ISSN: 2394-6881
International Journal of Engineering Technology and Management (IJETM)
Available Online at www.ijetm.org
Volume 2 Issue 2 Page No. 80-85
Analysis and Reliability Evaluation of Wind Turbine Generators
1
2
2
Bindhu L., Prof. K R Mohan, Prof. Satyanarayana Rao R D
1
P.G scholar, Department of Electrical and Electronics Engineering, AIT, Chikkamagaluru, Karnataka, India.
2
Department of Electrical and Electronics Engineering, AIT, Chikkamagaluru, Karnataka, India.
Email- bindulokesh92@gmail.com
Email- mohanhnpur@gmail.com
Email- shreyasrangadhol@gmail.com
ABSTRACT
Wind power generation is the most promising renewable energy and it is increasingly attractive to power industry and
the whole society. Wind energy is available everywhere in abundance, tapping this energy and utilizing it optimally is the
need of the day. Hence the optimal utilization requires some process. In this paper reliability evaluation of wind power
generation system is carried. The system reliability shows the availability and the power generation model. In this work
the basic system reliability indices are calculated. Historical data collected over one year is used for the evaluation. For
the data analysis excel data analysis tool is used and probability distribution of the wind speeds are calculated. This work
presents the reliability evaluation procedure for wind power generation system. This study shows the system availability
for the generation of power from wind turbine generators installed at the Harapanahalli near Davanagere of Karnataka
state.
Keywords: WTG, Reliability evaluation, Probabilistic model, wind energy.
Bindhu L., IJETM Volume 2 Issue 2 Page No.80-85
The most popular generation reliability index[1] is the loss
of load expectation (LOLE). In addition to this index,
Expected energy not supplied (EENS) and Energy Index of
Reliability (EIR) are used. The energy not supplied can be
found using the technique in which each state of the
capacity model Ck, the energy not supplied Ek is given
numerically by summing all positive values of (Li - Ck)
.where Li is the i-th load level and i=1 to n. The expected
energy not supplied is given in the equation 1.
Wind Power Generation System
Renewable energy sources, particularly WTGs, are
considered as important power generation alternative in
electric power systems due to their un exhausted nature
and being environmental friendly. The fact that wind
80
1.1 Generation System Reliability Studies.
In the generation system the total system generation is
evaluated to find the system adequacy to meet the total
system load demand. The system model in generation is
shown in the figure 1.
Figure 1: Generation system reliability model Reliability indices
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INTRODUCTION:
The basic function of a power system is to supply the
customer demands in both small and large within the
economic limits in an acceptable reliability and quality[1].
To satisfy this, power system should also remain in the
operational conditions. In the modern living status energy
should be continuously supplied to the consumers.
Particularly in Indian electricity sector there is a huge gap
between power supply and demand. To overcome this
crisis Indian government released some energy policies
regarding electricity supply to all. And also released rural
electrification policy 2006, this policy aims at providing
electricity to all households. To meet this criterion the
probabilistic evaluation of the system has to be carried. In
other words reliability evaluation has to be carried on the
system availability and the amount in which the power is
generated. In this work reliability evaluation of wind
power generation system is carried to obtain the
availability of the system to generate power form variable
wind speed.
Bindhu L., et al. International Journal of Engineering Technology and Management (IJETM)
2.2 Data Analysis
E cel data a al sis tool is used for the data a al sis.
The purpose of this tool is to analyze the wind data to
prove a wind resource exists at a specific location. The
spreadsheet is a program to create a Wind Rose graph,
and also a folder containing power curves for various
wind turbine generators. The data provided by wind farm
are used as an input to the tool. Some important
parameters calculated by the spreadsheet are the
average wind speed, estimated annual production, and
the capacity factor. A report sheet is also included, which
© 2015 IJETM. All Rights Reserved.
Wind speed statistics[2]:
The speed of the wind is continuously changing with the
time, making it required to define the wind by statistical
methods. One statistical quantity which is the average is
calculated by a set of measured wind speeds ui. Standard
deviation is calculated by the variance.
Average wind speed:
The measured wind speeds are in integer values, so that
each integer value is observed many times during a year
of observations. The numbers of observations of a
specific wind speed ui will be defined as mi. The mean is
then given by the equation 3.
Where, w is the number of different values of wind speed
observed and n is the total number of observations.
Standard deviation: To find the deviation of each number
from the mean and then find some sort of average of
these deviations. The mean of the deviations (ui – u) is
zero, which does not indicate much. Therefore to get all
positive quantities square each deviation. The variance of
the data is then given by the equation 4.
Where, w is the number of different values of wind speed
observed and n is the total number of observations.
Standard deviation is given in the equation 5
Frequency of occurrence: This is the determination of the
number of times in which the recorded wind speed
occurred through the measured time. The percent value
is given by the equation 6.
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2.1 Collection of Data
For the evaluation process the data is obtained from
Harapanahalli wind farm site. It consists of hourly basis
average wind speed, standard deviation and wind rose
data. Wind rose data is the data consists of wind direction
with respect to north and it is considered as 0o. Wind
data is available in hourly basis through the year
measured by the anemometers installed at the site
location. These data are obtained directly from the wind
site through the anemometer. The wind site data and
turbine data are obtained from the installed turbine
manufacturers. Those data are available in the turbine
manufacturer web site. Wind site data contains
geographic information about the wind site, turbine
power curve, swept area, capacity of the installed
turbine.
summarizes results and displays graphs.
2.3 Wind Speed Model for Selected Geographic Location
This is the estimation of wind speed model for the
specific geographic location. In this step the wind speed
model is developed by calculating the average and
standard deviation of the discrete wind speeds. With this
model frequency of occurrence and probability of the
wind speed in that specific site can be obtained. This
model also gives the probability distribution of the
discrete wind speeds.
Page
power contribution continues to increase has motivated a
need to develop more widely applicable methodologies
for evaluating the actual benefits of wind turbine
generating systems. Reliability evaluation of wind turbine
generating systems is a composite process. It needs an
accurate wind speed predicting method for the wind site.
The method involves historical wind speed data collected
over many years for the wind farm location to determine
the necessary parameters of the wind speed models for
the actual site. The estimation process should also exactly
model the irregular nature of power output from the
wind farm. In the evaluation process, there are many
steps involved. This work includes nine steps for
evaluation process which are listed below.
1. Collection of data
2. Data analysis
3. Wind speed model for selected geographic location
4. WTG power curve data
5. WTG power generation model
6. Probabilistic evaluation of power generated
7. Three state model for WTG system
8. Evaluation of Capacity factor and Availability
9. Calculation of reliability indices
Bindhu L., et al. International Journal of Engineering Technology and Management (IJETM)
The power generated can be calculated using the power
formula given in equation 8. A detailed explanation is
given in reference [4] to obtain the power equation for
the wind turbine. It can also be calculated by WTG power
curve.
2.4 WTG Power Curve Data:
This is the data obtained from the turbine
manufacturers[3] installed at the wind site. This data
contains the power output of the wind turbine generator
at different wind speed and the rated wind speed for the
rated power output, cut-in wind speed, cut-out wind
speed of the wind turbine. This can be represented in the
graphical form by plotting wind speed on x-axis and
power output on y-axis. These power curve data is
combined with the wind speed model obtained for
specific wind site to obtain power generated at different
wind speeds distributed through the year.
2.5 WTG Power Generation Model:
Wind turbine power generation model is obtained by
combining the wind speed distribution and wind turbine
generator power curve data. This model includes the
total annual power generated; power generated at
different wind speeds through the year. This is calculated
by combination of 2.3 and 2.4 subsections.
The probability P of the discrete wind speed ui being
observed as,
Where, Cp is the capacity factor given by the turbine
manufacturer
ρ is air de sit at the wi d site kg/
A is area swept by the turbine in m2 u is the wind speed
in m/sec
2.7 Three State Model for WTG System
The output of a wind turbine generator (WTG) is a
function of the wind speed. In this work the WTG is
represented by a three-state model. State Up1, State Up2
and State Down are three states, which represent
variable, constant and no outputs, respectively, in terms
of wind speed variation. The WTG three-state model is
shown in Figure 2. A wind farm usually consists of many
units and therefore the specified wind velocity is
assumed to be the same for all the units in the farm. The
power output of a wind farm is the summation of the
output of all the available units.
Where, P is probability, ui is measured wind speed at the
interval i, mi is the hours in which ui is observed, n is the
total number of hours. The cumulative distribution
function F(ui) as the probability that a measured wind
speed will be less than or equal to ui is given in the
equation 6b.
Figure 2: Three state model of WTG
The probability of turbine being in three different states
is calculated according to the state representation and it
is described by the relation as shown below
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82
2.6 Probabilistic Evaluation of Power Generated
This includes the probabilistic evaluation of the
generated power at different wind speeds through the
year. This is calculated by combining distribution of
discrete wind speeds. This can be calculated by estimated
energy output by the discrete wind speed and total
energy estimated through the year. This is described in
the equation 7.
© 2015 IJETM. All Rights Reserved.
Bindhu L., et al. International Journal of Engineering Technology and Management (IJETM)
In addition to this basic reliability index some more
indices are used those are described in the equation 1
and 2 respectively in the subsection 1.2.
Case Study
3.1 Wind Site Description
This site is located in Harapanahalli, Davanagere district
of Karnataka state. This site consists of 24 numbers of
Vestas® made 1.650MW rated WTG. The elevation of the
wind site 2 is 2076ft from the sea level. The data
obtained is from 01/01/2014 01:00 AM to 28/12/2014
00:00 PM. Air density at the wind site 1 is 1.119 kg/m3.
3.2 Features of WTG
Rating – 1.650MW
Blades – 3 numbers
Rotor diameter – 82 meter
Hub height – 82 meter
Cut in wind speed – 3.5 m/sec
Cut out wind speed – 25 m/sec
Rated wind speed – 16 m/sec
Conversion factor – 1Mph = 0.44704 m/sec
Power Curve V82
power o/p
Power output in kW
The value of Plant factor between 15 to 50% is good for
wind power generation. And if the wind is continuous the
Plant factor will be more except for planned and forced
outage. Plant availability is the wind turbine generator
which is available to generate power. This is obtained
from the equation 13.
0
20
40
60
80
Wind speed in Mph
Figure 3: WTG power curve
Figure 3 shows the wind turbine power curve to calculate
the power output from the WTG at different wind
speeds. The power generation model is obtained by
combining this power curve and the wind speed
distribution. The distribution of the discrete wind sped
plot is shown in the data analysis report in figure 4 It
shows the distribution of different wind speeds through
the year and gives the probability of wind speeds. From
the equation 8 the power generated by WTG is calculated
and with the necessary data described in section 3.2 the
WTG power output obtained by the average wind speed
of 7.02 m/sec is estimated as 3751750 kWh and annual
production is 3751750 kWh/year.
Page
2.9 Calculation of Reliability Indices:
The basic reliability index used in this work is Loss of load
expectation; it is the average number of hours for which
the load is expected to exceed the available generating
capacity. And it is given in the equation 15.
2000
1800
1600
1400
1200
1000
800
600
400
200
0
83
.
2.8 Calculation of Plant Factor and Plant Availability
Since wind speed is not constant and continuous, a wind
farm's annual power production is never as much as the
sum of the generator nameplate ratings multiplied by the
total hours in a year. Plant factor is the theoretical
maximum ratio of actual productivity in a year. Typical
Plant factors [4] are 15–50%; values at the upper end of
the range are achieved in favorable sites and are due to
wind turbine design improvements. The plant factor is
calculated by the equation 12 and it is given by,
© 2015 IJETM. All Rights Reserved.
Bindhu L., et al. International Journal of Engineering Technology and Management (IJETM)
© 2015 IJETM. All Rights Reserved.
The basic reliability index used in this work is Loss of load
expectation; it is the average number of hours for which
the load is expected to exceed the available generating
capacity and it is calculated by using equation15. And the
value of LOLE for wind site is found LOLE=2324.0hrs/year.
Second reliability index is EENS and it is calculated by
using equation 1 and the calculated value
EENS=1012.40kWh. It is the energy which is not supplied
by the WTG due to lack of wind speed.Third reliability
index is the Energy index of reliability (EIR). For the wind
turbine generator installed at the wind site EIR is
calculated by the equation 2 and it is given by,
1012.40 ℎ
�� = 1 −
1650
× 8676ℎ
�� = 0.99992927
These reliability indices are calculated by considering all
operating states of WTG.
Figure 4: Frequency distribution of wind speeds and estimated
energy
84
Figure 5: Wind rose graph for wind site indicating direction of wind
Page
3.3 Probabilistic Evaluation of Power Generated
With the power output formula the power generated by
the Wind turbine generator is calculated and the
probability of generated power at different wind speed is
calculated by using the equation 7. This includes the
probabilistic evaluation of the generated power at
different wind speeds through the year. This is calculated
by combining distribution of discrete wind speeds. From
equation 7, probability of generated power at wind speed
8m/sec is given by,
1272 .20
ℎ
= 0.00033995
�� 8 =
3751750
ℎ
The probability of generated power from WTG at
different wind speed is calculated in the same way.
3.4 Three State Model for WTG System
State UP1:
PUP1 = P .5≤ ui ≤
Total number of hours in which wind speed is between
cut in and rated = 6837hrs
Total number of hours in the data = 8676hrs
6837
Therefore PUP1 = P .5≤ ui ≤
= 8676 = 0.7880
Probability of wind speed between cut in and rated or
probability of state UP1 is 78.80%
State UP2:
PUP2 = P ≤ ui ≤
Total number of hours in which wind speed is between
rated and cutout = 859hrs
Total number of hours in the data = 8676hrs
859
Therefore PUP2 = P ≤ ui ≤
= 8676 = 0.0990
Probability of wind speed between rated and cutout or
probability of state UP2 is 9.90%
State DOWN:
PDOWN = 1 - PUP1 - PUP2
PDOWN = 1 - 0.7880- 0.0990= 0.1129
Probability of state DOWN is 11.29%
The plant factor is calculated by the relation 12
and it is given by,
3751749 ℎ
%�
=
100
1650
× 8676ℎ
%�
= 0.2620 × 100
%�
= 26.20
Plant availability is the wind turbine generator which is
available to generate power. This is obtained from the
relation that is given in equation 13.
6837ℎ + 589ℎ
�
� � ���=
100
8676ℎ
�
� � � � � = 0.8870 × 100
�
� � � � � = 88.70 %
� � � � � � = 1 − 0.8870
� � � � � � = 0.1129 × 100
� � � � � � = 11.29 %
Bindhu L., et al. International Journal of Engineering Technology and Management (IJETM)
in reliability evaluation. In this work the plant factor is
found to be 26.20% and it is very useful to generate
power from the wind in that wind site. And the plant
available for generation is found to be 88.70%. Reliability
indices LOLE, EENS and EIR are found to be 2324.
0hrs/year, 1012.40kWh and 0.99992927 respectively.
These indices show that the plant installed at the taken
site works satisfactorily. This work becomes more
valuable, when we consider wind turbine generator and
turbine outage models.
REFERENCES:
Figure 6: July wind variance at the wind site
Page
85
CONCLUSION:
Probabilistic reliability evaluation technique is useful for
electric power industries. which are expected to include
power form wind. The benefits from wind sources are
largely said by the wind organization at the wind farm
site. It is, therefore, very important to obtain suitable
wind speed simulation models and appropriate
techniques to develop power generation model for WTG
1. Roy Billinton and Ronald N. Allan, Relia ility
Assess e t of Large Ele tri Power “yste s , The
Kluwer international series in engineering and
computer science, Boston, USA, ISBN: 0-89838-266-1
2. Dr. Gary L. Johnson Wi d E ergy “yste s , Halsted
Press, New York, October 10, 2006.
3. http://www.powergeneration.siemens.com/en/win-d
power/index.cfmaccessed on 16 Feb 2014.
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