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Numerical Assessment of the Potential Wind on the Coastal Island of Zanzibar

Original scientific paper

Journal of Sustainable Development of Energy, Water and Environment Systems
ARTICLE IN PRESS (scheduled for Vol 12, Issue 03 (general)), 1120514
DOI: https://doi.org/10.13044/j.sdewes.d12.0514
Buruhan Shame1, Dominicus Danardono Dwi Prija Tjahjana2 , Ubaidillah Ubaidillah1, Godlisten Kombe3
1 Sebelas Maret Universsity, Surakarta, Indonesia
2 Universitas Sebelas Maret, Surakarta, Indonesia
3 Univerity of dodoma, Dodoma, Tanzania


The objectives of this paper are to analyse sustainability of wind energy potential, and select the best wind turbine model for installation at the study site. The study used the two-parameter Weibull distribution as the basic mathematical model to analyse half-hourly data collected at the Tanzania Meteorological Department data collection centre for two consecutive years, 2021 and 2022. Statistical methods were used to validate the best fit between the standard deviation, energy pattern, moment, and wind variability methods. The moment method was selected based on the validation results. The results of this research show that more than 66.7% of the most probable monthly wind speed in 2021 is between 5 and 8.6 m/s, while more than 75% is between 5 and 13.7 m/s in 2022. Furthermore, based on the National Renewable Energy Laboratory wind power classification, the study concluded that the site has a sustainable wind energy potential, as more than 90% of the 24 months and 8 climatic seasons have a calculated wind energy density between 700 and 7000 MWh/m². In addition, based on the calculated capacity factor and average power, all turbines selected in this study have high-capacity factors greater than 25% and can be considered for selection based on the projected investment budget. However, the most cost-effective wind turbine model was found to be the POLARIS P62-1000, due to its highest capacity factors and average power output on an annual, seasonal, and monthly basis.

Keywords: Weibull Distribution; Wind Energy Potential;Energy Analysis;Renewable Energy;Zanzibar.

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