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Technical and performance assessments of wind turbines in low wind speed areas using numerical, metaheuristic and remote sensing procedures

Author

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  • Akpan, Anthony E.
  • Ben, Ubong C.
  • Ekwok, Stephen E.
  • Okolie, Chukwuma J.
  • Epuh, Emeka E.
  • Julzarika, Atriyon
  • Othman, Abdullah
  • Eldosouky, Ahmed M.

Abstract

The application of innovative technologies in the manufacture of wind turbines (WT) has produced more efficient WT that can operate successfully in low wind speed (LWS) environments. This technology has not been implemented in many LWS parts of the world due to the paucity of enabling technical information (wind resource availability and wind turbine configuration). This study uses ten years wind speed data from twelve Nigerian cities and their population densities, remote sensing, and the configuration of some commercially available LWS turbines in generating technical information suitable for data-backed decision-making on low-speed turbine deployability, operational conditions, and energy yield at 50 and 400 m. Five different numerical and metaheuristic procedures were randomly selected and utilized to estimate Weibull parameters used in computing wind energy development (WEDP) parameters (effective wind power density, EWPD, and wind available time). WT with low cut-in speeds (∼2 m.s−1) can be installed in all the cities. With the highest EWPD and WEDP ratings (100%) at both 50 and 400 m, Obudu is the most suitable location for the development of wind power infrastructure.

Suggested Citation

  • Akpan, Anthony E. & Ben, Ubong C. & Ekwok, Stephen E. & Okolie, Chukwuma J. & Epuh, Emeka E. & Julzarika, Atriyon & Othman, Abdullah & Eldosouky, Ahmed M., 2024. "Technical and performance assessments of wind turbines in low wind speed areas using numerical, metaheuristic and remote sensing procedures," Applied Energy, Elsevier, vol. 357(C).
    • Handle: RePEc:eee:appene:v:357:y:2024:i:c:s0306261923018676
    DOI: 10.1016/j.apenergy.2023.122503
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    2. He, Tingting & Hu, Yihua & Li, Fashuai & Chen, Yuwei & Zhang, Maoxin & Zheng, Qiming & Jin, Yukan & Ren, He, 2025. "Mapping land- and offshore-based wind turbines in China in 2023 with Sentinel-2 satellite data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 214(C).
    3. Sajid Ali & Hongbae Park & Adnan Aslam Noon & Aamer Sharif & Daeyong Lee, 2024. "Accuracy Testing of Different Methods for Estimating Weibull Parameters of Wind Energy at Various Heights above Sea Level," Energies, MDPI, vol. 17(9), pages 1-19, May.

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