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Preliminary wind resource assessment in South Sudan using reanalysis data and statistical methods

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  • Ayik, A.
  • Ijumba, N.
  • Kabiri, C.
  • Goffin, P.

Abstract

The purpose of this study is to make a preliminary assessment of the wind resource in South Sudan. This is mainly to get data on the quality of the wind resource at different locations in the country and investigate its suitability for the development of wind power generation projects of all sizes. Wind data for 33 locations, covering the period from 1981 to 2019, were requested from Modern-Era Retrospective analysis for Research and Applications version 2 or MERRA-2. The data were then analysed to produce a variety of statistics that describe the quality of the wind resource in each location. Long-term monthly and annual averages together with wind direction were computed for each location at a height of 10 m above ground level. Wind speeds were extrapolated to hub heights of 30 and 50 m above ground level and fitted to five different distribution functions to get the parameters for estimating wind power density. Results show that at 10 m above ground level, the long-term annual average wind speeds range between 5.08 m/s and 2.36 m/s while wind power density range between 128.36 W/m2and 14.39 W/m2. Development of utility-scale wind power plants is marginal in two locations while small-wind turbines development may be possible in the north-north eastern locations. Further research is proposed to explore the possibility of deployment of large-scale wind turbines at locations north-north east. Investigating the wind resource in other locations using alternative methods as well as possibility of development of small wind turbines is suggested.

Suggested Citation

  • Ayik, A. & Ijumba, N. & Kabiri, C. & Goffin, P., 2021. "Preliminary wind resource assessment in South Sudan using reanalysis data and statistical methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    • Handle: RePEc:eee:rensus:v:138:y:2021:i:c:s1364032120309059
    DOI: 10.1016/j.rser.2020.110621
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    References listed on IDEAS

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    2. José Rafael Dorrego Portela & Geovanni Hernández Galvez & Quetzalcoatl Hernandez-Escobedo & Ricardo Saldaña Flores & Omar Sarracino Martínez & Orlando Lastres Danguillecourt & Pascual López de Paz & A, 2022. "Microscale Wind Assessment, Comparing Mesoscale Information and Observed Wind Data," Sustainability, MDPI, vol. 14(19), pages 1-12, September.
    3. Majidi Nezhad, Meysam & Heydari, Azim & Neshat, Mehdi & Keynia, Farshid & Piras, Giuseppe & Garcia, Davide Astiaso, 2022. "A Mediterranean Sea Offshore Wind classification using MERRA-2 and machine learning models," Renewable Energy, Elsevier, vol. 190(C), pages 156-166.
    4. He, J.Y. & Chan, P.W. & Li, Q.S. & Lee, C.W., 2022. "Characterizing coastal wind energy resources based on sodar and microwave radiometer observations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    5. Jianxiao Wang & Liudong Chen & Zhenfei Tan & Ershun Du & Nian Liu & Jing Ma & Mingyang Sun & Canbing Li & Jie Song & Xi Lu & Chin-Woo Tan & Guannan He, 2023. "Inherent spatiotemporal uncertainty of renewable power in China," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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