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All Journal International Journal of Renewable Energy Development
Ajavona, Ayité Sénah Akoda
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Chemistry Energy

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Influence of the Random Data Sampling in Estimation of Wind Speed Resource: Case Study Salami, Adekunlé Akim; Ouedraogo, Seydou; Kodjoa, Koffi Mawugno; Ajavona, Ayité Sénah Akoda
International Journal of Renewable Energy Development Vol 11, No 1 (2022): February 2022
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2022.38511

Abstract

In this study, statistical analysis is performed in order to characterize wind speeds distribution according to different samples randomly drawn from wind speed data collected. The purpose of this study is to assess how random sampling influences the estimation quality of the shape (k) and scale (c) parameters of a Weibull distribution function. Five stations were chosen in West Africa for the study, namely: Accra Kotoka, Cotonou Cadjehoun, Kano Mallam Aminu, Lomé Tokoin and Ouagadougou airport. We used the energy factor method (EPF) to compute shape and scale parameters. Statistical indicators used to assess estimation accuracy are the root mean square error (RMSE) and relative percentage error (RPE). Study results show that good accuracy in Weibull parameters and power density estimation is obtained with sampled wind speed data of 30% for Accra, 20% for Cotonou, 80% for Kano, 20% for Lomé, and 20% for Ouagadougou site. This study showed that for wind potential assessing at a site, wind speed data random sampling is sufficient to calculate wind power density. This is very useful in wind energy exploitation development.
Co-Authors Kodjoa, Koffi Mawugno Ouedraogo, Seydou Salami, Adekunlé Akim