Implementation of a topographic artificial neural network wind speed prediction model for assessing onshore wind power potential in Sibu, Sarawak

Wan Azlan, Bin Wan Zainal Abidin and Thelaha, Bin Hj Masri and Lawan, S. M. (2019) Implementation of a topographic artificial neural network wind speed prediction model for assessing onshore wind power potential in Sibu, Sarawak. The Egyptian Journal of Remote Sensing and Space Sciences. pp. 1-14. ISSN 1110-9823

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Abstract

This study presents a topographic machine learning based wind speed prediction model. Predicted and ground station data were used to examine the wind energy potential in Sibu. A terrain-based artificial neural network was developed using MATLAB/Simulink (2016). It was found that the developed model can predict wind speed values in areas where the model was implemented. The detailed wind resource assessment shows that the power and energy densities fall within Class 1, which is suitable for smallscale applications. The annual energy output of the selected wind turbines was found to be 2343.12– 12036.85 kWh/year with an annual capacity factor in the range of 2.16%–7.77%.

Item Type: E-Article
Uncontrolled Keywords: Wind energy, Renewable energy, Sarawak, Sibu, Artificial neural network, Geographic information system, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Academic Faculties, Institutes and Centres > Faculty of Engineering
Depositing User: Gani
Date Deposited: 06 Jan 2020 02:10
Last Modified: 24 Jun 2020 06:09
URI: http://ir.unimas.my/id/eprint/28686

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