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2013 (Vol. 6, Issue: 10)
Article Information:

The Probability Distribution Model of Wind Speed over East Malaysia

Nurulkamal Masseran, Ahmad Mahir Razali, Kamarulzaman Ibrahim, Azami Zaharim and Kamaruzzaman Sopian
Corresponding Author:  Ahmad Mahir Razali 

Key words:  Goodness of fit,, spatial pattern, wind energy, spatial pattern, wind speed distribution , ,
Vol. 6 , (10): 1774-1779
Submitted Accepted Published
October 22, 2012 December 20, 2012 July 20, 2013
Abstract:

Many studies have found that wind speed is the most significant parameter of wind power. Thus, an accurate determination of the probability distribution of wind speed is an important parameter to measure before estimating the wind energy potential over a particular region. Utilizing an accurate distribution will minimize the uncertainty in wind resource estimates and improve the site assessment phase of planning. In general, different regions have different wind regimes. Hence, it is reasonable that different wind distributions will be found for different regions. Because it is reasonable to consider that wind regimes vary according to the region of a particular country, nine different statistical distributions have been fitted to the mean hourly wind speed data from 20 wind stations in East Malaysia, for the period from 2000 to 2009. The values from Kolmogorov-Smirnov statistic, Akaike’s Information Criteria, Bayesian Information Criteria and R2 correlation coefficient were compared with the distributions to determine the best fit for describing the observed data. A good fit for most of the stations in East Malaysia was found using the Gamma and Burr distributions, though there was no clear pattern observed for all regions in East Malaysia. However, the Gamma distribution was a clear fit to the data from all stations in southern Sabah.
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  Cite this Reference:
Nurulkamal Masseran, Ahmad Mahir Razali, Kamarulzaman Ibrahim, Azami Zaharim and Kamaruzzaman Sopian, 2013. The Probability Distribution Model of Wind Speed over East Malaysia.  Research Journal of Applied Sciences, Engineering and Technology, 6(10): 1774-1779.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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