dc.description.abstract |
It was more than 40 years ago that Sri Lanka last established a wind loading map after the
severe cyclone that struck the country in 1978. It is strongly believed that statistical methods
had not been used in developing this wind loading map. Hence, the map can either
overestimate or underestimate the wind speeds at least in some of the regions of the country.
Therefore, an updated map which suits the changing climate patterns experienced in the
country has become a necessity. In Sri Lanka, different wind codes are being used when
structures are designed to withstand wind actions. Moreover, there is no suitable wind loading
map that can be used with the Eurocode 1 or BS 6399-2.
The existing wind resource maps for Sri Lanka have been developed in macro scales with low
resolutions which is not adequate for effective decision making in wind power generation.
Moreover, most of them represents wind speed distributions except for wind power
distribution. Therefore, the industry always uses expensive methods to identify the suitable
regions for the establishment of wind turbines.
As the initial stage of this study a wind loading map for Sri Lanka was developed for different
return periods (5, 10, 50, 100, 200, 500 and 1000 years) and for different averaging time
periods (3-second gust, 10-minute average and hourly mean) using the wind data obtained
from 24 weather stations. The data used were the monthly maximums of 3-minute average
and instantaneous maximum wind speeds, recorded over a period of about 35 years. Extreme
value distributions called Gringorten and Gumbel methods were tested to predict the extreme
wind speeds. Finally, the Gringorten methods was adopted due to its unbiased nature. The
generated wind contours for both 3-second gust and 10-minute average basic wind speeds were
analyzed for defining the wind loading zones for Sri Lanka.
Altogether a new wind power distribution map was proposed for Jaffna Peninsula region in
Sri Lanka which has been previously identified as a region with a higher wind energy potential.
The required data was obtained from SLSEA (Sri Lanka Sustainable Energy Authority) and
the Survey Department of Sri Lanka. Computational Fluid Dynamics based model has been
used for the generation of wind power distribution map. The resolution of the map has been
increased up to 150 m x 150 m (5” x 5”). Coastal regions such as Veravil, Pooneryn,
Ampan, Punkudutivu, Kayts, Kankesanturai, Ponnalli Khadu, Karainagar, Mandaitivu
and Alvai were identified as the regions which have the highest wind energy potential in
Jaffna Peninsula. |
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