Accurate wind resource assessment is fundamental to developing wind power, a key contributor to a sustainable energy future. This study presents a comparative analysis of the wind potential in Sabratha and Msallata, Libya, using 2017-2018 meteorological data for Msallata and online data for Sabratha, then Wind speed data were processed and fitted to probability distributions using EasyFit software,which identified the Burr and Johnson SB distributions as the best fit, as determined by Kolmogorov-Smirnov and Anderson-Darling tests. Mean monthly wind speed at 10m height was 5–8 m/s for Msallata and 5–11 m/s for Sabratha, corresponding to a wind power density (WPD) of 76.92–289.1 W/m² and 97.08–390.81 W/m², respectively. This classifies both sites as having good-to-very good wind potential. A technical assessment of various wind turbines identified the Winwind-1MW and ENERCON-E53 models as the most efficient, achieving capacity factors exceeding 40%. These results demonstrate a highly productive synergy between the local wind regimes and specific turbine technologies, providing critical insights for future wind energy projects in western Libya.
Rabee Ahmeed (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: