Statistical analysis of wind energy potential in Mongo, Chad, for small-scale renewable applications

Abstract

Wind plays a crucial role in various physical applications, including wind energy and pollutant transport and diffusion. Wind varies from both temporal and spatial perspectives. This paper presents a statistical analysis of wind energy potential in Mongo, the capital city of Guéra Province, Chad, using 11 years of data obtained from the local meteorological station. Using the Weibull distribution function, we analyzed the wind speed probability distributions based on the wind data obtained. The obtained results, based on average annual wind speed and energy generation, indicate that Mongo is suitable only for small-scale wind energy applications. The average wind speed within the chosen time interval is 3.2 m/s, which is classified as Class 1 according to the international system of wind classification. Wind rose plots illustrate that the wind directions vary across the years. The temperature data were also plotted, reporting an average temperature of 27.76°C over the 11-year study period. This indicates that Mongo has a relatively hot climate, which may contribute to the modest but consistent wind speeds observed in this city.

Keywords

Wind energy potential / Renewable energy / Wind and temperature data / Weibull distribution function

Funding

None.

Conflict of interest

The authors declare that they have no competing interests.

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