2011 International Conference on Alternative Energy in Developing Countries and Emerging Economies
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of the power-generation mix were studied [13]. Result
showed that the increase in emission reduction is slightly
sub-linear with the increase in installed wind power.
Recently, the policy supporting the introduction of wind
electricity in Denmark was surveyed [14]. Results
showed that under feed-in law, the incentive-based
systems can be more effective tradable quotas in
promoting the modernization of renewable plants. The
finding is relevant to the development of energy policy in
countries such as Germany, Spain, and developing
countries where the average age of wind turbines is much
younger than those existing in Denmark. One of the
means leading to CO
2
reduction is the substitution of
fossil fuels by renewable energy sources. Direct use of
renewable energy sources can cause a significant
reduction in GHGs emissions to the atmosphere. The
impact of cost and electricity production of high
penetration levels of intermittent electricity in OECD
Europe and the U.S.A. for wind energy is explored [15].
Result showed that the use of wind electricity would
mainly avoid the use of natural gas and coal in both
regions. However, the CO
2
emission abatement costs
differ in both regions due to the more rapid wind
electricity cost increase in OECD Europe. Lowest levels
of CO
2
abatement costs are found at about 15-35 US$/ton
CO
2
[15]. The use of wind energy does not lead to any
direct CO
2
emission. The indirect emissions during
construction are estimated to be 0.011 kg CO
2
/kWh [16].
However, if the world wants to avoid a change of climate,
many countries must stabilize their CO
2
emissions. To
achieve this goal, the power sector must utilize renewable
energy sources or power generation. Throughout
Thailand, wind power potential was roughly estimated to
be over 1,600 MW. Thai government has targeted the
power generation by wind energy about 115 MW the year
2011. Wind energy resource assessment based on wind
mapping developed by the Department of Alternative
Energy Development and Efficiency revealed that the
coastal area in southern Thailand has potential for wind
power. Consequently, the main objective of this paper is
to present the result from wind resource assess and
feasibility study of MW wind power along the coastal
lines of the Gulf of Thailand and the Andaman Sea in
southern Thailand.
III. M
ETHODOLOGY
A. Wind Measurement
Wind speed and wind direction at 20 m, 30 m, and 40
m were measured using 3-cup anemometers and wind
vanes model HOBO at 18 wind energy research stations
along the coastal lines of the Gulf of Thailand and the
Andaman Sea. The geographical coordinate and elevation
above sea level (a.s.l.) of 18 wind met stations is given in
Table I. The geographical distribution of 18 wind energy
research stations and buffer zone with 10 km is shown in
Fig. 1. The 14 stations were installed along the coastal
line of the Gulf of Thailand i.e. 4 stations in Surat Thani
province, 5 stations in Nakhon Si Thammarat province,
and 5 stations in Songkhla province. There were4 stations
installed along the coastal line of the Andaman Sea 2
stations in Krabi province, 1 station in Trang province
and another one in Satun province. Resolution of wind
speed measurement is 0.19 m/s and wind direction
measurement is 1.4
o
. Accuracy is
r
3% at wind speed of
17-30 m/s. Wind speed and direction sensors were
connected to a HOBOWare data logger. A PV battery
charging system is used for power supply backup.
Ambient air temperature was also measured for air
density calculation. The lightening arrester is used for
protecting the measuring equipments from severe
thunder. The main component and picture of wind energy
research station is shown in Fig. 2 and Fig. 3. Sampling
interval is 1 min and logging interval is 10 min. Wind
speed and direction data were recorded during 2008
–
2010.
TABLE
I
G
EOGRAPHICAL COORDINATE OF
18
WIND MET STATIONS
No. Site Name
Lat
(
o
N)
Long
(
o
E)
Elavatiom
(m) (m.s.l)
1
Tha Chana
09
o
31’
99
o
13’
9
2
Tha Chang
09
o
13’
99
o
10’
4
3
Kanchadit
09
o
11’
99
o
29’
9
4
Don Sak
09
o
15’
99
o
35’
9
5
Khanom
09
o
08’
99
o
51’
17
6
Sichon
08
o
57’
99
o
53’
7
7
Thasala
08
o
40’
99
o
56’
9
8
Pak Phanang
08
o
16’
100
o
16’
3
9
Huasai
08
o
06’
100
o
16’
3
10
Ranot
07
o
41’
100
o
23’
7
11
Sathing Phra1
07
o
36’
100
o
24’
10
12
Sathing Phara2 07
o
32’
100
o
25’
5
13
Singha Nakhon 07
o
18’
100
o
30’
5
14
Chana
06
o
58’
100
o
37’
7
15
Nuaeklong
07
o
58’
98
o
58’
10
16
Kolanta
07
o
40’
99
o
02’
7
17
Hatsamran
07
o
14’
99
o
34’
17
18
Thung Wa
07
o
00’
99
o
40’
9
