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. I lence. the map can either overestimate or underestimate the wind speeds at least in some of the regions ol the country. Therefore, on updated map which suits the changing climate patterns experienced in the country has become a necessity. In Sri Lanka, different wind codes arc being used when structures are designed to withstand wind actions. Moreover, (here is no suitable wind loading map that can be used with the Eurocode 1 or BS 6399-2. I he existing wind resource mops 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-$econd gust, 10-minute average and hourly mean) using the wind data obtained from 24 weather stations. The data used were the monthly maxi mums 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 delining 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 Vcravil, Pooneryn, Ampan, Punkudulivu, Kayts, Kankcsanlurai. Ponnalli Khadu, Karainagar, Mandaitivu and Alvai were identified as the regions which have the highest wind energy potential in Jaffna Peninsula.
