Design of Wind Turbines in an Area with Tropical Cyclones

Design of Wind Turbines in an Area with Tropical Cyclones
Niels-Erik Clausen, niels-erik.clausen@risoe.dk, Søren Ott, Niels-Jacob Tarp-Johansen, Per Nørgård and
Xiaoli Guo Larsén
Risø National Laboratory, P.O. Box 49, DK-4000 Roskilde, Denmark.
Phone +45 4677 5070, Fax +45 4677 5083.
Edmund M. Pagalilawan, pagalilawan@energy.com.ph and Samuel Hernando
PNOC-Energy Development Corporation Energy Center, Fort Bonifacio, Global City, Taguig, Metro
Manila, Philippines, Phone +632 893 6001.
Summary
The lifetime and cost of wind turbines is influenced by a combination of fatigue and extreme loads and the applied
design codes. In general wind turbines are designed for 20 years of operation using design standards which are based
largely on European conditions. In areas with tropical cyclones application of these structural design codes and the
fact that information on external conditions is limited may result in either too high cost or too high risk. The present
paper analyses the design basis of wind turbines, when applied in areas of the world where tropical cyclones occur in
certain parts of the year. Tropical cyclones are distinct different phenomena from ordinary storms and traditional
extreme wind statistics will not take into account the tropical cyclones. A method is developed to characterise tropical
cyclones and to derive the structural design wind speed (U 50 ) at a given site, based on existing and publicly available
cyclone data. An extreme wind atlas with a resolution of 1° x 1° is developed for the Northern West Pacific i.e. the
sea around the Philippines, Taiwan and Japan. Verification is in progress of the actual values in the atlas using data
from ground stations. Based on a simple model of the cost of a wind turbine the increase in cost is estimated at 20-
30% in an area with an estimated U 50 of 60 m/s compared to a site with U 50 of 50 m/s.
Introduction and motivation
Modern wind turbines are designed according to international and national standards and codes with the aim that the
wind turbine can resist the loads with a defined survival probability. These codes and standards are generally based
on European and North American conditions and do not include experience from areas with phenomena as tropical
cyclones. In principle it is no problem to design wind turbines that can survive at high wind speeds – even when hit
by a tropical cyclone. The challenge is to cost optimise the wind turbine design for sites with risk to be exposed by
cyclones. For that we need data about the characteristics of cyclones expressed in a format appropriate for wind
turbine design purposes. Moreover there is a need to modify or extend existing methodologies used in the wind
turbine design codes and standards so that the designs can be optimised to the specific wind conditions in cyclone risk
areas.
There is presently little experience with assessment of safety requirements for wind turbines situated in places where
tropical cyclones are likely to occur - like in the Philippines. The paper aims at analysing the way hurricanes or
typhoons are characterised and compare that with today’s specification of the design basis for wind turbines in order
to get a better basis for design in hurricane areas. This paper deals only with the extreme wind speeds experienced in
cyclones. In this initial work this approach has been chosen because the experience up to date shows that fatal turbine
failures in areas with tropical cyclones are almost exclusively related to the passage of cyclones. So this is the
obvious place to start in the attempt to improve structural reliability of wind turbines in such areas.
In this paper the international standard IEC 61400-1 [1] is used as main reference, as it is expected to be gradually
accepted world wide. The design philosophy of IEC 61400-1 is not significantly different from most other current
wind turbine standards. Most current wind turbine standards include load cases for operational conditions and
extreme environmental conditions. In order to simplify the specification of the wind turbines and to make the
standard operational a number of wind turbine classes are defined that specifies standardised wind conditions. The
design of wind turbines are determined by a mix of fatigue loads, loads from extreme environmental conditions (i.e.
storms), and extreme loads during operation which is expressed in terms of both deterministic and random process
wind conditions. It might be that extreme operational gusts and other operational conditions defined in the standards
will not apply to areas with tropical cyclones. The IEC 61400-1 states clearly that, “The particular external conditions
defined in classes I, II, and III are neither intended to cover offshore conditions nor wind conditions experienced in
tropical storms such as hurricanes …”. Therefore it cannot be expected that designs made according to the IEC
61400-1 will ensure sufficient structural reliability of turbines in regions of the world, where tropical cyclones occur.
National building standards cannot be applied to wind turbine design either. Local standards will of course account
for the severity of tropical cyclones where relevant, but they will most likely miss load cases important for wind
turbine design because they are typically limited to structures that can be assumed to behave statically in response to

European Wind Energy Conference, Athens, 27 February – 2 March 2006
wind loads. The fact that wind turbines are equipped with a control and safety system leads to a lot of different
considerations to be made regarding the possible malfunction of the control system, e.g. in consequence of grid loss,
and the demands on structural strength in case of such malfunctioning of the control and safety system. IEC 61400-1
has several crucial load cases that address these issues.
The Philippines lies in the northwest Pacific and is thus prone to tropical cyclones – called typhoons in this area. On
average, 19 out of 22 tropical cyclones forming in the area annually enter the ‘Philippine Area of Responsibility’.
Typhoons typically hit Samar and Bicol provinces in the eastern part of the country and travel west or northwest. In
cases where it takes a western path, Southern Luzon is the area mostly affected. Where it travels northwest, the areas
of eastern and north-eastern Luzon are almost always in the receiving end of strong winds and heavy rainfall. This is
mainly attributed to the Cordillera mountain range dividing eastern and western Luzon.
The National Structural Code of the Philippines (NSCP) has taken the frequency and strength of the typhoons passing
through the Philippines and integrated this to the design limits for structures in the country. The country is divided in
three zones (Fig. 5 - right), where zone 1 is the most severe. Comparing the extreme wind speed specified in the
NSCP and IEC 61400-1, it will be noted that NSCP Zone 2 (west of the Cordillera) would require Class 1 wind
turbines and Class S for areas in Zone 1 (east of the Cordillera).
So far, Northern Luzon is identified as having the best wind resource in the country. The first wind farm constructed,
NorthWind Power Development Corporation’s 25 MW Bangui wind farm, is located in the town of Bangui, Ilocos
Norte, within Zone 2. It was commissioned between the 2 nd and 3 rd quarter of 2005 and has so far experienced two
typhoons. PNOC Energy Development Corporation’s 40 MW Northern Luzon Wind Power Project – Phase 1
(NLWPP 1) in Burgos, Ilocos Norte is about 10 kilometers west of the Northwind project and is similarly within
Zone 2. PNOC EDC is also looking at developing the 46 MW NLWPP 2 (between Bangui and NLWPP 1) and the
40 MW Pagudpud Wind Power Project in the town of Pagudpud, approximately 30 kilometers from Burgos.
So far, all major wind power projects in the Philippines are located in Zone 2 areas, including the San Carlos Wind
Power Project in Negros Oriental and Trans-Asia’s Sual Wind Power Project in Pangasinan. This is generally
attributed to the following factors:
• Lack of reliable wind data
• Expected high investment costs
• Risks associated with typhoons
A collaboration between Risoe National Laboratory, PNOC-EDC, IED and Mercapto, is currently investigating the
feasibility of developing wind farms in Zone 1 areas under a grant provided by the EC-ASEAN Energy Facility. A
meteorological mast was erected in Sta. Ana, Cagayan (Zone 1) in 2005. The conclusion from this on-going study
aim at providing the parameters, at which a wind farm project could become feasible even with the risks of typhoon.
The cyclone challenges may be handled in different ways. One way is design the wind turbines to cope with the
environmental conditions; another way is to try to protect the wind turbine by lowering the wind turbine, while the
cyclone passes. This is an option for smaller wind turbines only, and the procedure requires i) that the wind turbine is
prepared for easy and quick lowering and ii) that the wind turbine is lowered in due time before the wind speed
becomes too high for safely lowering. There are several problems related to this procedure. In case of a cyclone
warning, the skilled staff originally appointed to carry out the lowering of the wind turbines may have to prioritise
their time and effort between various items to secure – including their families and personal belongings. Because the
wind turbines for both personal and equipment safety reasons must be lowered while the wind speed is (still) low and
in order to be sure that the wind turbines always have been lowered in case of a cyclone pass, this will necessarily
lead to some unnecessary lowering operations and many operational hours will be lost. Tropical cyclones are always
accompanied with heavy rain, and access to the wind turbine site may become difficult. Even when the wind turbines
are lowered and secured they may be damaged by flying objects in the strong wind.
In a number of Pacific Island Countries in the South Pacific Region they have experiences with the 20 kW Vergnet
wind turbine and this tilt-down procedure, and the general experience is that in practice the decision of lowering the
wind turbines always comes too late for a safe operation and that the skilled personal at that time are very busy with
securing other things. At Viti Levu in Fiji the national utility company Fiji Electricity Authority (FEA) is presently
constructing a 10 MW wind farm consisting of 37 of 275 kW Vergnet wind turbines. An organisation with a cyclone
warning system will be established and teams of local staff will be trained in lowering and securing the wind turbines.
The aim is to be able to lowering all wind turbines within 10 hours. This project will be an interesting full-scale test if
the procedure is a realistic approach.
The present work will focus on developing a method for design of large commercial wind turbines for areas with
tropical cyclones.
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European Wind Energy Conference, Athens, 27 February – 2 March 2006
Tropical cyclones
Figure 1: Examples of satellite images of fully developed tropical cyclones.
Tropical cyclones are common in the northern West Pacific, in particular around the Philippines and Japan, where
they cause much damage to life and property. In this section we outline a simple and practical method to derive
extreme wind statistics from available meteorological information, for a more detailed discussion we refer to Ott [2].
The aim is to estimate the wind speed with a recurrence of 50 years (the fifty year wind) U 50 at any given location.
The method is applicable to regions where extreme winds are caused by tropical cyclones.
Cyclones are circulating, low pressure wind systems. A tropical cyclones (TC) has a warm centre surrounded by
relatively colder air and, contrary to extra-tropical cyclones, there have no fronts. The energizing mechanism in TCs
is the condensation of water vapour supplied by sufficiently hot sea surface. Rising, humid air causes the formation of
intense, local thunderstorms which tend to concentrate in spiral shaped rain bands. In case of landfall the supply of
water vapour is cut and the cyclone deteriorates fast, but it can still endanger a zone along the coastline several
hundreds of kilometres wide. The central region is covered by a dense overcast, but just at the centre there usually is a
circular spot, the 'eye', which is free of clouds. Inside the eye wind speeds are moderate. This is in contrast to the edge
of the eye, the eyewall, where maximum wind speeds are found. Figure 1 shows a few satellite pictures of typical,
fully developed tropical cyclones. The circulatory motion results from a balance between the centripetal acceleration,
the radial pressure gradient and, to a lesser extent, the Coriolis force and surface friction. The velocity generally
decreases with height because the pressure gradient decreases. Near the surface the friction takes over causing the
opposite trend so that the velocity has a maximum found typically at an elevation of about 500m. Below the velocity
maximum friction makes the wind turn towards the centre, but near the eyewall it is caught by a vertically spiralling
jet extending 5-10~km up into the troposphere. At the top the jet 'spills over' and splits into an outgoing jet and a jet
going back into the eye. The air inside the eye is therefore generally subsiding (descending) and flowing out towards
the eyewall along the surface. This explains why there are no clouds in the eye.
The dimensions of the primary vortex (overall circulation) can be quantified by the eyewall radius R w which is
typically about 50km. Occasionally the primary vortex is overlayed by smaller meso-vortices which are a few
kilometres wide. Meso-vortices are found in region near the eyewall and can give rise to local enhancement of the
wind speed with rapidly changing wind direction. Some TCs even spawn tornados. These are even smaller vortices,
about 100-300m in diameter, which are generated by wind shear. Most tornados are found near the cost where a TC
3

European Wind Energy Conference, Athens, 27 February – 2 March 2006
makes landfall and they are not confined to the eyewall. A tornado on top of a TC has devastating effects, but due to
its smallness chances of being struck by a tornado inside a TC is relatively small. According to Novlan and Gray [3]
about 25% US hurricanes spawn tornados and in these the material damage caused by tornados amounts to less than
half a percent.
The mechanisms that control tropical cyclone genesis are not fully understood, and there is no explanation of why
typhoons are particularly frequent in the western North Pacific. It can be shown that tropical cyclones cannot form
unless the sea temperature exceeds 26°C, but this appears not to be the only condition for formation. In fact there are
major parts of the tropics, with plenty of warm sea, where tropical cyclones never occur. These include the Eastern
South Pacific, the South Atlantic and a ten degree wide strip around the Equator.
Best tracks
Tropical cyclones are monitored closely by meteorologists both at national and international levels. Regional warning
centers are organized by the World Meteorological Organization (WMO) in the framework of the World Weather
Watch (WWW) Programme. Analyses and forecasts of tropical cyclones in the western North Pacific are provided by
the RSMC Tokyo-Typhoon Center, which is operated by the Japanese Meteorological Agency (JMA). Independent
forecasts for the region are made by the US navy at the Joint Typhoon Warning Center (JTWC) on Hawaii. Historic
typhoon data are available from these two sources in the form of so-called 'best tracks'. These are constructed on the
basis of all available information, 'hindcasting' rather than forecasting. The amount of detail given in track records
vary, but as a minimum they contain the center position and the central pressure (at sea level) at 6 hours intervals.
The JMA track records cover all tropical cyclones north of the equator in the region between the 100E and 180E
meridians (the western North Pacific and the South China Sea) for the period 1951-2004. From 1977 onwards the
'maximum sustained wind' representing the maximum ten minute average wind speed measured ten meter above
surface is also given as well as the radii to 50 knot and 30 knot wind speeds (also ten minutes averages at ten meter).
The JTWC tracks contain central pressures and positions for the period 1945-2003. For 2001-2003 the following data
are also included: ambient pressure (at the last closed isobar), radius to the last closed isobar, maximum sustained
wind, radius of maximum wind and radius of 34 knot surface wind. Positions are given to the nearest tenths of a
degree, wind speeds are usually rounded to the nearest five knots (i.e. 35,40,55 knots) and distances to the nearest 5
nautical miles. This should not be taken as an indication of the degree of uncertainty of the numbers.
The amount and quality of the information on which the best tracks are estimated is varying. There are generally few
conventional surface observations to rely on since met stations, platforms and buoys are relatively scarce in the
oceanic region. Velocities at ten meter elevation are therefore inferred from other data. These include satellite
pictures, reconnaissance aircraft, radar and radiosonde observations. Of these the reconnaissance aircraft data are the
most detailed, but have not available for the NW Pacific since 1987, where US military reconnaissance ceased. Most
of the best track data is gained by satellite image interpretation using the Dvorak [4], [5] and [6] method, and listed
central pressures and the maximum sustained wind speeds are in fact rarely, if ever directly measured.
The JMA best tracks for the period 1977-2004 to were used for the extreme wind analysis since they contain size
information.
The Holland model
Fig.2 Schematics of the Holland velocity profile.
Holland [7], see also Harper & Holland [8], proposed a simple tropical cyclone model, which we have used to
interpret best track data. The model is based on the gradient wind V g which is defined so that the radial component of
the acceleration balances the pressure gradient and the Coriolis force:
4

European Wind Energy Conference, Athens, 27 February – 2 March 2006
2 r ∂P
Vg = − frV g
ρ ∂r
(1)
where f is the Coriolis parameter and ρ is taken to be constant (=1.15kg/m 3 ). Investigations by Willoughby [9] show
that gradient balance indeed exists at the flight levels of reconnaissance aircraft. When the surface pressure gradient
is inserted, V g corresponds to a wind that would have been in the absence of friction. In figure 3, reproduced from
Franklin, Black and Valde [10], it corresponds to neglecting the lower 500m and extrapolate the upper part of the
profile to the surface. Thus the ratio K m between the surface wind at 10m and the gradient wind can be read from the
plot. Very conveniently we find K m = 0.7 both at the eyewall and at the outer edge, so this values is taken to be
representative for the whole profile. It is in reasonable agreement with Harper [11] who suggests K m = 0.7.
Figure 3. Hurricane wind profiles measured with dropsondes. From Franklin, Black and Valde [10].
Holland proceeds by prescribing the pressure profile:
P r)
= P
c
+ ( P
n
⎡ ⎛
− Pc
) exp⎢-
⎜
⎣ ⎝
5
R 0
( (2)
where P c is the central pressure, P n is the ambient pressure defined e.g. as the pressure corresponding to the last
closed isobar, R 0 is a characteristic length that essentially coincides with the eyewall radius R w , and B is a
dimensionless shape parameter. Holland found good agreement with data using this parametrization.
The JMA track data list R 50 , the radius to 50 knots wind speed, the central pressure P c and the maximum sustained
wind V max at 10m. The ambient pressure P n is unknown, but it is conventional to adopt the value P n = 1010 hPa in the
NW Pacific. Using ρ =1.15 kg/m 3 and K m = 0.7 we can determine the model parameters B and R 0 .
A comprehensive validation of Holland's model was made recently by Willoughby [12] who compared it with aircraft
measurements of almost 500 hurricane cases. Although the validation left some room for improvements, the model
performed quite well. Fitted model wind speed profiles reproduce measurements within an rms error of 4 m/s.
Statistical methods
In order to estimate the fifty year wind U 50 at some given location we use the best track data and the Holland model
to estimate the maximum wind for each of the typhoons that passed. Only wind speeds exceeding the cut-off value
U cut = 50 knots = 25.7 m/s are kept and from these values a set of annual maxima is formed. 50 knots is the wind
speed limit used by JMA to qualify a TC as a typhoon. If the maximum wind speed is less than 50 knots, R 50 , has no
value and a Holland wind profile cannot be estimated. Thus the data is censured and there is not necessarily a
maximum for each year. In case an annual maximum is missing we have found it convenient to assign the cut-off
value. Following convention we assume that the annual maxima are independent and follow a Gumbel distribution:
⎡ ⎡ V - β ⎤⎤
(V ) = exp⎢−
exp
⎢
-
⎥⎥
⎣ ⎣ α ⎦⎦
r
F (3)
Where α and β are the two Gumbel parameters. Due to the censoring and the assignment of the value U cut to missing
values we have F(V)=0 for V< U cut . It can be shown that the fifty year wind can be determined as
⎞⎤
⎟⎥
⎠⎦

European Wind Energy Conference, Athens, 27 February – 2 March 2006
U
50
= β + α log 50
(4)
In order to determine α and β from data we use a variant of Abild’s [13] method suitable for censored data. More
details are given in Ott [2], where the method is tested by Monte Carlo simulation and found superior to the
traditional Gumbel plot method. One major advantage of the method is that it allows the Gumbel parameters to be
estimated from annual maxima from a group of locations rather than all complying with the same Gumbel
parameters, even if the annual maxima at different locations are correlated. In practice a square mesh of observation
points with one-by-one degree cells is made and groups of 9 points, covering two-by-two degree squares, are used for
the analysis. The estimated Gumbel parameters vary smoothly with position.
Figure 4 shows the result of the analysis. It should be noted that the U 50 values correspond to ten minutes average
wind speeds measured ten meter above a sea surface, even at locations that are actually over land. Much of the red
area, with U 50 ,< 35m/s, is actually never hit by typhoons so the analysis does not apply there. The ‘typhoon ally’
between Japan and the Philippines is prominent. Figures 5 shows a close-up of the Philippines (left) along with a map
taken from the Philippine National Structural Code (right). The code defines the fifty year wind speed in terms of a 3
second gust (10 m over land) so the numbers are not directly comparable. However, the general shape of the zones in
the two maps is consistent.
Figure 4. Extreme wind atlas for the NW Pacific from typhoon track data (left). The numbers indicate
intervals in m/s (e.g. the green area covers 45-55 m/s). Right is shown the extreme wind atlas derived
from NCEP/NCAR data.
Figure 5. Left: close-up of the Wind atlas (as in Fig. 4-left). Right: Wind zones according to the
Philippine National Structural Code [16].
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European Wind Energy Conference, Athens, 27 February – 2 March 2006
Impact on design basis
The fundamental question to answer when deciding what should be the consequence of tropical cyclone conditions on
design requirements is if it is at all economically feasible to design turbines to survive such cyclones. In this paper
this question is not addressed in detail, however a simple model for construction costs is put up that would be helpful
in the evaluation of feasibility. There are two main concerns regarding extreme loads in tropical cyclones:
What should be the safety factor to associate with the 50-yr wind speed?
What should be the demands to the control and safety system?
To take the later first; should that case occur that the eye of the cyclone passes over the turbine site the demands on
yaw speed can potentially be high because of the possibly steep descent of the wind speed as one crosses though the
eyewall into the eye. After that follows a 180° change of wind direction as the eyewall on the other side of the eye
approaches. The change in wind direction can be rather drastic if the wind speed grows rapidly close to the eyewall.
Initial investigations of the issue has been made that seem to indicate that the controls of modern wind turbines can
keep up with the wind direction change as long as they are powered.
The first concern listed relates to the level of structural safety provided that the control and safety system performs as
required. This is ensured through the specification of the characteristic wind speed, which is the 50-yr wind speed in
the IEC 61400-1, in combination with the safety factor. The safety factor is needed to provide higher reliability than
what is implied simply by designing to survive the 50-wind speed. Said heuristically the purpose of the safety factor
is to ensure design can survive loads of a longer return period than 50 yrs, say 1500 yrs. That it, said quite
simplistically that the load factor is in a certain sense the ratio of the 1500-y r load to the 50-yr load. Having this
simplistic understanding in mind it is obvious that climates with higher variability of extreme wind speeds than others
must have higher safety factors if the same reliability is desired. In the following we will demonstrate that this is
indeed the case for the typhoons passing the Philippines relative to the North European climate and similar climate
which have been prime concern in the formulation of IEC 61400-1. So, there are two parameters that govern design
loads: 50-yr wind speed that signifies the level of extreme wind speeds and the load factor that accounts for the
inherent variability of the extreme wind speeds. The variability will in the following also be termed uncertainty,
because it represents the uncertainty the designer has regarding the likeliness that the structure will not survive
extreme wind speeds. In the following sections a preliminary investigation of the need for change of safety factors if
a level of reliability level similar to that intended in the IEC 61400-1 should be demanded in the Philippines. It is
stressed that this work rests on the approach to extreme value statistics in typhoons described in the previous parts of
the paper. This work must be verified against ground measurements before the conclusions reach below can be
considered to be solid. For instance it is noted that the uncertainty in determination of pressure etc. from satellite
images is considerable, and may well exceed what can be covered by safety factors. First a simple reliability
assessment for a typical North European environment is considered. Next the Philippine typhoon environment is
considered leading to the calibration of the load safety factor.
The reliability assessment consists in an evaluation of the probability of structural failure. To this end one needs an
equation for the failure limit state, a probability model describing the probability distributions of all relevant variables
influencing the reliability, i.e. wind speeds, material strengths, and model uncertainties. Further one need to define
characteristic values for materials and for loads (i.e. the 50-yr mean wind speed), and one needs the relevant load and
strength safety factors. The model assumption made here has been adopted from [14] (of which a short presentation is
given in [15]). The reader is referred to these references on the details of the model. Applying this so-called
Davenport model the failure limit state is expressed as
2
fy = cinfUhub (1+
2 kpIcamp
)
1 42443
c
dyn
(5)
where the factor c inf is an influence number relating the load to the product U 2 c dyn of the mean wind pressure and the
dynamic response factor. The influence number depends on the design of the turbine; among others c inf depends on
the geometry of tower and the blades, and the lift and drag coefficients. It also accounts for the air density ρ. The
factor c dyn is the dynamic response factor given by the peak factor k p , the along wind turbulence intensity I 1 , and the
factor c amp which accounts for dynamic amplification and for admittance. Because the admittance depends on lift and
drag coefficients, c amp depends on the design of the turbine just like c inf does. Finally the peak factor depends on the
response frequency f 0 implying that k p depends on the design too. The expression in Eq. (5) is believed to represent
well the tower bottom response but it is not necessarily well-suited for blades. Finally f y denotes a generic material
strength. It turns out after some manipulations that the reliability can be expressed by
1+
X T
Pr{survival} = Pr{ γ γ ≥
}
2
2
dyn
m fFX
%
y m
U% XEa
(6)
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European Wind Energy Conference, Athens, 27 February – 2 March 2006
In this expression the material strength has been substituted by its random variable counterpart and normalised by its
characteristic value. Likewise of the mean wind speed U. An additional three uncertainty variables, X m , X Ea , and X dyn
have been introduced to account for uncertainty in modelling of material strength, uncertainty in modelling of wind
loads, and uncertainty in modelling of dynamic response, respectively. Further the uncertainty related to the statistical
estimation of extreme wind speeds etc. has been included in the mean wind speed variable U. Finally the safety factor
γ f and γ m for loads and material strengths, respectively, are there too. The distributional assumptions are listed in
Table 1. It is noted that for the European environment it is the distribution of the mean wind speed squared i.e. the
mean wind pressure that is assumed to be Gumbel. For the typhoon climate it is the mean wind speed that is assumed
Gumbel distributed. This may limit the possibilities of comparing the reliabilities evaluated in the two cases, and it
may underestimate the reliability for the typhoon case. In other words the safety factor arrived at in the typhoon case
may be too large. It is noted that the coefficient of variance of the squared mean wind speed for the European
environment is similar to the coefficient of variance for the mean wind speed in the typhoon case. This reflects the
higher uncertainty of the extreme winds generated by typhoons.
Table 1: Distribution assumptions for uncertainty model
Name Description Type Bias CoV
U %
Europe: Annual max 10-min mean wind squared
and normalized by characteristic value
The Philippines: Annual max 10-min mean wind
normalized by characteristic value
Char.
value
Gumbel 1.00 32% 98%
Gumbel 1.00 31% 98%
X Ea Model uncertainty, aerodynamic loads Lognormal 1.00 10% Mean
T Normalized extreme turbulent response Gumbel 1.00 10% Mean
X
dyn Model uncertainty Lognormal 1.00 5% Mean
F % y
Normalized yield strength Lognormal 1.13 5% 5%
X m Model uncertainty, resistance Lognormal 1.11 8.5% Mean
Calibrating now leads to the conclusion that a load safety factor of 2 is required if the same reliability shall be
obtained in the typhoon case as in the case of a European climate. As explained, the fundamental differences in the
uncertainty models applied for the European and the Philippine environment implies that it may be assumed that a
safety factor for the typhoon condition may be in the range from 1.7 to 2.0.
If it is decided to aim at survival of turbines in cyclones up to certain strengths a special wind turbine class should be
devised that defines 50-yr wind speed and safety factors. The authors are aware that steps are taken in Japan to
address problems similar to those discussed here – also in the framework of IEC 61400-1. The Japanese code
committee seems to aim at increasing 50-yr wind speed and probably the load factor as well and define a special
Japanese wind turbine class. They are also considering including effects from strong lightening in Japan.
The paper provides a very simple cost model for an evaluation of the cost increase in relation to an increase in
extreme wind speed. It is assumed that the consequence of failure will be purely monetary, i.e. it is assumed that there
will be no human fatalities and no pollution related to a turbine collapse. The assumption of no human fatalities
seems fair, since it is unlikely that people should deliberately come close to wind turbines in case of typhoons. Such a
simplified model may be used in a consequence-of-failure assessment relevant in e.g. feasibility studies. If grid
connection costs are disregarded, the substructure and foundation contribute about one sixth of the total costs and the
turbine is responsible for the remainder. For the turbine; the rotor, the nacelle, and the tower each contribute about
one third of the costs. The rotor-nacelle-assembly is basically limited by fatigue, while approximately one half of the
tower costs are assumed driven by extreme loads, and half of the substructure/foundation costs are assumed driven by
extreme loads. The extreme load driven costs are assumed proportional to the load which is proportional to the square
of the mean wind speed and the load factor. With these simplifying assumptions the relative cost change due to
changes in extreme mean wind speed becomes approximately
2
3 1 V γ
f
+ (7)
4 4V
γ
2
ref
8
f ,ref

European Wind Energy Conference, Athens, 27 February – 2 March 2006
2
The product V ref γ f,ref is the typical mean wind speed and safety factor currently used in design of Class IA turbines,
i.e. 50 m/s and 1.35. The alternative mean wind speed and load factor are denoted V and γ f , respectively.
In Northern Luzon the increase in 50-yr wind speed from 50 m/s to 60 m/s and the increase of the load factor from
1.35 to 1.7-2.0 yields with the model in Eq. (7) a relative cost increase in the range from 20% to 30%. Though it is
well-known that O&M costs are important in the estimation of the lifetime costs, an investment increase of 20% to
30% is a challenge. These preliminary results have to be treated in a more detailed investigation, where also the
uncertainty model is updated.
Conclusions
A systematic and detailed analysis of 28 years of typhoon tracks leads to significantly higher U 50 values than the
traditional estimation from NCEP/NCAR database in the Northern West Pacific (Fig. 4). This is in line with the
general understanding that tropical cyclones (in this area called typhoons) is a unique phenomena different from the
normal wind climate, but attributes also to the course resolution of the NCEP/NCAR database.
Comparison of track data from JMA and JTWC reveals differences of more than 40% in the maximum wind speeds
for the most severe typhoons during the three years (2001 to 2003), where data are available from both sources for the
same typhoons in the Northern West Pacific [2].
A design philosophy is applied that aims at ensuring the same structural reliability in typhoon areas as is implied by
the IEC 61400-1 for north European environmental conditions. The result is an increase in load safety factor from
1.35 in Europe to about 1.7 to 2.0 in typhoon areas. Together with the increase in the 50-yr wind speed from 50 m/s
to 60 m/s the increased load factor leads - with the model in Eq.(7) - to a relative cost increase in the range from 20%
to 30%. Though it is well-known that O&M costs are important in the calculation of the lifetime costs an increase of
20% to 30% can be a challenge. This will be the topic of a more detailed investigation, where also the uncertainty
model is updated. It is emphasised that verification against ground measurements of the extreme wind statistics
applied here is crucial for the validation of the results presented. The inherent uncertainty in the interpretation of
satellite images used to determine the typhoon characteristics used here can be considerable compared to the load
safety factor. Preliminary investigation of the best track data and the changes in wind direction during the passage of
a typhoon suggests that changes in the wind direction can be handled by today’s yaw controls. This means that
backup power to the wind turbine control and yaw systems is essential to cope with the change in wind direction
during passage of the typhoon, where the grid connection is often lost.
If on the other hand it could be accepted that wind turbines should not survive a severe typhoon it might be that a load
safety factor below 1.35 as recommended in IEC 61400-1 is feasible. This should be a subject of further research.
This initial study considers the influence of extreme loads under standstill only. It must still be kept in mind that
fatigue and operational loads are design driving too.
Acknowledgements
The work presented is part of the project Feasibility Assessment and Capacity Building for Wind Energy
Development in Cambodia, the Philippines and Vietnam. The project is financially supported by the European Union
through the EU-ASEAN Energy Facility in Jakarta.
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European Wind Energy Conference, Athens, 27 February – 2 March 2006
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Abbreviations
JMA
JTWC
NCEP/NCAR
RSMC
TC
U 50
Japanese Meteorological Agency, Tokyo
Joint Typhoon Warning Centre, Hawaii
Database of reanalysis weather data by National Centres
for Environmental Prediction and National Centre for
Atmospheric Research
Regional Specialised Meteorological Centre
Tropical cyclone
Extreme wind with a recurrence period of 50 years
10