wind characteristics and energy
TRANSCRIPT
-
7/29/2019 Wind Characteristics and Energy
1/17
This article was downloaded by: [CERIST]On: 27 February 2013, At: 06:24Publisher: Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
International Journal of Green EnergyPublication details, including instructions for authors andsubscription information:
http://www.tandfonline.com/loi/ljge20
Wind Characteristics and Energy
Potential in Belen-Hatay, TurkeyBesir Sahin
a& Mehmet Bilgili
a
aFaculty of Engineering and Architecture, Mechanical Engineering
Department, Cukurova University, Adana, Turkey
Version of record first published: 07 Apr 2009.
To cite this article: Besir Sahin & Mehmet Bilgili (2009): Wind Characteristics and Energy Potential inBelen-Hatay, Turkey, International Journal of Green Energy, 6:2, 157-172
To link to this article: http://dx.doi.org/10.1080/15435070902784947
PLEASE SCROLL DOWN FOR ARTICLE
Full terms and conditions of use: http://www.tandfonline.com/page/terms-and-conditions
This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden.
The publisher does not give any warranty express or implied or make any representationthat the contents will be complete or accurate or up to date. The accuracy of anyinstructions, formulae, and drug doses should be independently verified with primarysources. The publisher shall not be liable for any loss, actions, claims, proceedings,
demand, or costs or damages whatsoever or howsoever caused arising directly orindirectly in connection with or arising out of the use of this material.
http://dx.doi.org/10.1080/15435070902784947http://www.tandfonline.com/page/terms-and-conditionshttp://dx.doi.org/10.1080/15435070902784947http://www.tandfonline.com/loi/ljge20 -
7/29/2019 Wind Characteristics and Energy
2/17
WIND CHARACTERISTICS AND ENERGY POTENTIALIN BELEN-HATAY, TURKEY
Besir Sahin and Mehmet Bilgili
Faculty of Engineering and Architecture, Mechanical Engineering Department,
Cukurova University, Adana, Turkey
In this study, wind characteristics in the Belen-Hatay province situated in southern Turkey were
investigated by using the Wind Atlas Analysis and Application Program (WAsP) for future windpower generation projects. Hourly wind speeds and directions between the years 2004 and 2005
were collected by the General Directorate of Electrical Power Resources Survey Administration
(EIEI). Before the construction of the wind turbine generator in Belen-Hatay province, several
fundamental properties of the site such as wind behavior, availability, continuity, and probability
were carried out in order to provide the necessary information to the potential investors about
cost and economical aspects of the planning wind energy project. The dominant wind directions,
probability distributions, Weibull parameters, mean wind speeds, and power potentials were
determined according to the wind directions, years, seasons, months, and hours of day,
separately. Finally, at a 10 m height above ground level, mean wind speed and power
potential of the site were found to be 7.0 m/s and 378 W/m2, respectively.
Keywords: Wind speed; Wind power potential; Weibull parameters; Wind characteristics
INTRODUCTION
The demand for energy in the world grows rapidly and is expected to continue to
grow in the near future as a result of social, economic, and industrial developments and high
population levels. Parallel to this development, renewable energy sources have received
increasing attention from the world due to limited reserves of fossil fuels and their negative
impacts on the environment. In this regard, the utilization of renewable energy resources,
such as solar, geothermal, and wind energy, appears to be one of the most efficient andeffective solutions (Hepbasli and Ozgener 2004).
Turkey does not have large fossil fuel reserves. Almost all types of oil and natural gas
are imported from neighboring countries. Excluding lignite, reserves of coal, oil, and
natural gas in country are limited and far from being able to meet the projected domestic
demand. Coal is a major fuel source for Turkey. Domestically produced coal accounted for
about 24% of the countrys total energy consumption, used primarily for power generation,
steel manufacturing, and cement production. Turkey is a large producer of lignite; proven
reserves of lignite are in order of 8,075 million tons, of which 7,339 million tons is
economically feasible to use (Kaya 2006).
International Journal of Green Energy, 6: 157172, 2009
Copyright Taylor & Francis Group, LLC
ISSN: 1543-5075 print / 1543-5083 online
DOI: 10.1080/15435070902784947
Address correspondence to Besir Sahin, Professor of Energy Division, Faculty of Engineering and Architecture,
Mechanical Engineering Department, Cukurova University, 01330 Adana, Turkey. E-mail: [email protected]
157
-
7/29/2019 Wind Characteristics and Energy
3/17
Turkey has substantial reserves of renewable energy resources. Renewable energy
production represented about 14.4% of total primary energy supply. The main renewable
energy resources are hydro, biomass, wind, biogas, geothermal, and solar (Kaya 2006).
As reported by the Turkish Statistical Institute (TSI) and the Turkish Electricity
Transmission Company (TETC) in 2006, the installed capacity of electric power plantsin 2005 in Turkey was 38,843.5 MW, with annual electricity production of 161,983.3 GWh,
as seen in Table 1. In this year, 122,174.0 GWh of energy was produced in operating
thermal power plants. On the other hand, annual electricity productions of hydropower
plants and wind power plants were 39,658.1 GWh and 56.6 GWh, respectively. During next
20 years, the electric power plants installed capacity is expected to reach 109,227 MW and
annual electricity production by 623,835 GWh. Statistical evaluations on hydropower
performed by the General Directorate of State Hydraulic Works (GDSHW) in 2006 is
presented in Table 2. At present Turkey has 135 hydroelectric power plants in operation
with total installed capacity of 12,631 MW, generating an average of 45,325 GWh/year,
which is 36% of the economically viable hydroelectric potential. Forty-one hydroelectricpower plants are currently under construction with 3,187 MW of installed capacity to
generate an average 10,645 GWh energy annually, representing 8% of the economically
viable potential. Furthermore, 502 more hydroelectric power plants will be constructed in the
future to be able to utilize maximum use of the remaining 71,411 GWh/year of economically
viable hydropower energy potential. Consequently, a total of 678 hydroelectric power plants
with the installed capacity of 36,260 MW will be in use in coming years.
One of the main renewable energy resources all over the world is wind, which has
played a long and important role in the history of human civilization. Wind power has been
harnessed by mankind for thousands of years. Since earliest recorded history, wind power
has been used to move ships, grind grain, and pump water (Hepbasli and Ozgener 2004).
The last decade was characterized by rough development of wind power engineering all
over the world. Leading positions are taken by Germany, Spain, and the United States. The
Table 1 The installed capacity and annual electricity production of electric power plants in the year 2005 in Turkey
(TSI 2006; TETC 2006).
Power plants Installed capacity Annual production
MW % GWh %
Thermal 25902.3 66.68 122174.0 75.42
Hydro 12906.1 33.23 39658.1 24.48
Geothermal 15 0.04 94.6 0.06Wind 20.1 0.05 56.6 0.04
Total 38843.5 100 161983.3 100
Table 2 Potential of hydro power plants in Turkey (GDSHW 2006).
Status of economically
viable potential
Number of
hydro-electric plants
Total installed
capacity (MW)
Average annual
generation (GWh/year)
Rate (%)
In operation 135 12631 45325 36
Under construction 41 3187 10645 8
To be constructed 502 20442 71411 56
Total potential 678 36260 127381 100
158 SAHIN AND BILGILI
-
7/29/2019 Wind Characteristics and Energy
4/17
rates of growth of this branch of power engineering exceed 39% annually. No other branch
of power engineering developed with such higher rates (Kenisarin et al. 2006).
Previous meteorological stations located in _Iskenderun and Antakya is now surrounded
by obstacles and buildings. The heights of the measuring devices are 10 m above ground level.
For example, Bilgili and others (2004) and Sahin and others (2005) have predicted the level ofwind speed and energy using WAsP. Presently evaluated results are approximately doubled
comparing to the results of old stations. Around the present wind speed measuring stations, there
are no obstacles at all. A velocity measuring device is connected directly to the data logger. The
time interval between readings is 1 hour. There is no manual interference in recording data.
Consequently, the present wind speed measuring station constructed for the purpose of defining
the wind energy potential of Turkey by meteorological Belen-Hatay is very reliable.
In this study, wind power characteristics in the Belen-Hatay province situated in the
eastern Mediterranean region of Turkey were investigated using a computer package program
called WAsP. Before the construction of the wind turbine generator in Belen-Hatay, several
fundamental properties of the site, such as wind behavior, availability, continuity, andprobability, were investigated in order to provide the necessary information to the potential
investors about cost and economical aspects of the planning wind energy project. Wind speed
probability distribution, wind direction frequency distribution, Weibull parameters, mean
wind speed, and power potential variations were determined for the years 2004 and 2005.
All of these wind characteristics were studied according to the wind directions, years, seasons,
months, and hours of day, separately.
DISTRIBUTION OF WIND POWER PLANTS IN TURKEY
Turkey has a land surface area of 774,815 km2. It is surrounded by the Black Sea in the
north, the Marmara and Aegean Seas in the west, and the Mediterranean Sea in the south,providing very long seashores. Especially, the regions of Aegean, Marmara and East-
Mediterranean have high wind energy potential. But not all the land area of Turkey is suitable
for the installation of wind turbines, due to topographic structure (Hepbasli and Ozgener
2004). Although Turkey has sufficient wind energy potentials, the practical utilization of
wind energy as known is limited by installed capacity of 131.35 MW as of May 2007 (EMRA
2007). On the other hand, the cumulative installed capacity of wind energy worldwide is
59,206 MW by the end of 2005, an increase of 24.45% compared to 2004. The countries with
the highest total installed capacity are Germany (18,427 MW), Spain (10,028 MW), the
United States (9,142 MW), India (4,434 MW), and Denmark (3,127 MW) (WPHPBA 2006).
Progress in wind energy technology in recent years has drawn the attention of theprivate sector to these wind energy resources. The distribution of wind energy plants installed
as of May 2007 is illustrated in Table 3 and Figure 1 (EMRA 2007). Although the first
Turkish wind turbine was constructed in Cesme at the Golden Dolphin Hotel by Vestas in
1985 (55 kW), the development of modern Turkish wind power engineering began in
November 1998 when the first 3 Enercon E40 wind turbines of 500 kW began to operate
at Alacat, _Izmir. Then, the wind farm consisting of 12 Vestas V44/600 turbines was
constructed at the same location in November 1998. The third wind farm with total installed
capacity of 10.2 MW started to operate in June 2000 at Bozcaada Island (Hepbasli and
Ozgener 2004; Kenisarin et al. 2006). A wind farm consisting of 20 General Electric GE/1.5
MW turbines was constructed at Bandrma, Balkesir, in September 2006 (WPHPBA, 2006).
Total installed wind power capacity of Turkey is 131.35 MW as of May 2007. As seen inTable 3, according to the projection of the Energy Market Regulatory Authority (EMRA), the
WIND CHARACTERISTICS AND ENERGY POTENTIAL IN BELEN-HATAY 159
-
7/29/2019 Wind Characteristics and Energy
5/17
Table 3 Distribution of Turkeys wind energy installations by regional as of May 2007 (EMRA 2007) (*: In
operation, others: Under construction).
Place Company Date of
commissioning
Installed capacity
(MW)
Cumulative installed
capacity (MW)
Izmir-Cesme* Demirer A.S. 1998 1.5 1.5
Izmir-Cesme* Gucbirligi A.S. 1998 7.2 8.7
Canakkale-
Bozcaada*
Demirer-Enercon 2000 10.2 18.9
_Istanbul-
Hadmkoy*
Sunjut A.S. 2003 1.2 20.1
Balkesir-
Bandrma*
Bares A.S. I/2006 30.0 50.1
_Istanbul-Silivri* Erturk A.S. II/2006 0.85 50.95_Izmir-Cesme* Mare A.S. I/2007 39.2 90.15
Manisa-Akhisar* Deniz A.S. I/2007 10.8 100.95
Canakkale-_Intepe* Anemon A.S. I/2007 30.4 131.35
Canakkale-
Gelibolu
Dogal A.S. II/2007 15.2 146.55
Manisa-Sayalar Dogal A.S. II/2007 30.4 176.95
Hatay-Samanda g Deniz A.S. II/2007 30.0 206.95_Istanbul-
Gaziosmanpasa
Lodos A.S. I/2008 24.0 230.95
_Izmir-Aliaga _Innores A.S. I/2008 42.5 273.45
Aydn-Cine Sabas A.S. I/2008 19.5 292.95_Istanbul-Catalca Erturk A.S. I/2008 60.0 352.95
Canakkale As Makinsan
Temiz A.S.
II/2008 30.0 382.95
_Izmir-Kemalpasa Ak-El A.S. II/2008 66.6 449.61
Hatay-Samanda g Ezse Ltd. Sti. II/2008 35.1 484.61Hatay-Samanda g Ezse Ltd. Sti. II/2008 22.5 507.11
Balkesir-Saml Baki A.S. II/2008 90.0 597.11
Balkesir-
Bandrma
Banguc A.S. II/2008 15.0 612.11
Osmaniye-Bahce Rotor A.S. I/2009 130.0 742.11
*stanbul-Hadmky/1.2MWstanbul-atalca/60MW
stanbul-Gaziosmanpaa/24MW* stanbul-Silivri/0.85MW
*Balkesir-Bandrma/30MW
Osmaniye-Bahe/130MW
Hatay-Samanda/22.5MW
Hatay-Samanda/30MWHatay-Trbe/35.1MW
anakkale-Gelibolu/15.2
MW*anakkale-ntepe/30.4MW
*anakkale-Bozcaada/10.2MW
anakkale/30MW
*zmir-eme/1.5MW*zmir-eme/7.2MW*zmir-eme/39.2MW
*Manisa-Akhisar/10.8MW
zmir-Kemalpaa/66.66MW
zmir-Aliaa/42.5MW
Aydn-ine/19.5MW
Manisa-Akhisar/30.4MW
Balkesir-Bandrma/15MW0 5
0100
150
200
250
Km
Balkesir-aml/90MW
TURKEY
Figure 1 Wind power plants in Turkey (EMRA 2007) (*: In operation, others: Under construction).
160 SAHIN AND BILGILI
-
7/29/2019 Wind Characteristics and Energy
6/17
installed capacity of wind energy in Turkey will reach 742.11 MW by the year 2009 (EMRA
2007). It is also clear from the table that there are three wind power plants under construction
with total installed capacity of 87.6 MW in Hatay province.
One of the most suitable areas of Turkey for wind power generation is some locations
of the eastern Mediterranean region. Along the Mediterranean coast, valleys and mountainsare not perpendicularly formed, and the Taurus Mountains are situated away from the
seacoast in many regions. Therefore, these regions are exposed to southerly winds that are
not as strong as the northerly winds that occur over the Black Sea. In the vicinity of_Iskenderun Bay especially, there are suitable locations for wind power generation (Durak
and Sen 2002). In addition to deciding the most suitable site for a wind turbine and defining
the necessary parameters about turbines, such as size, blade shape, total capacity, and
direction, it also requires a feasibility report on the fundamental properties of the site, such
as wind behavior, availability, continuity, and probability in the proposed region. In order
to use those properties, statistical and dynamic characteristics of wind of the site should be
obtained using wind observations and statistical wind data (Karsli and Gecit 2003).
MATERIALS AND METHODS
Location of the Site
The data used in this study were collected from Belen-Hatay station, located in the
eastern Mediterranean region of Turkey. This station has been set up by the General
Directorate of Electrical Power Resources Survey Administration (EIEI). The map of the
region and the location of the station are presented in Figure 2. Adana and Hatay are two of
the industrialized provinces in the eastern Mediterranean region of Turkey, with a population
of around 3.2 million. With the neighboring provinces the population goes up to
Black Sea
Aegean
Sea
Mediterranean Sea
40
28 32 36 40
0 100
200
Km
44
28 32 36 40 4436
40
36
TURKEY
MEDITERRANEAN
SEA
Belen
skenderunBay
Amik
Lowland
AmanosM
ountain
AdanaMersin
Hatay
(Antakya)
Figure 2 The map of the region and the location of the station.
WIND CHARACTERISTICS AND ENERGY POTENTIAL IN BELEN-HATAY 161
-
7/29/2019 Wind Characteristics and Energy
7/17
approximately 6 million according to the population census done in 2004. Estimated popula-
tion of Adana and Antakya combined is presently 4.2 million and with neighboring provinces
the population goes up to 7.8 million. Electricity production from wind power should be
locally preferred over thermal power plants (Sahin et al. 2005).
Two important mountain passes, Gulek mountain pass and Belen mountain pass,provide a highway route between Europe and the Middle East. More specifically, Belen
mountain pass is situated along the wide spread valley between east of Mediterranean
region and Amik lowland, on the Amanos mountain in the city of Belen. In this region, there
is a wide range of land that is suitable for wind turbine farming. Belen has fairly high wind
speeds that vary proportional to the altitude. A Mediterranean climate is dominant in this
region, usually hot and dry in summer and lukewarm and rainy in winter. But climate
properties vary depending on the height above sea level. On the slope of a mountain looking
at the sea, an increase of terrestrial effects on climate is observed. However, the weather in
this region does not show intense terrestrial climate due to the Mediterranean Sea effect.
Wind Data
The long-term wind data, containing hourly wind speeds and directions, cover the period
from 2004 to 2005. The mean monthly, annual, and diurnal wind speeds were calculated from
these hourly wind speed data. The anemometer of the station is 10 m above ground level.
Geographical coordinates and measurement period of this station are given in Table 4. The
wind observation station is situated at the coordinates of 361200N latitude and 382801E
longitude. The height of the station is 474 m above sea level. Around the measurement area,
there were no obstacles that would cause an impact on the wind speeds and directions.
WAsP Program
In this study, Wind Atlas Analysis and Application Program (WAsP) was used to
investigate wind characteristics in Belen-Hatay city. WAsP program and associated soft-
ware has been developed by Riso National Laboratory, Denmark. WAsP is a PC program
for the vertical and horizontal extrapolation of wind climate statistics. It contains several
models to describe the wind flow over different terrains and close to sheltering obstacles.
WAsP consists of five main calculation blocks: analysis of raw data, generation of wind
atlas data, wind climate estimation, estimation of wind power potential, and calculation of
wind farm production (Mortensen et al. 2001).
Four basic data are considered necessary for the WAsP packet program that is used inthe determination of wind power potential. These are hourly wind speed and direction,
sheltering obstacles, surface roughness changes, and orographic data (terrain height).
Obstacles have an impact on the wind speed and alter the wind direction, particularly for
lower level of height. If there are obstacles around the measurement station, wind speeds
must be reconsidered again by taking the effect of these parameters into account (Bilgili
Table 4 Geographical coordinate and measurement period of Belen station.
Station Latitude Longitude Altitude (m) Period Anemometer height (m)
Belen 36 12 00 N 38 28 01 E 474 20042005 10
162 SAHIN AND BILGILI
-
7/29/2019 Wind Characteristics and Energy
8/17
et al. 2004). In deciding about the effectiveness of the wind speed measurement around a site,
the topographic and climatic conditions must be taken into consideration. Any method of
wind speed predictions should consider the topographic and climatologic features. The wind
speed measured at a site is determined mainly by two factors: the overall weather systems
(which usually have an extent of several hundred kilometers) and the nearby topographywithin few kilometers of the station. The collective effect of the terrain surface and obstacles,
leading to an overall retarding of the wind near the ground, is referred to as the roughness of
the terrain. Orographic elements, such as hills, cliffs, ridges, and escarpments, exert an
additional influence on the wind. Roughness and orography are among the main factors
that affect the wind speed (Durak and Sen 2002).
RESULTS AND DISCUSSION OF WIND CHARACTERISTICS
Wind Speed Probability Distribution
Generally, previously measured wind data are used for the estimation of wind power
potential of any area. First of all, at any location, hourly wind speeds and wind directions
are first observed and monitored. These results are used for frequency and probability
modeling. Wind speed data in time-series format is usually arranged in the frequency
distribution format since it is more convenient for statistical analysis. Therefore, the available
time-series data were translated into frequency distribution format. The wind speed
probability distributions and the functions representing them mathematically are the main
tools used in the wind-related literature. Their use includes a wide range of applications, from
the techniques used to identify the parameters of the distribution functions to the use of such
functions for analyzing the wind speed data and wind energy economics (Celik 2003). The
frequency distribution and probability density of the wind speeds help toward answering
questions of how long a wind power plant is out of action in the case of lack of wind, which is
the range of the most frequent wind speeds, and how often the wind power plant achieves its
rated output (Pashardes and Christofides 1995). Probability density for each wind class
according to the relation is stated as
pvi fiPN
i1
fi
Here,fi is frequency of occurrence of each speed class andNis number of hours in theperiod of time considered. The cumulative probability density is determined as
Pvi XNi1
pvi
Yearly cumulative distributions derived from the long-term wind speed data of
Belen-Hatay are presented in Figure 3. It is also clear from the figure that the two curves
show the same variation according to each other. This figure indicates that the hourly wind
speeds in Belen-Hatay are higher than 5 m/s in about 70% of occasions. Seasonal cumulative
distributions for the years 2004 and 2005 are presented in Figure 4. It is interesting to note thatthe wind speeds of summer months in Belen-Hatay are higher than the others.
WIND CHARACTERISTICS AND ENERGY POTENTIAL IN BELEN-HATAY 163
-
7/29/2019 Wind Characteristics and Energy
9/17
Dominant Wind Direction
There are two important aspects in the selection of the type of orientation of the wind
turbines and their location. These are the wind speed distribution in each direction and the most
frequent wind directions (Torres et al. 1999). Besides the level and structure of wind speeds, the
direction of the wind is of decisive significance for the evaluation of the possibilities of utilizing
wind power. The direction statistics play an important role in optimal positioning of a wind
turbine farm in a given area (Pashardes and Christofides 1995). Wind directions and speeds are
also affected by topography (Matsui et al. 2002). Yearly dominant wind directions of
Belen-Hatay station are presented in Figure 5. It is also clearly seen from the figure that the
two curves show the same variation. The data of the wind direction show that the maximum
frequency occurs at the west-north (WN) direction. In this region, northwestern winds are
effective and the winds from WN direction continuously blow during 42.5% of the time for the
year 2004 with a speed of 9.23 m/s. The effect of wind that is observed at the lowest degree is in
the direction of south (S), south-west (SW), and west-south (WS), with a speed of 2.21 m/s,
2.06 m/s, and 2.69 m/s, respectively. Monthly dominant wind directions of Belen-Hatay station
for the year 2004 are presented in Figure 6. It is also clear from the figure that during spring,
summer, and autumn months, wind speeds at the west-north (WN) direction are effective. Onthe other hand, during winter months, wind speeds at the south-east (SE) direction are effective.
0
20
40
60
80
100
0 2 4 6 8 10 12 14 16 18 20 22
Wind speed (m/s)
Cumulativedensity(%)
2004
2005
Figure 3 Yearly cumulative probability distributions of wind speeds.
10
10
30
50
70
90
110
0 2 4 6 8 10 12 14 16 18 20 22
Wind speed (m/s)
Cumulativedensity(%)
Spring (2004)
Spring (2005)
Summer (2004)
Summer (2005)
Autumn (2004)
Autumn (2005)
Winter (2004)
Winter (2005)
Figure 4 Seasonal cumulative probability distributions of wind speeds for the year 2004 and 2005.
164 SAHIN AND BILGILI
-
7/29/2019 Wind Characteristics and Energy
10/17
Variation of Weibull Parameters
It is known that there are several efforts to construct an adequate statistical model for
describing the wind speed frequency distribution, which may be used for predicting the
energy output. The Weibull distribution has been accepted to give a good fit to wind data
for wind energy applications (Incecik and Erdogmus 1995). The Weibull distribution is atwo-parameter distribution. This distribution is expressed as
pwv k
c
v
c
k1exp
v
c
k
where pw
(v) is the probability of observing wind speed v, kis the Weibull shape parameter
(dimensionless), and c is the Weibull scale parameter, which has a reference value in the
units of wind speed (Akpinar and Akpinar 2004).
For the years 2004 and 2005, the Weibull parameters according to the wind directions
in Belen-Hatay station are given in Table 5. The Weibull shape parameters (k) are withinthe range 1.353.81 for the whole year. The Weibull scale parameters (c) also vary between
0
10
20
30
40
Frequency(%)
N NE EN E ES SE S SW WS W WN NW
Wind direction
2004
2005
Figure 5 Yearly dominant wind directions.
10
10
30
50
70
90
110
N NE EN E ES SE S SW WS W WN NW
Wind direction
Frequency(%)
January FebruaryMarch AprilMay JuneJuly AugustSeptember October November December
Figure 6 Monthly dominant wind directions for the year 2004.
WIND CHARACTERISTICS AND ENERGY POTENTIAL IN BELEN-HATAY 165
-
7/29/2019 Wind Characteristics and Energy
11/17
2.2 m/s and 10.3 m/s. It can be seen that the maximum c parameter appears in the direction of
WN with 10.3 m/s. On the other hand, the minimum c parameter is in the direction of SW
with 2.2 m/s. The highest kparameter for the whole year is in the direction of WN with 3.81,
while the lowest appears in the direction of EN with 1.35. The monthly Weibull parameters of
Belen-Hatay station are given in Table 6. It is seen from the table that the monthly Weibull
shape parameters (k) for the whole year range from a low of 1.82 in December to a high of
5.84 in July. While the highest monthly Weibull scale parameter (c) value is determined as
11.9 m/s in August, the lowest monthly c value is found as 5.3 m/s in December.
Variation of Wind Speeds
The production of wind energy is essentially dependent on the magnitude and
regularity of wind speeds (Pashardes and Christofides 1995). Wind speed is the most
important parameter in the design and study of wind energy conversion systems
Table 5 The Weibull parameters according to the wind directions.
Wind direction 2004 2005 Whole
c (m/s) k c (m/s) k c (m/s) k
0 (N) 2.7 1.29 2.8 1.52 2.8 1.44
30 (NE) 1.6 1.75 3.5 1.54 3.1 1.4
60 (EN) 6.3 1.43 4.7 1.47 5.1 1.35
90 (E) 8.9 3.17 7.6 2.73 8.3 2.85
120 (ES) 5.7 1.81 5.3 1.69 5.5 1.74
150 (SE) 4.9 1.8 5.2 2.2 5.1 1.95
180 (S) 2.5 1.54 2.1 1.54 2.3 1.54
210 (SW) 2.3 1.84 2.0 2.03 2.2 1.86
240 (WS) 3.0 2.58 3.3 1.39 3.2 1.74
270 (W) 6.7 1.81 10.7 4.32 9.6 2.97
300 (WN) 10.2 3.92 10.4 3.72 10.3 3.81
330 (NW) 7.8 2.85 7.0 2.32 7.4 2.61
Table 6 The monthly Weibull parameters.
Month 2004 2005 Whole
c (m/s) k c (m/s) k c (m/s) k
January 6.4 1.65 6.9 2.02 6.7 1.84
February 7.1 2.00 6.4 1.98 6.8 1.99
March 7.1 2.70 6.0 2.4 6.6 2.55
April 7.2 2.04 7.4 2.27 7.3 2.16
May 8.9 3.64 8.8 2.97 8.9 3.31
June 10.3 5.09 10.4 3.81 10.4 4.45
July 10.8 4.90 12.0 6.78 11.4 5.84
August 11.5 4.59 12.2 5.36 11.9 4.98
September 8.6 3.78 8.8 5.36 8.7 4.57
October 6.0 2.36 5.8 2.24 5.9 2.3
November 6.1 1.96 5.6 2.26 5.9 2.11
December 6.1 1.65 4.5 1.98 5.3 1.82
166 SAHIN AND BILGILI
-
7/29/2019 Wind Characteristics and Energy
12/17
(Akpinar and Akpinar 2005). A detailed knowledge of the wind speed distribution and
the most frequent wind directions are substantially important when choosing wind
turbines and locations (Torres et al. 1999). For this purpose, yearly mean wind speeds
according to the wind directions, monthly mean wind speeds, and daily variation of
wind speeds of Belen-Hatay station were determined by using the WAsP program. The
variation of yearly mean wind speeds according to the wind directions of Belen-Hatay
station is presented in Figure 7. It is also clear from the figure that the two curves show
the same variation according to each other. The highest yearly mean wind speed for the
year 2004 is in the direction of WN with 9.23 m/s, while the lowest appears in the
direction of SW with 2.06 m/s. In this region, wind speeds observed in the direction of
WN are effective and strong.
The monthly variation of mean wind speeds of Belen-Hatay station for the year 2004
and 2005 is presented in Figure 8. The highest monthly mean wind speeds for the year 2005
occur mainly in July and August with 11.1 m/s and 11.3 m/s respectively, and the lowest
wind speeds occur in November and December with 4.7 m/s and 3.9 m/s respectively. It isapparent from the figure that monthly mean wind speed data of 2004 and 2005 agree well
with each other. The variation of diurnal wind speeds of Belen-Hatay station for the year
0
2
4
6
8
10
Wind
speed(m/s)
N NE EN E ES SE S SW WS W WN NW
Wind direction
2004
2005
Figure 7 The variation of yearly mean wind speeds according to the wind directions.
0
2
4
6
8
10
12
Windspeed(m/s)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
2004
2005
Figure 8 The monthly variation of mean wind speeds for the year 2004 and 2005.
WIND CHARACTERISTICS AND ENERGY POTENTIAL IN BELEN-HATAY 167
-
7/29/2019 Wind Characteristics and Energy
13/17
2004 and 2005 is presented in Figure 9. It is also clear from the figure that the three curves
show the same variation. Diurnal wind speed for the whole year varies between 6.05 m/s
and 7.76 m/s. The diurnal wind speed has its minimum value during the morning hours and
its maximum value during the afternoon hours. In other words, in this region, the wind
speed is higher during the day and lower during the night. This is due to the high level ofsolar intensity during the day. Figure 10 shows the variation of diurnal mean wind speeds
for the seasons of winter, spring, summer, and autumn in the year 2005. The graph reveals
that diurnal wind speeds during the summer are higher than diurnal wind speeds during the
winter, spring, and autumn.
Variation of Wind Power Potential
The variation of yearly mean wind power potential according to the wind
directions of Belen-Hatay station is presented in Figure 11. It is also clear from the
figure that the two curves show the same variation according to each other. Thehighest yearly mean wind power potential for the year 2004 is in the direction of WN
5
5,5
6
6,5
7
7,5
8
2 0 2 4 6 8 10 12 14 16 18 20 22 24
Hour of day
Windspee
d(m/s)
2004 2005 Whole
Figure 9 The variation of diurnal wind speeds for the year 2004 and 2005.
2
4
6
8
10
12
2 0 2 4 6 8 10 12 14 16 18 20 22 24
Hour of day
Windspeed(m/s)
Winter Spring
Summer Autumn
Figure 10 The variation of diurnal mean wind speeds for the seasons in the year 2005.
168 SAHIN AND BILGILI
-
7/29/2019 Wind Characteristics and Energy
14/17
with 599 W/m2, while the lowest appears in the direction of SW with 11 W/m2. In
this region, wind power potential determined in the direction of WN is effective and
fairly strong.
The monthly variation of mean wind power potential of Belen-Hatay station for
the year 2004 and 2005 is presented in Figure 12. The highest monthly mean wind
power potential for the year 2005 occurs mainly in July and August with 911 W/m2
and 993 W/m2 respectively, and the lowest in November and December with 122 W/m2
and 75 W/m2 respectively. It is apparent that monthly mean wind power potential
data of 2004 and 2005 agree well with each other. The variation of diurnal wind
power potential of Belen-Hatay station for the year 2004 and 2005 is presented inFigure 13. It is also clear that the three curves show the same variation with a good
agreement. Diurnal wind power potential for the whole year varies between 291.5 W/m2
and 448 W/m2. The diurnal wind power potential has its minimum value during the
morning hours and its maximum value during the afternoon hours. In other words, in
this region, the wind power potential is higher during the day and lower during the
night.
0
100
200
300
400
500
600
700
Windpowerp
otential
(W/m2
)
N NE EN E ES SE S SW WS W WN NW
Wind direction
2004
2005
Figure 11 The variation of yearly mean wind power potential according to the wind directions.
0
200
400
600
800
1000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
2004
2005
Windpowerpotential
(W/m2)
Figure 12 The monthly variation of mean wind power potential for the year 2004 and 2005.
WIND CHARACTERISTICS AND ENERGY POTENTIAL IN BELEN-HATAY 169
-
7/29/2019 Wind Characteristics and Energy
15/17
OVERALL DISCUSSIONS
Turkeys energy demand is growing rapidly and expected to continue to grow in the
near future. The annual increase in energy consumption is 68%, except for recession years.
The installed capacity of electric power plants in the year 2005 was 38,843.5 MW with
annual electricity production 161,983.3 GWh. Presently, 66.68% of this energy is
produced in operating thermal power plants. The combustion of coal, lignite, petroleum,
wood, agricultural and animal waste, causes environmental pollution and will be a
serious problem in the future. In this regard, renewable energy resources appear to be
one of the most efficient and effective solutions for sustainable energy development and
environmental pollution prevention in Turkey (Ocak et al. 2004).
The Belen-Hatay region has a reasonably good wind power potential. In this region,
the hourly wind speeds are higher than 5 m/s in about 70% of occasions at 10 m height
above ground level. The monthly mean wind speeds are higher than 5 m/s during nine
months of the year; on the other hand the monthly mean wind power potentials are higher
than 200 W/m2 during eight months of the year. While a wind generator is being installed
in this region, the yearly wind characteristics should be provided basic information about
the wind strength and consequently about the supply of wind power. The variations of the
yearly mean wind characteristics measured in 2004 and 2005 are given in Table 7. It can
be seen from this table that in 2004, the mean wind speed is 7.1 m/s and the mean wind
power potential is 374 W/m2. On the other hand in 2005, the mean wind speed is 7.0 m/s
and the mean wind power potential is 382 W/m2. According to the critical values of meanwind speed, having wind speed of 7.1 m/s is good for the utilization of the wind energy
potential.
0
100
200
300
400
500
2 0 2 4 6 8 10 12 14 16 18 20 22 24
Hour of day
Windpowerpote
ntial(W/m2)
2004 2005 Whole
Figure 13 The variation of diurnal wind power potential for the year 2004 and 2005.
Table 7 The yearly mean wind characteristics measured in the year of 2004 and 2005.
Wind characteristics 2004 2005 Whole
Weibull parameter (c) (m/s) 8.30 8.20 8.30
Weibull parameter (k) 2.63 2.31 2.46
Wind speed (m/s) 7.10 7.00 7.00
Standard deviation of wind speeds (m/s) 3.50 3.66 3.58Wind power potential (W/m2) 374 382 378
170 SAHIN AND BILGILI
-
7/29/2019 Wind Characteristics and Energy
16/17
CONCLUSIONS
It can be concluded that present regions are suitable for the plantation of wind energy
turbines. Several locations can quite reasonably be considered favorable for the production
of wind energy. It is known that there is no wind turbine placed in the region of Belen-Hatayyet for electricity production. The present results suggest that it can be profitable to
establish a wind farm in this region. At 10 m height above the ground level, mean wind
speed and power potential of the site are 7.0 m/s and 378 W/m2, respectively. The hourly
wind speeds are higher than 5 m/s in about 70% of occasions. The monthly mean wind
speeds are higher than 5 m/s during nine months of the year; on the other hand the monthly
mean wind power potentials are higher than 200 W/m2 during eight months of the year. In
this provision, there is very large land area available for constructing wind energy farms.
However, their suitability and availability for these applications are acceptable in terms of
other aspects such as being in close proximity to the electrical grid lines, land ownership,
road network infrastructure, and so forth.
ACKNOWLEDGMENT
The authors wish to thank the office of Scientific Research Projects of Cukurova University for
funding this project under contract no. MMF2006D18.
REFERENCES
Akpinar, E. K., and S. Akpinar. 2004. Determination of the wind energy potential for Maden-Elaz g,
Turkey. Energy Conversion and Management 45 (1819): 290114.
Akpinar, E. K., and S. Akpinar. 2005. A statistical analysis of wind speed data used in installation ofwind energy conversion systems. Energy Conversion and Management 46 (4): 51532.
Bilgili, M., B. Sahin, and A. Kahraman. 2004. Wind energy potential in Antakya and _Iskenderun
regions, Turkey. Renewable Energy 29 (10): 173345.
Celik, A. N. 2003. A statistical analysis of wind power density based on the Weibull and Rayleigh
models at the southern region of Turkey. Renewable Energy 29 (10): 593604.
Durak, M., and Z. Sen. 2002. Wind power potential in Turkey and Akhisar case study. Renewable
Energy 25 (3): 46372.
EMRA (Energy Market Regulatory Authority). 2007. Electricity Market. http://www.epdk.org.tr.
GDSHW (General Directorate of State Hydraulic Works). 2006. Sources of Energy, Hydroelectric
Energy. http://www.dsi.gov.tr.
Hepbasli, A., and O. Ozgener. 2004. A review on the development of wind energy in Turkey.Renewable and Sustainable Energy Reviews 8 (3): 25776.
Incecik, S., and F. Erdogmus. 1995. An investigation of the wind power potential on the western coast
of Anatolia. Renewable Energy 6 (7): 86365.
Karsli, V. M., and C. Gecit. 2003. An investigation on wind power potential of Nurdag-Gaziantep,
Turkey. Renewable Energy 28 (5): 82330.
Kaya, D. 2006. Renewable energy policies in Turkey. Renewable and Sustainable Energy Reviews
10 (2): 15263.
Kenisarin, M., V. M. Karsl, and M. Caglar. 2006. Wind power engineering in the world and
perspectives of its development in Turkey. Renewable and Sustainable Energy Reviews
10 (4): 34169.
Matsui, M., T. Ishihara, and K. Hibi. 2002. Directional characteristics of probability distribution of
extreme wind speeds by typhoon simulation. Journal of Wind Engineering and IndustrialAerodynamics 90 (1215): 154153.
WIND CHARACTERISTICS AND ENERGY POTENTIAL IN BELEN-HATAY 171
-
7/29/2019 Wind Characteristics and Energy
17/17
Mortensen, N. G., D. N. Heathfield, L. Landberg, O. Rathmann, I. Troen, and E. L. Petersen. 2001.
Wind Atlas Analysis and Application Program (WAsP): Getting started with WAsP 7, Manual.
Roskilde, Denmark: Riso National Laboratory.
Ocak, M., Z. Ocak, S. Bilgen, S. Keles,and K. Kaygusuz. 2004. Energy utilization, environmental
pollution and renewable energy sources in Turkey. Energy Conversion and Management45 (6): 84564.
Pashardes, S., and C. Christofides. 1995. Statistical analysis of wind speed and direction in Cyprus.
Solar Energy 55 (5): 40514.
Sahin, B., Bilgili M., Akilli H., 2005. The wind power potential of the eastern Mediterranean region of
Turkey. Journal of Wind Engineering and Industrial Aerodynamics 93 (2): 17183.
TETC (Turkish Electricity Transmission Company). 2006. Turkish Electricity Generation-Transmission
Statistics. http://www.teias.gov.tr.
Torres, J. L., A. Garcia, E. Prieto, and A. D. Francisco. 1999. Characterization of wind speed data
according to wind direction. Solar Energy 66 (1): 5764.
TSI (Turkish Statistical Institute). 2006. Electricity Generation and Distribution. http://www.turkstat.
gov.tr.
WPHPBA (Wind Power and Hydropower Plants Businessmens Association. Statistics). 2006. The
Installed Capacity of Electric Power Plants in Turkey. http://www.ressiad.org.tr.
172 SAHIN AND BILGILI