2011 International Conference on Alternative Energy in Developing Countries and Emerging Economies
- 328 -
Université de Moncton, developed high resolution
(200 m) wind atlas for the provinces of Prince Edward
Island [7], New Brunswick [8-9] and Nova Scotia [10].
Furthermore, when wind atlas are made available in the
public domain, they provide a means to inform the
general public in regards to the wind resource in their
area.
TABLE
I
H
ISTORY OF
W
IND
R
ESOURCE
M
APPING IN
T
HAILAND
Year
Model
Scale
Res.
(km)
Territory
Org.
2001
Atm.
Meso
10
Thailand
World
Bank
2005
Ext.
Meso
10
Thailand
Fellow
Co.
Ltd.,
DEDE
2009
RAMS
Meso
5
Thailand
EGAT,
JGSEE,
NRCT
2010
MM5
Meso
5
Thailand
JGSEE,
TRF
2010
KAM
Meso
5
Thailand
SPU,
DEDE
2011
MC2/
MsMicro
Meso/
Micro
0.02
Nakhon Si
Thammarat
and
Songkhla
provinces
TSU,
UdeM
Notes: Atm. Atmospheric Model
Ext. Extrapolation Model
Res. Resolution
Org. Organization
DEDE
Department of Alternative Energy Development
and Efficiency, Thailand
EGAT Electricity Generating Authority of Thailand
JGSEE Joint Graduate School of Energy and
Environment, Thailand
NRCT The National Research Council of Thailand
SPU Silpakorn University, Thailand
TRF Thailand Research Fund
TSU Thaksin University, Thailand
UdeM University of Moncton, Canada
The objective of this paper is to develop a wind atlas
of Nakhon Si Thammarat and Songkhla provinces,
Thailand, at a resolution of 200 m. The wind atlas
consists of wind resource maps at 40, 80, and 100 m
elevation above ground level (a.g.l.).
II. M
ETHODOLOGY
A. Wind Resource Assessment Model
The methodology used to develop the wind resource
maps of Nakhon Si Thammarat and Songkhla provinces,
Thailand, is based on the Anemoscope model.
Anemoscope is a wind energy simulation toolkit
developed by Environment Canada and the Canadian
Hydraulics Centre. This is the same model used by the
K.C. Irving Chair in Sustainable Development in the
development of the wind atlas of the provinces of New
Brunswick and Nova Scotia, Canada.
The simulation process in Anemoscope is based on a
state-of-the-art statistical-dynamical downscaling method
[11]. The method consists of using large scale, long term
atmospheric data and their statistical properties to run a
mesoscale model and post-process its output in order to
get a small scale representation of atmospheric motion.
This method involves the following steps: wind climate
classification, mesoscale simulations, statistical post-
processing, and microscale modeling.
The first step in the simulation process, wind climate
classification, consists of classifying the wind regimes
such as to produce a climate state database. The
NCAR/NCEP reanalysis database which covers the entire
globe with a 2.5 degree resolution is included in
Anemoscope. For each database grid point, or climatic
station, the climatic states are defined and characterized
by their frequency of occurrence. This information is
necessary to initialize the mesoscale model.
The second step consists of producing simulations
with the Mesoscale Compressible Community (MC2)
model [12]. The MC2 model is a three-dimensional, non-
hydrostatic, time variable model widely used by
Environment Canada, Canadian universities, and many
other groups worldwide. In Anemoscope, the MC2
model is used to combine the terrain information and the
climate information provided by the climate database into
a series of mesoscale wind maps with a resolution of 1 to
5 km.
The next step in Anemoscope is to use the statistical
module WEStats, which combines the MC2 simulation
results while considering the frequency of occurrence.
From the WEStats module, a mesoscale wind map of the
region is obtained with a 1 to 5 km resolution. This same
methodology was used by Environment Canada to create
the Canadian Wind Energy Atlas. The mesoscale wind
map includes a complete set of the wind data necessary
for the microscale simulations in the next step.
The last step in Anemoscope is to use the
Mesoscale/Microscale Coupler (MMC) module which
uses the wind energy statistics compiled at the previous
step to determine the wind patterns for a subset of the
area, i.e. the microscale region. The microscale region is
composed of hundreds, or possibly thousands of tiles,
depending on the resolution of the mesoscale grid. MMC
uses the microscale wind model, developed by
Environment Canada Atmospheric Environment Service,
MS-Micro [13], to determine the effects of wind flow
across a single microscale tile in a particular direction.
MMC then transforms the results from MS-Micro and
reassembles the results into a microscale wind map.
In the development of the wind atlas of Nakhon Si
Thammarat and Songkhla Provinces, Thailand, two
500 km by 500 km mesoscale grids with a 5 km
resolution were used, each centered on the respective
province, as shown in Fig 2. Furthermore, in order to
completely cover both provinces, 20 microscale grids
were superimposed; each being 160 km by 160 km with a
200 m resolution, as shown in Fig 3. In order to achieve
the final wind resource maps for specific elevations
above ground level, the microscale wind maps were
stitched using the ArcGIS software into one large wind
resource map covering the entire territory.
