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
Depositing User: Unnamed user with email
Date Deposited: 03 Aug 2016 06:07
Last Modified: 23 Oct 2017 05:35

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