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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Abstract
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 |
|---|---|
| Keyword: | Wind energy, Renewable energy, Mycielski, K-means clustering, Weibull |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Department: | SCHOOL > School of Engineering and Information Technology |
| Depositing User: | ADMIN ADMIN |
| Date Deposited: | 03 Aug 2016 14:07 |
| Last Modified: | 25 Nov 2020 10:59 |
| URI: | https://eprints.ums.edu.my/id/eprint/13753 |
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