The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON MATHEMATICS
Transactions ID Number: 32-215
Full Name: Azami Zaharim
Position: Associate Professor
Age: ON
Sex: Male
Address: Solar Energy Research Institute (SERI), ,Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor. MALAYSIA
Country: MALAYSIA
Tel: 603-89216843
Tel prefix: 603-89216681
Fax: 603-89216960
E-mail address: azami@vlsi.eng.ukm.my
Other E-mails: azaminelli@gmail.com
Title of the Paper: Analyzing Malaysian Wind Speed Data Using Statistical Distribution
Authors as they appear in the Paper: AZAMI ZAHARIM, SITI KHADIJAH NAJID, AHMAD MAHIR RAZALI , KAMARULZAMAN IBRAHIM2 AND KAMARUZZAMAN SOPIAN
Email addresses of all the authors: azami@vlsi.eng.ukm.my, khadijahnajid@gmail.com, mahir@ukm.my,kamarulz@ukm.my, ksopian@vlsi.eng.ukm.my
Number of paper pages: 10
Abstract: Many studies have been carried out to develop a suitable statistical model in order to describe wind energy potential. The most important parameter in estimating the wind energy potential is wind speed. Wind speed is a random phenomenon; statistical methods will be very useful in estimating it. For this reason, wind speed probabilities can be estimated by using probability distributions. An accurate determination of probability distribution for wind speed values is very important in evaluating wind speed energy potential of a region Based on the past literature; Weibull and Rayleigh are two widely used distributions. However, in this paper, Burr, Lognormal and Frechet distribution were applied to data sets for a specific location in Pahang, Malaysia. In determining the proper distribution, an approach consisting Kolmogorov-Smirnov (Ks), Anderson Darling (AD) and chi square (��2) test also the fitted graphics of probability distribution function (PDF) !
and cumulative distribution function (CDF) have been used. Based on the graphical and the computed goodness of fit results, general inference can be made that Burr distribution would be the best model which fitted the data very well.
Keywords: Wind speed, wind speed distribution, goodness of fit tests
EXTENSION of the file: .doc
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How Did you learn about congress: kpustaka@ukm.my webptsl@ukm.myPerpustakaan Tun Seri Lanang,Universiti Kebangsaan Malaysia
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