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Mawugno Koffi Kodjo, Mawugno Koffi
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Chemistry Energy

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Estimating Weibull Parameters for Wind Energy Applications using Seven Numerical Methods: Case studies of three costal sites in West Africa Guenoukpati, Agbassou; Salami, Adekunlé Akim; Kodjo, Mawugno Koffi; Napo, Kossi
International Journal of Renewable Energy Development Vol 9, No 2 (2020): July 2020
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.9.2.217-226

Abstract

In this study, the effectiveness of seven numerical methods is evaluated to determine the shape (K) and scale (C) parameters of Weibull distribution function for the purpose of calculating the wind speed characteristics and wind power density. The selected methods are graphical method (GPM), empirical method of Justus (EMJ), empirical method of Lysen (EML), energy pattern factor method (EPFM), maximum likelihood method (MLM) moment method (MOM) and the proposed. Hybrid method (HM) derived from EPFM and EMJ. The purpose is to identify the most appropriate method for computing the mean wind speed, wind speed standard deviation and wind power density for different costal locations in West Africa. Three costal sites (Lomé, Accra and Cotonou) are selected. The input data was collected, from January 2004 to December 2015 for Lomé site, from January 2009 to December 2015 for Accra site and from January 2009 to December 2012 for Cotonou. The results indicate that the precision of the computed mean wind speed, wind speed standard deviation and wind power density values change when different parameters estimation methods are used. Five of them which are EMJ, EML, EPF, MOM, ML, and HM method present very good accuracy while GPM shows weak ability for all three sites. 
The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters Salami, Adekunlé Akim; Ajavon, Ayité Sénah Akoda; Kodjo, Mawugno Koffi; Ouedraogo, Seydou; Bédja, Koffi-Sa
International Journal of Renewable Energy Development Vol 7, No 2 (2018): July 2018
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.7.2.139-150

Abstract

In this article, we introduced a new approach based on graphical method (GPM), maximum likelihood method (MLM), energy pattern factor method (EPFM), empirical method of Justus (EMJ), empirical method of Lysen (EML) and moment method (MOM) using the even or odd classes of wind speed series distribution histogram with 1 m/s as bin size to estimate the Weibull parameters. This new approach is compared on the basis of the resulting mean wind speed and its standard deviation using seven reliable statistical indicators (RPE, RMSE, MAPE, MABE, R2, RRMSE and IA). The results indicate that this new approach is adequate to estimate Weibull parameters and can outperform GPM, MLM, EPF, EMJ, EML and MOM which uses all wind speed time series data collected for one period. The study has also found a linear relationship between the Weibull parameters K and C estimated by MLM, EPFM, EMJ, EML and MOM using odd or even class wind speed time series and those obtained by applying these methods to all class (both even and odd bins) wind speed time series. Another interesting feature of this approach is the data size reduction which eventually leads to a reduced processing time.Article History: Received February 16th 2018; Received in revised form May 5th 2018; Accepted May 27th 2018; Available onlineHow to Cite This Article: Salami, A.A., Ajavon, A.S.A., Kodjo, M.K. , Ouedraogo, S. and Bédja, K. (2018) The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters. Int. Journal of Renewable Energy Development 7(2), 139-150.https://doi.org/10.14710/ijred.7.2.139-150
Evaluation of wind potential for an optimum choice of wind turbine generator on the sites of Lomé, Accra, and Cotonou located in the gulf of Guinea Salami, Akim Adekunlé; Ajavon, Ayité Sénah Akoda; Kodjo, Mawugno Koffi; Bedja, Koffi-Sa
International Journal of Renewable Energy Development Vol 5, No 3 (2016): October 2016
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.5.3.211-223

Abstract

This work presents the characterization and assessment of wind energy potential in annual and monthly levels of the sites of Lomé, Accra and Cotonou located in the Gulf of Guinea, and the optimal characteristics of wind turbines to be installed on these sites. Studies of characterization and the wind potential of these sites from the wind speed data collected over a period of thirteen years at a height of 10 meters above the ground, show an annual average speed of 3.52 m/s for Lomé, 3.99 m/s for Cotonou and 4.16 m/s for Accra. These studies also showed that a monthly average speed exceeding 4 m/s was observed on the sites of Cotonou and Accra during the months of February, March, April, July, August and September and during the months of July, August and September on the site of Lomé. After a series of simulation conducted using the software named PotEol that we have developed in Scilab, we have retained that the wind turbines rated speeds of ~8 to 9 m/s at the sites of Lomé and Cotonou and ~ 9 to 10 m/s on the site of Accra would be the most appropriate speeds for optimal exploitation of electric energy from wind farms at a height of 50 m above the ground.Article History: Received May 26th 2016; Received in revised form August 24th 2016; Accepted August 30th 2016; Available onlineHow to Cite This Article: Salami, A.A., Ajavon, A.S.A , Kodjo, M.K. and Bédja, K. (2016) Evaluation of Wind Potential for an Optimum Choice of Wind Turbine Generator on the Sites of Lomé, Accra, and Cotonou Located in the Gulf of Guinea. Int. Journal of Renewable Energy Development, 5(3), 211-223.http://dx.doi.org/10.14710/ijred.5.3.211-223
Co-Authors Ajavon, Ayité Sénah Akoda Bédja, Koffi-Sa Guenoukpati, Agbassou Koffi-Sa Bedja, Koffi-Sa Napo, Kossi Ouedraogo, Seydou Salami, Adekunlé Akim Salami, Akim Adekunlé