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Velocity and power density analysis of the wind at Letšeng-la-terae in Lesotho

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  • Mathaba, Tebello
  • Mpholo, Moeketsi
  • Letuma, Mosuoe

Abstract

The wind profile of Letšeng-la-Terae in Lesotho is analyzed using a 2-year data of 10-min averages. Wind velocity distribution data is estimated as a Weibull distribution using the Graphical Method and Method of Moments. The optimal Weibull parameters for the bi-annual data are obtained using the Method of Moments and the values of the dimensionless shape parameter, k = 1.76, and the scale parameter, c = 6.71 m/s at 10 m above ground level. The calculated air density at the site is 0.875 kg/m3 using the temperature and the pressure measurements. The data shows that the wind is prevalently from the West. The daily wind speed trends show that the interval between 5.00 am and 3.00 pm is the windiest for every month of the year. The months with the most and the least wind speeds are August and February, respectively. Letšeng-la-Terae is a class 4 wind energy site with a 95% confidence interval of both the bi-annual mean wind speed given by 5.97 ± 0.07 m/s and the bi-annual mean power density given by 208.56 ± 7.31 W/m2, both calculated at 10 m above the ground level. The typical turbines on the site are expected to operate 82.8 ± 6.7% of the time. The results show that the site is ideal for large-scale electricity generation.

Suggested Citation

  • Mathaba, Tebello & Mpholo, Moeketsi & Letuma, Mosuoe, 2012. "Velocity and power density analysis of the wind at Letšeng-la-terae in Lesotho," Renewable Energy, Elsevier, vol. 46(C), pages 210-217.
    • Handle: RePEc:eee:renene:v:46:y:2012:i:c:p:210-217
    DOI: 10.1016/j.renene.2012.04.003
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    References listed on IDEAS

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    Cited by:

    1. Francesco Pasanisi & Gaia Righini & Massimo D’Isidoro & Lina Vitali & Gino Briganti & Sergio Grauso & Lorenzo Moretti & Carlo Tebano & Gabriele Zanini & Mabafokeng Mahahabisa & Mosuoe Letuma & Muso Ra, 2021. "A Cooperation Project in Lesotho: Renewable Energy Potential Maps Embedded in a WebGIS Tool," Sustainability, MDPI, vol. 13(18), pages 1-26, September.
    2. Yang, An-Shik & Su, Ying-Ming & Wen, Chih-Yung & Juan, Yu-Hsuan & Wang, Wei-Siang & Cheng, Chiang-Ho, 2016. "Estimation of wind power generation in dense urban area," Applied Energy, Elsevier, vol. 171(C), pages 213-230.
    3. Mpholo, Moeketsi & Nchaba, Teboho & Monese, Molebatsi, 2015. "Yield and performance analysis of the first grid-connected solar farm at Moshoeshoe I International Airport, Lesotho," Renewable Energy, Elsevier, vol. 81(C), pages 845-852.
    4. Chandel, S.S. & Ramasamy, P. & Murthy, K.S.R, 2014. "Wind power potential assessment of 12 locations in western Himalayan region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 530-545.
    5. Juan, Y.-H. & Wen, C.-Y. & Chen, W.-Y. & Yang, A.-S., 2021. "Numerical assessments of wind power potential and installation arrangements in realistic highly urbanized areas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    6. D’Isidoro, Massimo & Briganti, Gino & Vitali, Lina & Righini, Gaia & Adani, Mario & Guarnieri, Guido & Moretti, Lorenzo & Raliselo, Muso & Mahahabisa, Mabafokeng & Ciancarella, Luisella & Zanini, Gabr, 2020. "Estimation of solar and wind energy resources over Lesotho and their complementarity by means of WRF yearly simulation at high resolution," Renewable Energy, Elsevier, vol. 158(C), pages 114-129.
    7. Sichilalu, Sam & Mathaba, Tebello & Xia, Xiaohua, 2017. "Optimal control of a wind–PV-hybrid powered heat pump water heater," Applied Energy, Elsevier, vol. 185(P2), pages 1173-1184.

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