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The impact of turbulence intensity and atmospheric stability on power deficits due to
wind turbine wakes at Horns Rev wind farm
Hansen, Kurt Schaldemose; Barthelmie, Rebecca J.; Jensen, Leo E.; Sommer, Anders
Published in:
Wind Energy
Link to article, DOI:
10.1002/we.512
Publication date:
2012
Link back to DTU Orbit
Citation (APA):
Hansen, K. S., Barthelmie, R. J., Jensen, L. E., & Sommer, A. (2012). The impact of turbulence intensity and
atmospheric stability on power deficits due to wind turbine wakes at Horns Rev wind farm. Wind Energy, 15(1),
183-196. https://doi.org/10.1002/we.512
The impact of turbulence intensity and atmospheric
stability on power deficits due to wind turbine wakes
at Horns Rev wind farm
Kurt S. Hansen
1
Department of
Mechanical
Engineering,
Technical
University of
Denmark,
ksh@mek.dtu.dk
Rebecca J. Barthelmie
2
,
Atmospheric Science
and Sustainability
Indiana University
Bloomington
IN 47405
rbarthel@indiana.edu
Leo E. Jensen
3
DONG Energy A/S,
7000 Fredericia,
Denmark
LEOJE@dongenergy.dk
Anders Sommer
4
Vattenfall AB,
7000 Fredericia,
Denmark
Anders.Sommer@
vattenfall.com
Abstract
The wind turbine operational characteristics, power measurements and the meteorological
measurements from Horns Rev offshore wind farm have been identified, synchronized, quality
screened and stored in a common database as 10 minute statistical data. A number of flow
cases have been identified to describe the flow inside the wind farm and the power deficits
along rows of wind turbines have been determined for different inflow directions and wind
speed intervals. A method to classify the atmospheric stability based on the Bulk-Ri number
has been implemented. Long term stability conditions have been established that confirm, in
line with previous results, that conditions tend towards near-neutral as wind speeds increase
but that both stable and unstable conditions are present at wind speeds up to 15 ms
-1
.
Moreover, there is a strong stability directional dependence with southerly winds having fewer
unstable conditions while northerly winds have fewer observations in the stable classes.
Stable conditions also tend to be associated with lower levels of turbulence intensity and this
relationship persists as wind speeds increase. Power deficit is a function of ambient
turbulence intensity. The level of power deficit is strongly dependent on the wind turbine
spacing and as turbulence intensity increases the power deficit decreases. The power deficit is
determined for four different wind turbine spacing distances and for stability classified as very
stable, unstable and other (near-neutral to very unstable). The more stable conditions are, the
larger the power deficit.
Keywords: wind farms, offshore, stability, wakes, observations, power deficits.
1 Introduction
As wind farms increase in size a fundamental issue with accurately estimating power output
has been noted and may be due in part to modeling flow and wakes [1]. Wind turbine wakes
are complex and their relationship with atmospheric variables such as the variability of wind
speed, wind direction, turbulence intensity and atmospheric stability is not yet fully understood
(see e.g. [1], [2]), particularly for large arrays where the modification of the flow appears to
occur on a number of spatial scales [3]. In order to improve wind farm and wake models,
further understanding of the relationships between wakes and the atmosphere are required.
A detailed analysis of the atmospheric conditions and the flow deficit due to wind farm wakes
have been investigated inside the Horns Rev offshore wind farm in Denmark as part of two EU
funded research projects. Preliminary analysis of wake measurements at Horns Rev wind farm
were reported in [4] and in [5], an estimate of total wind farm efficiency of about 90% was
given and the importance of atmospheric stability in determining wind turbine wake losses was
stated. Recent release of two years additional data have increased the database size and
enabled an examination of wakes with a higher resolution in terms of wind speed, wind
direction, turbulence intensity and stability. While stable conditions can persist at high wind
speeds, high wind speeds tend to force conditions towards neutral, at least in northern
European waters [6], [7]. Despite the limited number of datasets, the impact of turbulence
intensity and stability on wind turbine wakes has been examined previously. For offshore wind
farms, velocity deficits tend to be larger in stable than in near-neutral conditions [3], [5], [8] and
wake recovery tends to be slower. The relationship between wind speed, turbulence intensity
and atmospheric stability offshore is somewhat complex. Turbulence intensity at turbine
heights (above 50 m) is typically less than 6% offshore and has been shown to be high at low
wind speeds and at high wind speeds with a minimum between 8 and 12 ms
-1
[8], [9]. This
implies that for wind speeds in the frequently occurring range of 8-12 ms
-1
, where wake losses
are relatively high due to high thrust coefficients, turbulence intensity can be relatively low
impacting wake recovery at these wind speeds. Conversely, at lower wind speeds when
turbines are still operating (4-8 ms
-1
) turbulence intensity may be higher at hub-height
depending on stability conditions. Recent analysis has been initiated to evaluate the impacts
of atmospheric stability and turbine spacing on the magnitude of the power deficit induced by
wind turbine [3].
2 Wind farm layout
The Horns Rev wind farm (HR) has a shared ownership by Vattenfall AB (60%) and DONG
Energy AS (40%). It is located 14 km from the west coast of Denmark as shown in Figure 1b,
with a water depth of 6-14 m. The wind farm has a rated capacity of 160 MW comprising 80
wind turbines, which are arranged in a regular array of 8 by 10 turbines. The wind turbines are
installed with an internal spacing along the main directions of 7 D, as shown in Figure 1a. The
diagonal wind turbine spacing is either 9.4 D or 10.4 D. Figure 1a furthermore illustrates the
location of the three offshore meteorological masts associated with the wind farm. Mast M2,
with a height of 62m, was installed prior to the wind farm installation to document the wind
conditions [10]. Two identical masts M6 and M7 were installed as part of the Horns Rev wind
farm wake measurements program [11] with a height equal to the hub height. The lowest cup
anemometer level is 15 m at M2 and 20 m at M6 and M7.
This analysis includes two periods each of three years; where the first period represents three
years of measurements originally used for site assessment 15 May 1999 – 14 May 2002 and
the second period represents three years of wind turbine operation 1 Jan 2005 – 31 Dec 2007.
2.1 Meteorological measurements
The Horns Rev measurement systems have been in operation for several years and not all
instruments have been calibrated or quality controlled regularly. This means that signal quality
control has been necessary and some of the procedures presented in [12] have been
implemented in this project. Below is a summary of potential problems or uncertainties related
to the instruments and observations.
Mast M2, height 62m
: The instrumentation consists of Risø high quality cup anemometers
combined with ED-vanes and has been in operation since 1999 with regular calibration and
inspections, unfortunately the signal quality has decreased during the recent years and the
data acquisition system was stopped completely at the beginning of 2007. Furthermore,
periods of wind direction measurements were erroneous from 2005 to 2007, which has
resulted in a lack of reliable wind direction measurements from mast M2.
Mast M6, height 70m
: The instrumentation consists of Risø high quality cup anemometers
combined with ED-vanes and has been in operation since 2004 with regular calibration and
inspections.
Mast M7, height 70m
: The instrumentation consists of Risø high quality cup anemometers
combined with ED-vanes and has been in operation since 2004 with regular calibration and
inspections.
2.2 Wind turbines
The wind farm comprises VESTAS V80 turbines, which are 2 MW pitch controlled, variable
speed wind turbines with a diameter of 80 m and 70 m hub height. A limited number of
channels have been extracted from the wind farm SCADA system
1
and used to investigate the
wind farm flow conditions in combination with the [external] meteorological observations. From
each wind turbine, the following data are used to describe the wind turbine operational
conditions: Electrical power, rotor speed, pitch angle, yaw position, yaw misalignment and
nacelle wind speed, registered as 10 minute statistical values. The SCADA signals are
supervised as part of the ordinary wind turbine supervision, but no reports were provided on
the SCADA signal quality.
Figure 2 illustrates how the wind turbine operational characteristics in terms of power, thrust,
pitch and rotor speed are highly dependent on the local wind speed. The manufacturer’s
power
2
curve and thrust coefficient
3
curve as function of wind speed are shown in Figure 2a.
The combined rotor speed and pitch control are used to obtain a constant thrust coefficient of
0.8 for the wind speed range 4-10 ms
-1
as shown in Figure 2b. The thrust coefficient
decreases for increasing wind speeds. The operational wind turbine characteristic in terms of
rotor speed and pitch angle depends on local wind speed, turbulence, wind direction, stability
and spacing in the wind farm and are shown in Figure 2b. Wind turbines operating in wake
conditions operate at 10-15% lower rotor speeds up to rated power.
2.3 Quality of measurements
The meteorological measurements were recorded with stand-alone data acquisition systems
and afterwards merged with the SCADA data. Since the data quality was not reported by the
data providers, it was necessary to perform quality screening of all data. The contents of this
data quality screening with reference to the signal types are listed in [11] and summarized
below:
1
Supervisory Control And Data Acquisition [SCADA] system
2
The official power curve is measured with reference to the IEC 61400-12 Power performance
measurements and used in WAsP®.
3
The thrust coefficient curve is calculated and provided by VESTAS A/S.
