APA
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Kihel, B. E., Elyamani, N. E. E. K., Chillali, A., & Slimani, H. (2024). Exploring the Potential of Wind Data through Weibull and Rayleigh Functions at Ten Sites along Morocco's Atlantic Shore. 2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET).
Chicago/Turabian
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Kihel, Badr El, Nacer Eddine El Kadri Elyamani, Abdelhakim Chillali, and Hicham Slimani. “Exploring the Potential of Wind Data through Weibull and Rayleigh Functions at Ten Sites along Morocco's Atlantic Shore.” 2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET) (2024).
MLA
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Kihel, Badr El, et al. “Exploring the Potential of Wind Data through Weibull and Rayleigh Functions at Ten Sites along Morocco's Atlantic Shore.” 2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET), 2024.
BibTeX Click to copy
@article{badr2024a,
title = {Exploring the Potential of Wind Data through Weibull and Rayleigh Functions at Ten Sites along Morocco's Atlantic Shore},
year = {2024},
journal = {2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)},
author = {Kihel, Badr El and Elyamani, Nacer Eddine El Kadri and Chillali, Abdelhakim and Slimani, Hicham}
}
This article aims to assess the offshore wind potential of ten locations along the Atlantic coast of the Kingdom of Morocco. Wind data collected at a height of 50 meters between 2013 and 2022 were extracted from the Merra2 climatic reanalysis system developed by NASA and extrapolated to 100 meters and 105 meters. This assessment is divided into two phases: descriptive statistical analyses and probability analyses. The Rayleigh and Weibull distribution functions were used, with three distinct methods to determine the shape factor (k) and scale factor (c) parameters. The optimal values of k and c were determined using the coefficient of determination R2 and the root mean square error RMSE. The results highlight predominant wind directions characterized by frequent occurrences and uniform directions at all studied locations (St1 to St9), except for St10. The Weibull distribution function fits the data better than the Rayleigh function. All positions show a better capacity factor, except for station St6 on the coast of the Souss Massa region and St9 on the shore of the Casablanca Settat region. The Vestas V.164 turbine with a power of 9.5 MW is identified as the optimal choice for all the studied sites, generating these remarkable performances.