2011 International Conference on Alternative Energy in Developing Countries and Emerging Economies
- 323 -
Abstract
—
We present wind maps for Bangkok generated
via a mesoscale model with updated input land cover,
vegetation fraction, albedo, and surface roughness data.
Modified inputs have little impact on wind speed, but
significantly improve temperature reproduction in the
model. Mean annual wind speed over the province from the
model ranges from 3.5 ms
-1
to 4.8 ms
-1
at 20 m above ground
level, and from 5.0 ms
-1
to 5.8 ms
-1
at 100 m above ground
level, with highest values in the southern part of Bangkok,
indicating most promise for wind turbine installation in this
area. Given wind speeds in the province, low wind speed
turbines are more suitable for installation than conventional
wind turbines.
Index Terms
—
mesoscale modeling, MM5, urban surface
roughness, urban wind energy, wind resource assessment
I.
I
NTRODUCTION
Bangkok, located in central Thailand in the upper part
of the Gulf of Thailand (Fig. 1), is the capital city and has
the highest electricity demand in the country. Interest is
growing in supplementing this demand with the use of
wind turbines, but those interested in installing of wind
turbines in Bangkok currently have little reliable wind
information on which to base their selections of wind
turbine and installation location. Although many wind
measurements are collected across the city, most of these
are from wind anemometers at 10 m above ground level
(agl) and are much too close to man-made structures and
vegetation, resulting in wind observations dominated by
localized turbulence effects such as eddies in the wake of
buildings. Even a few tens of meters from a
meteorological station wind can thus significantly differ
from measured observations, which could result in lower
power output from an installed turbine than expectations
based upon these observations.
Wind resource assessments produced over recent years
covering the entirety of Thailand and some neighboring
countries [1, 2, 3] are of high resolution (1-km) and
without the disadvantages of 10 m wind observations in
the city. However, as these studies cover very large
domains, they have not properly represented land surface
processes in large urban areas such as Bangkok.
* Corresponding author:
This work was financially supported by the Joint Graduate School of
Energy and Environment and Center for Energy Technology and
Environment, and the Thailand Research Fund under Grant No.
RDG5050016.
Fig. 1. Location of Bangkok within Thailand.
This work incorporates more up-to-date data in the
mesoscale model in the production of wind maps
specifically for Bangkok.
II. METHODOLOGY
The PSU/NCAR mesoscale model (MM5) version
3.7.1 [4] was set up with four one-way nested domains of
27, 9, 3, and 1-km resolutions, with the final domain
covering the entirety of Bangkok plus sufficient ocean
area for the capturing of land-sea breezes in the model.
Initial and boundary conditions for the model were
updated every six hours from the Japanese 25-year
Reanalysis (JRA-25) for meteorological variables [5], the
National Center for Environmental Prediction (NCEP)
Global Final (FNL) Analyses for soil and snow [6], and
the Daily Real-Time Global Sea Surface Temperature
–
High Resolution Analysis at NOAA/NCEP (RTG-SST)
Enhanced Urban Wind Mapping for Bangkok
City Using 1-km Mesoscale Modeling
Carina Paton* and Kasemsan Manomaiphiboon*
,
**
*The Joint Graduate School of Energy and Environment,
King Mongkut’s University
of Technology Thonburi, (
Thailand
)
**Center for Energy Technology and Environment, Ministry of Education, (
Thailand
)
