5
Figure 77
The influence of the wakes as a function of distance from the wind farm can also be analysed. Below are shown plots of noise as a function of distance in the receptor row extending in the same direction as the wind farm orientation with a wind direction along the same
axis.
The impact of the wake is almost constant with distance.
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Noise with distance from turbines, 8,5 m/s, 0
degrees, wind direction 270 degrees.
46
LW(A)
44
Incl. wake reduction
42
40
Excl. wake reduction at
turbines
38
Excl. wake reduction at
receptors
36
34
400
450
500
550
No wake reduction
Distance
Figure 78
Noise with distance from turbines, 11,5 m/s, 0
degrees, wind direction 270 degrees.
46
LW(A)
44
Incl. wake reduction
42
40
Excl. wake reduction at
turbines
38
Excl. wake reduction at
receptors
36
34
400
450
500
550
No wake reduction
Distance
Figure 79
7.10.2 Square layout
A similar analysis can be made for the square layout. In this layout there are only two rows
of receptors and the closest receptor in each row is 600 m from the closest turbine.
The noise impact at the receptor due to the internal wake in the wind farm as a function of
wind direction is shown in Figure 80 and Figure 81.
The primary difference between this situation and the one seen above for the row layout is
that the wake effect is distributed over a wider range of directions. No matter which direction the wind is coming from there will be a wake influence on the wind speed where the
turbines are located.
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A secondary difference is that the amount of turbines and the distances involved make the
wind direction having an influence on the noise impact itself without the wake effect. This
is particularly seen in the 45 degree receptor where there is about 2 dB difference between
wind directions toward the receptor from the turbines to wind directions from the receptor
to the turbines.
Noise as a function of wind direction. All wind
speeds, angle 0 degrees. Reference: free wind
speed
330,5
300,5
270,5
46
44
42
40
38
36
34
32
30
0,5
30,5
60,5
6,5 m/s
7,5 m/s
90,5
8,5 m/s
9,5 m/s
10,5 m/s
240,5
120,5
210,5
11,5 m/s
150,5
180,5
Figure 80
Noise as a function of wind direction. All wind
speeds, angle 45 degrees. Reference: free
wind speed
330,5
300,5
270,5
46
44
42
40
38
36
34
32
30
0,5
30,5
60,5
6,5 m/s
7,5 m/s
90,5
8,5 m/s
9,5 m/s
10,5 m/s
240,5
120,5
210,5
150,5
180,5
Figure 81
11,5 m/s
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If the reference point for the wind speed is moved to the receptor the plots become the
ones shown below. There are internal wind speed reductions within the wind farm in all
wind directions, but there is also the wake effect at the receptor affecting the noise impact
when the wind direction is toward the receptor from the turbines. This results in a rather
jagged rose depending on, if a particular direction is dominated by the wake inside the
wind farm and/or the wake at the receptor.
Noise as a function of wind direction. All wind
speeds, angle 0 degrees. Reference: at receptor
330,5
300,5
270,5
46
44
42
40
38
36
34
32
30
0,5
30,5
60,5
6,5 m/s
7,5 m/s
90,5
8,5 m/s
9,5 m/s
10,5 m/s
11,5 m/s
240,5
120,5
210,5
150,5
180,5
Figure 82
Noise as a function of wind direction. All wind
speeds, angle 45 degrees. Reference: at receptor
330,5
300,5
270,5
46
44
42
40
38
36
34
32
30
0,5
30,5
60,5
6,5 m/s
7,5 m/s
90,5
8,5 m/s
9,5 m/s
10,5 m/s
11,5 m/s
240,5
120,5
210,5
150,5
180,5
Figure 83
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As for the row analysis the 8.5 m/s and 11.5 m/s data can be arranged to see the influence
of the internal wake in the wind farm and the wake on the receptors.
For 8.5 m/s (~6 m/s at 10 m height) the plots are presented in Figure 85 to Figure 87. For
the receptor located along the side of the square layout the wake on the receptor is spread
out widely and largely cancels out the effect of the internal wake. When the wind is coming from the wind farm the total effect is typically slightly higher (<1.5 dB) that without
any wake effects. However, the receptor at the corner of the wind farm is subjected to a
more massive and narrow wake from the wind farm. Whereas the internal wake in general
reduces the noise impact at the receptor, the wake at the receptor results in an increase in
noise impact of up to 2 dB.
Noise as a function of wind direction. 8,5 m/s,
angle 0 degrees.
330,5
46
0,5
44
30,5
42
300,5
60,5
40
Incl. wake reduction
38
36
270,5
90,5
34
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
No wake reduction
240,5
120,5
210,5
150,5
180,5
Figure 84
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Change in noise due to wakes. 8,5 m/s, angle 0
degrees.
330,5
4
0,5
30,5
2
0
300,5
60,5
-2
-4
Incl. wake reduction
-6
270,5
90,5
-8
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
240,5
120,5
210,5
150,5
180,5
Figure 85
Noise as a function of wind direction. 8,5 m/s,
angle 45 degrees.
330,5
46
0,5
44
30,5
42
300,5
60,5
40
Incl. wake reduction
38
36
270,5
90,5
34
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
No wake reduction
240,5
120,5
210,5
150,5
180,5
Figure 86
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Change in noise due to wakes. 8,5 m/s, angle
45 degrees.
330,5
4
0,5
30,5
2
0
300,5
60,5
-2
-4
Incl. wake reduction
-6
270,5
90,5
-8
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
240,5
120,5
210,5
150,5
180,5
Figure 87
At 11.5 m/s the influences are much dampened. Both the internal wake and the wake at the
receptor do not change the noise impact much and accordingly the total result is not so different from the noise impact without wakes.
Noise as a function of wind direction. 11,5
m/s, angle 0 degrees.
330,5
48
0,5
46
30,5
44
300,5
60,5
42
Incl. wake reduction
40
38
270,5
90,5
36
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
No wake reduction
240,5
120,5
210,5
150,5
180,5
Figure 88
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Change in noise due to wakes. 11,5 m/s, angle
0 degrees.
330,5
4
0,5
30,5
2
0
300,5
60,5
-2
-4
Incl. wake reduction
-6
270,5
90,5
-8
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
240,5
120,5
210,5
150,5
180,5
Figure 89
Noise as a function of wind direction. 11,5
m/s, angle 45 degrees.
330,5
48
0,5
46
30,5
44
300,5
60,5
42
Incl. wake reduction
40
38
270,5
90,5
36
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
No wake reduction
240,5
120,5
210,5
150,5
180,5
Figure 90
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Change in noise due to wakes. 11,5 m/s, angle
45 degrees.
4
330,5
0,5
30,5
2
0
300,5
60,5
-2
-4
Incl. wake reduction
-6
270,5
90,5
-8
Excl. wake reduction at
turbines
Excl. wake reduction at
receptors
240,5
120,5
210,5
150,5
180,5
Figure 91
Noise impact as a function of distance from the wind farm has also been examined and the
result is shown in Figure 92 and Figure 93. At 8.5 m/s the impact of the wakes is quite
large (~4 dB), but the total wake influence is quite small. Within the range examined the
difference between the results is constant. At 11.5 m/s the influence is much smaller
(~2 dB) and also almost constant with distance.
Noise with distance from turbines, 8,5 m/s, 0
degrees, wind direction 270 degrees.
46
LW(A)
44
Incl. wake reduction
42
40
Excl. wake reduction at
turbines
38
Excl. wake reduction at
receptors
36
34
580
600
620
Distance
Figure 92
640
660
No wake reduction
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Noise with distance from turbines, 11,5 m/s, 0
degrees, wind direction 270 degrees.
48
LW(A)
46
Incl. wake reduction
44
42
Excl. wake reduction at
turbines
40
Excl. wake reduction at
receptors
38
36
580
600
620
640
660
No wake reduction
Distance
Figure 93
7.11
Conclusion on the model study
The model study on the noise impact consequence of the wind speed reduction in the wake
of wind turbines has shown that the models indeed predict an influence of the wakes.
The reduction of wind speed on the turbines causes a reduced source noise level of the turbines. The largest reduction on the noise impact at the receptors is when the closest turbines are in a deep wake, whereas if the deep wake is elsewhere in the wind farm the noise
reduction is less.
The reduction in noise is less at high wind speed than at low wind speed. This is due to the
shape of the noise curve of the wind turbine and so while this may be qualitatively true for
wind turbines in general, the magnitude will be different for different turbine models.
In the tested row layout with 5 wind turbines the maximum noise reduction at a distance of
400 m from the wind farm is 5.2 dB at 8.5 m/s at hub height (6.1 m/s at 10 m height) and
3.4 dB at 11.5 m/s at hub height (8.3 m/s at 10 m height). However, this happens in a very
narrow window of wind directions. The influence is detectable over 2 sectors, but only of
relevant size within a single 30 degree sector. The most frequent wind direction sector (30 o
direction window) in Denmark has a frequency of 16 %. However, in order to minimize
wake losses it is customary to place the wind farms as perpendicular to the prevailing wind
direction as possible. In Denmark the directions perpendicular to the prevailing wind direction is north-northwest and south-southeast with typical frequencies in Denmark of 4 %
and 5 % respectively. The reduction of noise due to wake reduced wind speed is therefore
a rare event.
Around a square layout the influence extend to a wider range of wind directions as the
more complex layout means that some of the wind turbines will almost always be in the
wake of other turbines. For the square layout tested this may result in reductions in noise at
600 m distance of up to 3.7 dB at 8.5 m/s and 1.7 dB at 11.5 m/s.
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The issue of choosing the reference location for the reference wind speed at 10 m above
ground level can complicate matters. The above reductions due to the wake wind speed
reductions in the wind farm may be valid if the reference wind speed is the undisturbed
free wind speed. However, if the reference wind speed is the 10 m wind speed at the receptor then this location will also be subjected to the wake. The correction in hub height wind
speed that this leads to was also investigated.
At low wind speed the receptor wake correction leads to an increased wind speed at the
turbines at hub height and an increase in source noise level. At high wind speed the increase in wind speed at hub height will lead to no change in noise for some turbines, while
for other turbines, like the turbine type used in this investigation, the noise level will actually decrease with increasing wind speed.
The influence of the wake on the wind speed at the receptor depends on distance from the
turbines as well as the amount of turbines. The small layout of 5 turbines will at 400 m
distance cause a decrease in wind speed of typically 30 %, while the larger wind farm of
25 turbines will at a distance of 600 m from the closest turbine be subjected to a wind
speed reduction of up to 20 % reduction but much more variation between directions.
At low wind speed the wake at the receptor oppose the internal wake effect in the wind
farm so that when the two coincide as in the maximum wake direction behind the row layout, they will largely cancel each other out. When they do not coincide the receptor wake
effect may increase noise impact at the receptor up to 3 dB at 400 m distance in case of the
row layout and up to 2.5 dB in the case of the square layout.
At high wind speed the receptor wake reduction reduces the noise from the turbine. However, since the two wake effects affects the turbine wind speed at hub height oppositely the
two noise reductions are not added together when coinciding but cancel each other. The
influence of the two effects is smaller than at low wind speed.
Summarizing the results the combined wake influence on the noise impact is a complex
function of wind direction, wind speed and wind farm geometry. It may cause deviations
from the undisturbed noise impact of several dB, both up and down, but that effect may
change rapidly with small changes in wind direction. For noise measurements made in the
wake of wind turbines it is certainly worthwhile to keep this influence in mind.
It is a weakness of the calculation that no data were included for the directivity of the
source noise level of the turbines. Those data could have a significant impact on the results.
Another weakness of the calculation is that any change in the properties of the noise due to
the wake (effect of turbulence, shear, interference etc) has not been included in the calculation. Such data might also have an impact on the results.
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8.
Conclusions
The influence of wake on noise emission in wind farms has been investigated both experimentally and theoretically in this project.
As a supplement to the main measurement campaign in the DAN AERO MW project
where surface pressure and inflow measurements were performed on one of the blades on
a NM80 2 MW wind turbine, far field measurements were made using an acoustic parabolic measurements system.
A parabolic measurement system (PMMS) was designed and tested as part of this project.
The parabolic reflector with diameter 2.4 m was mounted on a trailer with hydraulic height
and position adjustments making it easy and fast to set up the PMMS and change the focus
point. An analysis program has been made and it is possible to use different gating on the
recorded acoustic signal to analyse different parts of each wind turbine blades passage of
the focus area of the PMMS. With the PMMS it has been possible to measure and separate
the noise characteristics of each individual blade on the test turbine. The PMMS focus spot
diameter is 5 m at 100 m distance for frequencies above 1000 Hz.
Based on the measurement results obtained with surface pressure sensors and results from
the far field measurements using the PMMS it is concluded that:

The variance of surface pressure at the trailing edge (TE) agrees with the theory with
regard to variation of pressure spectra with varying inflow angle (AoA) to the blade.
Low frequency TE surface pressure increases with increased AoA and high frequency
surface pressure decreases with increased AoA.

It seems that the TE surface pressure remains almost unaltered during wake operation

Results from the surface transducers at the leading edge (LE) and the inflow angles
determined from the pitot tube indicates that the inflow at LE is more turbulent in
wake for the same AoA and with a low frequency characteristic, thereby giving rise to
more low frequency noise generated during wake operation..

The trailing edge surface pressure hardly varies with wake or power but is dependent
of the inflow angle, AoA.

The far field measurements supports that on one hand there will be produced relative
more low frequency noise due to a turbulent inflow to the blade and on the other hand
there will be produced less noise in the broader frequency range/high frequency range
due to a lower inflow angle caused by the wind deficit in the wake. The net effect of
wake on the total noise level is unresolved.
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
The noise observed from a position on the ground is related to directional effects of the
noise radiated from the wind turbine blade. Theoretical results confirmed by PMMS
measurements concludes that for an observer position close to the ground directly
downwind of the wind turbine the major part of the noise is received from the part of
the rotor plane with downwards movement of the blades.
Due to a limited number of recordings for situations with wake and without wake at comparable situations regarding wind speed and blade configuration it has not been possible to
get a precise estimation of the effect on the noise generation for a given wake degree based
on the far field noise measurements. This means that implementation of a more complex
wake model in the program WindPRO has not been possible.
A study based on the effect of the wind deficit due to wake has been carried out. This
model study on the noise impact consequence of the wind speed reduction in the wake of
wind turbines using the WindPRO Nord2000 program has shown that the models indeed
predict an influence of the wake. The basic assumption for this study has been that a turbine operating in wake radiates the same noise as a turbine with free inflow at the same
power output.
The reduction of wind speed on the turbines causes a reduced source noise level of the turbines. The largest reduction on the noise impact at the receptors is when the closest turbines are in a deep wake, whereas if the deep wake is elsewhere in the wind farm the noise
reduction is less.
The reduction in noise is less at higher wind speed than at lower wind speed. This is due to
the shape of the noise curve of the wind turbine used for this study and so, while this may
be qualitatively true for wind turbines in general, the magnitude will be different for different turbine models.
Summarizing the results from the study of wake effects for different wind farm layout it is
concluded that the combined wake influence on the noise impact is a complex function of
wind direction, wind speed and wind farm geometry. It may cause deviations from the undisturbed noise impact of several dB, both up and down, but the effect may change rapidly
with small changes in wind direction.
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9.
References
[1]
Madsen, Helge Aagaard et al.
The DAN-AERO MW Experiments – Final Report
Risø-R-1726, Risø DTU September 2010
[2]
Aagaard Madsen, Helge, Larsen, Gunner Chr., Larsen, Torben J., Troldborg, Niels,
Mikkelsen, Robert Flemming, (2010), Calibration and Validation of the Dynamic
Wake Meandering Model for Implementation in an Aeroelastic Code. Journal of Solar Energy Engineering — 2010, Volume 132, Issue 4, pp. 041014 (14 pages))
[3]
Bertagnolio, F, Madsen, H.Aa., Bak, C. (2010) Trailing edge noise model validation
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[4]
Oerlemans, Stefan; López, Beatriz Méndez
Localisation and quantification of noise sources on a wind turbine.
Proceedings from Wind Turbine Noise, Berlin 2005
[5]
IEC:”Wind turbine generator systems – Part 11: Acoustic noise measurement techniques”. IEC 61 400-11 second edition (Ed 2.1) 2006-11.
[6]
Katic, I., Højstrup J., Jensen, N.O.
A Simple Model for Cluster Efficiency. European Wind Energy Association Conference and Exhibition, Rome, 1986.
[7]
Sørensen, T., Nielsen, P., Thøgersen, M.L.
Recalibrating Wind Turbine Wake Model Parameters – Validating the Wake Model
Performance for Large Offshore Wind Farms, EWEC, Athens, 2006.
[8]
Miljøstyrelsen (The Danish Environmental Agency): Bekendtgørelse om støj fra
vindmøller. Bekendtgørelse nr. 1518 af december 2006.
[9]
Plovsing, Birger
Nord2000 Comprehensive Outdoor Propagation Model
AV 1849/00, DELTA 2006
[10] Søndergaard, B. Plovsing, B. Sørensen, T.: PSO-07 F&U Project no. 7389, Noise
and energy optimization of wind farms, Validation of the Nord2000 propagation
model for use on wind turbine noise. AV 1238/09, DELTA, EMD International A/S
and DONG Energy, October 2009.
[11] Howe, M.S.
“A review of the Theory of Trailing Edge Noise”, J. Sound Vib., Vol.61, No. 3, pp.
437-465, 1978