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Supersize wind turbines in the US
Wind analysis
Boost data accuracy
at higher levels
With wind blades on taller turbines now spinning at more than twice the height of standard
60-metre meteorological towers, the ability to assess proposed wind plant sites with remote
sensing technology is essential. Dan Bernadett explains
aws truepower
Remote sensing Part
of a cost-effective way
to obtain accurate
wind-speed data at
greater hub heights
M
easuring wind speeds at a proposed site
to determine how much electricity will
be produced is one of the essential first
steps of developing a wind project. But,
as the size of modern turbines increases
in height and rotor diameter, it is
becoming increasingly complicated to find the right mix of
technology to measure the wind resource accurately.
Hub heights of 80 metres were once considered the
ceiling for cutting-edge turbines, but they are now reaching
100 metres and beyond. With blade tips reaching 150
metres, the days when two or three 60-metre
meteorological (met) towers would be enough to measure
potential wind resource are disappearing. But, while larger
turbines are delivering economies of scale and value,
cost-effective met towers typically end at 60 metres. As a
result, wind resource data above the 60-metre level is often
approximated by extrapolating the data available from the
lower met towers. This, however, introduces significant
uncertainty into energy-production estimates and could
affect the ability to secure finance or choose the best
turbines for the site.
Remote sensing, which uses light waves or sound waves
to measure the conditions via equipment at ground level, is
a less expensive way to capture hub-height measurements
and has the added advantage of making direct
measurements across the rotor plane.
When designing a pre-construction wind resource
analysis, a number of important factors need to be
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Mobile measurement
A single remote unit
can easily be moved
around a site
Supersize wind turbines in the US
Wind analysis
considered. It must characterise the atmospheric
conditions at the site over a range of time scales from
seconds to years, and a range of vertical and horizontal
distances from metres to kilometres. A full understanding
of the uses and limitations of the meteorological
instruments available, both fixed and remote sensing, is, of
course, essential. Equally important are the location and
distribution of the measurements collected at the site.
The general industry rule of thumb is that a minimum of
one year of data must be collected to assess seasonal and
daily effects. However, the data collected during this short
time period must then be corrected to the long-term
average. This can be done using an appropriate reference
station, such as a nearby airport or other meteorological
station, which can provide a set of wind data that can be
compared with the site-specific measurements for the
proposed wind project. Failure to do this could result in a
drastic miscalculation of its energy-generation potential.
The toolkit
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The most commonly used instrument for measuring wind
speed is the cup anemometer, which looks like a set of
spinning cups. Propeller and three-dimensional (3D)
ultrasonic anemometers are also used. The wind direction,
equally important, is typically captured with a wind vane.
The past few years have seen remote sensing grow in
popularity and it is now often employed, particularly at
sites with complex terrain or wind regimes. While it has
yet to become standard best practice, it is proving its value
in a wind resource assessment campaign, and using it to
complement traditional wind measurements from met
towers is increasingly seen as offering the most
comprehensive data set. By combining technologies, a
pre-construction wind analysis can be created that far
outweighs its cost, as the example below illustrates.
Remote sensing above hub heights
There are two primary remote sensing technologies
available to establish wind conditions: sodar (sonic
detection and ranging) and lidar (light detection and
ranging). Sodar has been used in the wind industry for ten
years or more, while the use of lidar for wind energy
applications is more recent. Both devices offer many
advantages over traditional met towers and enhance the
value of a site’s wind analysis when used in conjunction
with tower measurements.
They are capable of measuring across the entire wind
turbine rotor plane and providing the speed and 3D
direction. The remote sensors are usually portable and can
be moved throughout a site by one technician, limiting the
number of units required as well as the total cost. A mix of a
combining data sources The cost-effective option
A
s turbine hub heights grow,
meteorological (met) masts
and installation costs
increase significantly. Met towers
higher than 60 metres (200 feet)
must also apply for permitting
approval from the US Federal
Aviation Administration, which can
take 90 days to come through and
may result in a requirement to
install aviation safety lighting —
adding further to costs. Other ways
to analyse wind must be considered.
Low met towers, lower value
To provide 14 hub-height met towers
for the wind resource assessment of
a gigawatt-scale wind farm might
cost several million dollars. The
developer’s first instinct might be to
use only 60-metre towers, saving
installation costs of less than half a
million dollars. However, this must
be balanced against the reduction
of the all-important P90 value of
the project, which can significantly
affect finance.
P90 value is a pre-construction
estimation of a project’s energy
production that is 90% sure to be
exceeded. P90 and other variations
on this figure (P95 or P99) indicate
the level of risk of failing to meet
debt repayments. They are typically
assessed by the investor or lending
institution as part of the duediligence process for the loan. This
is similar to the evaluation that a
loan officer might make of a
proposed business plan when
evaluating a small-business loan.
Where there is no data at and
above hub heights, the greater
uncertainty in pre-construction
energy estimates means the P90
value might be reduced by almost
1%, making the wind site appear
slightly less attractive to lenders or
potential equity investors. This in
turn could reduce the value of a
gigawatt-scale project by several
million dollars and make it harder
for the developer to secure finance
at an attractive enough rate to
construct the project. This is like a
small business seeking a loan with a
slightly lower credit score, or a
weaker business model, which the
banker may view as representing an
increased risk or simply not an
attractive lending opportunity.
Combined approach
A smarter approach would be to
combine 60-metre and hub-height
met towers with remote sensing.
One sonic detection and ranging
(sodar) unit can be moved around
the site and placed at each of the
met towers for a period of four to
six weeks. The data from these
resources will identify the variation
of wind shear with speed and
direction across the entire rotor
plane throughout the project.
This information is typically able
to reduce uncertainty about wind
shear above the tower by a factor of
two — a developer can be twice as
certain of the average wind forces
likely to be placed on the upper end
of the rotor plane.
A few well-placed hub-height met
towers through the site could
confirm the improvement in
calculations of wind shear up to the
hub height, but only the sodar and
lidar (light detection and ranging)
units can capture the wind resource
variations across the entire rotor
plane.
Changing the hub height
Remote sensing also allows the
developer to select the turbine hub
height after the wind assessment
has begun. A site that may have
been originally conceived with
80-metre hub heights may be
upgraded to a higher-output
100-metre hub height when the site
conditions are better understood.
Such a meteorological
programme might cost less than a
million dollars, but would achieve a
P90 similar to a wind resource
analysis using only hub-height met
towers. The reduction in wind shear
uncertainty alone makes sodar
cost-effective, as it increases the
accuracy of the energy production
estimate.
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Supersize wind turbines in the US
Wind analysis
few hub-height met towers with a greater number of
shorter towers, alongside fixed and roving remote sensors,
can provide an economic means to reduce the uncertainty
in energy-production estimates for today’s larger wind
turbines. Careful configurations of this mix of technologies
can help to define the 3D wind field at the measurement
locations. These measurements can then be used to validate
models that predict the 3D wind field at all proposed
turbine locations throughout the rotor plane.
Higher turbulence
It is important to understand not only the horizontal wind
characteristics, but the vertical components as well, as they
will affect turbine performance and aerodynamic loads.
Wind shear — the variation of wind speed with height
— can often lead to a large differential in speed between the
bottom and top of the rotor. This can result in uneven
loading on the rotor and drive train of a turbine.
Wind speeds throughout the rotor plane and the
propensity for turbulence at higher elevations are factors
to consider when designing a wind project, and the forces
at work on a turbine need to be understood as accurately as
possible. Remote sensing can help a wind project developer
better understand the wind speeds affecting the entire
rotor plane, which is often well above where met tower
measurements are available.
Accurate measurements across the rotor plane may soon
be required to comply with the forthcoming version of the
International Electrotechnical Commission standard for
power performance measurement techniques. This is likely
to define the performance of a turbine by integrating the
wind-shear profile across the rotor plane.
An example of the value of remote sensing on energy
production and turbine loading can be observed in forested
Height, metres
150
Extrapolation
from met mast
Measured
data using
sodar
100
50
2.5 MW
Turbine
60 metre
met mast
9
10
0
36
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terrain (see diagram, below left). Met-tower measurements
might indicate a very high wind shear value because of the
roughness of the land around the project. So, without
remote sensing, the energy production might be
significantly overestimated. Wind turbine manufacturers
use the wind shear value to estimate the physical loads
that will be placed on the turbine. If a high shear value is
reported, the manufacturer may require a smaller rotor
diameter to control the physical loads on the machine,
resulting in lower power productivity over a given period of
time — a reduced capacity factor. In this case, remote
sensing equipment could help prevent significant
underperformance at the plant, caused by inappropriate
wind resource assessment and turbine choice.
Although wind shear is a primary driver for uncertainty in
energy-production estimates and turbine loading, other
factors come into play as hub heights and rotor diameters
grow. These include directional shear (veer), inclined flow,
turbulence and extreme winds. It is not just the mean
values for these parameters that are important, but also
their spatial range and distribution over time periods.
Additionally, episodic events, such as low-level jets (a
fast-moving ribbon of air in the low atmosphere, common
in the Midwest and eastern US), may be the defining design
factors for some sites.
Clearly, the entire wind resource assessment process
must evolve to keep pace with the move towards larger hub
heights, rotor diameters and project sizes. Developers,
meteorological consultants and manufacturers need to
work closely together to ensure intelligent design of a site’s
wind analysis, careful implementation, regular
maintenance, sophisticated modelling, and rigorous
energy-production estimates and turbine-loading
calculations. By collecting high-quality data and using it
effectively, the value of each project can be increased and
clean energy brought to the customer at the lowestpossible cost.
Within a forested area, the variations in wind speed at tall turbine hub heights are
significant; these are not captured from lower-level meteorological mast calculations
6
7
Wind speed, metres/second
Met towers Combined data provides greatest accuracy
More uncertainty with height
Remote sensing is clearer
1.5 MW
Turbine
aws truepower
“Remote sensing
could prevent
significant
underperformance
caused by
inappropriate
wind resource
assessment and
turbine choice”
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Daniel Bernadett is chief engineer, Julien Bouget is senior engineer
and James Perry is manager of project engineering at AWS
Truepower, formerly AWS Truewind