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Irregular Wind Gust at Sitakundu of Bangladesh
Abstract:
Wind energy is a non-polluting very cost
able renewable energy source. People
extract energy from wind in various ways. In
Bangladesh it is growing very fast and
improvable methods are applying on it, the
cost of generating power has come down.
For the purpose of wind data it is collected
for one year and sorted in sequence in
appropriate frequency. The data are further
analyzed into several useful parameters,
like daily and mean monthly and mean
annual wind speed. After that, velocity
frequency bar, energy bar, velocity duration
curve graphs have been analyzed and
plotted. During analyzing, September
characteristic are unusual. This is also
analyzed for determining wind gusts and
Weibull parameters. The value of Weibull
shape factor (k) and scale factor (c) are
calculated, plotted and compared by using
different methods. The material is used
according to peak wind velocity and
equivalent pressure on rigid body and the
dynamic.
1. Introduction
Sitakundu has been developing a wind
load meteorological background to
support its standards. Its impact is one
of the major load affecting and other
construction building and transmission
pylon affected, resulting in serious
collateral damaged indifferent areas [1].
Namely, the European standards (ENV
1991.2.4, 1995; CENELEC/TC 11 (SEC) 40
1997) recommend the use of 10 min
average wind speed by the calculation of
many parameters [2]. There such data are
available for more than 3 years but not
more than 10 [3], basic for the
development of a meteorological
background. That presents a direct
application of hourly wind speed instead of
10 min average for defining maximum local
instantaneous speed. It is important to
know persistency of strong wind [2, 5]. To
define the wind condition at there the
speed of the 2 same months are compared
by day and day. Comparing the maximum
mean hourly speed and instantaneous wind
speed [4, 5]. The relationship of these two
maximum speeds has been analyzed [3,
6&7]. The analysis are based on European
standards for building European power
transmission lines.
2. Outline Of Methodology
First of all wind data is collected and sorted
in sequence in appropriate frequency. The
data is further divided into daily, hourly,
weekly, monthly and annual mean wind
speed. After that velocity frequency bar,
energy bar and velocity duration curve

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graphs are plotted and analyzed. It is
analyzed that frequency is increased on
August and September than other months.
The estimation of wind gusts based on
mean 10 min wind speed values has been
suggested to processed as follows
Vg=Kg Vmean (1)
Where Vg is gust speed (m/s), Vmean is
the mean 10 min wind speed (m s-1)
And Kg is gust factor. The gust factor is
define d as shown below;
Where
z = height above ground in meters
z0 = the roughness length in meters
That’s depends on their characteristics. At
that locations the heights above ground
z=10m. The value of roughness length,
zo=.03m. From equation two, the long wind
profile is used to be define gust.
Where k is the von Karman constant equal
to K =0.4;
U*
is friction velocity;
Z is length above the ground;
Z0 is length of roughness surface.
Where T is averaging period, g(T) is the
gust peak factor which is the function of T
and σv (z)= √βu* is the rms value of the
longitudinal fluctuating wind speed at
height z, terrain dependent coefficient is
shown by β. Eurocode uses factors of 3.7
and 3.5 for g(T). By eq 1, eq 3 and eq 4 , the
following gust factor equation is obtained;

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Where I(z) is longitudinal turbulence
intensity and it is defined as;
Eq 4, 5, and 6 indicate that constant 2.28 in
equation 2 is calculated as;
The recommended eq (1) has been
modified and the following modification has
testified;
Where Vg is a maximal gust on the day and
k is the same parameter and is a
maximal speed hour. All equations which
are derived separately for every maximal
mean hourly wind speed, have the form;
Where C is a constant and it is a mean
difference.
3. Result and Discussion
Fig. 1: Monthly Average Wind Speed
Curve
.
Fig. 2: Daily Average Wind Speed Curve
Fig. 3: Frequency Vs. Wind SpeedCurve

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Fig. 4: Instantaneous Variation of Wind
Velocity
Figure. 5: Energy Vs. Wind Velocity
Curve
Table 01; Weibull paper Method.
Location Month K C
April 2.10 4.97
May 1.90 5.03
Sitakundu,06
June 2.00 5.43
July 2.20 6.02
August 1.95 5.66
September 1.32 10.83
October 1.90 2.56
Table2. Standard Darivation
Fig. 06; Weibull Shape Factor K curve by
different Methods.
3.1 Discussion
The tables and graphs shows that the
behavior at sitakundu from August to
October is irregular than others that is clear
from figure .1. The daily average speed
curve at sitakundu is shown in figure 2.
Where hourly from August to September its
behavior is very rough and irregular as
because the speed of air is very fast and
storms are happened there this is all
happening in these couple of months. Wind
speed curve is shown in figure 3. Maximum
wind gusts is shown very clearly in figure 4.
The value of K and C is out of range in
August and September. That is all happen
Location Month K C
April 2.40 4.98
May 2.41 5.04
Sitakundu,06
June 2.32 5.43
July 3.19 4.88
August 2.09 3.47
September 1.10 2.23
October 2.19 2.57
Table 3: Energy Method

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due to irregular behavior of wind velocity
and high magnitude of wind Gust.
4. Conclusions
By studying its behavior we have made the
Coastal areas and we use good material and
we use different types of generator to
generate energy or electricity. The K and C
are determined for each month. K remains
between 1.90 and 3.19 and C remains 2.56
to 10.98. the steps can provid
e modifications. Firstly mean ten wind
speed is replaced by mean hourly as we
have replace the European scale because it
is best for large areas and to cover large
areas. In few cases it is not good it is as
locally exceptional and some other times it
shows the behavior and relationship
between gust speed and mean hourly
speed.
References
[1].“Wind Energy Resources Mapping
(WERM), 2003”, a project of Local
Government Engineering Department
(LGED) financed by United Nation
Development Program (UNDP).
[2]Choi, E. C. C. and Hidayat, F. A. (2002):
Gust factor for thunderstorm and non-
thunderstorm winds, Journal of
wind engineering and industrial
aerodynamics, 90, 1683–1696.
[3]Davenport, A. G. (1965): The
relationship of wind structure to wind
loading. Proc. of Conf. On Wind Effects
on Structeres., National Physical
Laboratory 54– 102.
[4]Chowdhury, S.C., Ramana Rao, B.V. and
Sharma P. (1981) “Performance of low-
cost Sail-Wing Windmill ”, Journal of
Agriculture Mechanization in Asia,
Africa and Latin America, Vol. 12, No.
1: pp 66-68
[5]Goyette S., Brasseur, O. and Beniston,
M. (2003): Application of a new wind
gust parameter sation: Multiscale case
studies performed with the Canadian
regional climate model – art. no. 4374, J.
Geophys. Res.
– Atmos. 108.
[6]Jungo, P., Goyette, S. and Beniston, M.
(2002): Daily wind gust speed
probabilities over Switzerland according
to three types of synoptic circulation,
Int. J. Climatol., 22, 485–499.
[7]Alam, M. M. and Burton, J. D. (1998)
“The Coupling of Wind Turbine to
Centrifugal Pumps”, Journal of Wind
Engineering. Vol. 22, No. 5: pp223-234

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Nomenclature
Symb
ol Meaning Unit
K Shape factor …
C Scale factor m/s
σ
Standard
Deviation ….
V Velocity of Air m/s
N
Total number of
hours hurs
T Total time hurs
P(v) Wind Power W
p(v)
Wind power
density W/m2
Vmea
n
Mean wind
Speed m/sec
R
Correction Co-
efficient …
Vg Gust Speed m/s
Kg Gust Factor ….
Z
Height above the
ground m
Z0
Roughness
length m
g(T) Gust peak factor ….
I(z)
Longitudinal
turbulence ….
intensity.