Wind energy assessment considering wind speed correlation in Malaysia

Teo, Kenneth Tze Kin and Goh , K.C. and Chua, Q.S and Lee, S.W (2016) Wind energy assessment considering wind speed correlation in Malaysia. Renewable and Sustainable Energy Reviews, 54 . pp. 1389-1400. ISSN 1364-0321


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Renewable energy is the current trend of energy sourcing. Numerous scientists, inventors, and engineers are working hard to harness renewable energy. The application of renewable energy is very wide; it can be as small as lighting an LED bulb or as large as generating the electricity of a town or even a country. Wind energy plays an important role in the context of electricity generation. Wind energy is highly dependent on the wind speed at a wind site. Wind prediction is necessary for a wind energy assessment of a potential wind farm. In this study, the wind energy assessment is based on wind prediction using the Mycielski algorithm and K-means clustering in Kudat, Malaysia. The predicted results are analysed using Weibull analysis to obtain the most probable wind speed. From the results of this study, K-means clustering is more accurate in prediction when compared with the Mycielski algorithm. The most probable wind in Kudat is sufficient to operate the wind turbines.

Item Type:Article
Uncontrolled Keywords:Wind energy, Renewable energy, Mycielski, K-means clustering, Weibull
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:SCHOOL > School of Engineering and Information Technology
ID Code:13753
Deposited By:IR Admin
Deposited On:03 Aug 2016 14:07
Last Modified:03 Aug 2016 14:07

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