1Equipe de Recherche en Sciences de l’Ingénieur (ERSI), Department of Electrical Engineering, Ecole Nationale Supérieure d’Ingénieurs (ENSI), University of Lomé, BP 1515, Lomé TOGO, Togo
2Polytechnic University of bobo-Dioulasso, Burkina-Faso, Burkina Faso
BibTex Citation Data :
@article{IJRED17815, author = {Adekunlé Salami and Ayité Ajavon and Mawugno Kodjo and Seydou Ouedraogo and Koffi-Sa Bédja}, title = {The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters}, journal = {International Journal of Renewable Energy Development}, volume = {7}, number = {2}, year = {2018}, keywords = {Odd bin wind speed time series, Even bin wind speed time series, Weibull parameters, Statistical analysis, Comparative evaluation.}, 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, R 2 , 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 16 th 2018; Received in revised form May 5 th 2018; Accepted May 27 th 2018; Available online How 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 }, pages = {139--150} doi = {10.14710/ijred.7.2.139-150}, url = {https://ejournal.undip.ac.id/index.php/ijred/article/view/17815} }
Refworks Citation Data :
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 online
How 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
Article Metrics:
Last update:
Analysis and efficient comparison of ten numerical methods in estimating Weibull parameters for wind energy potential: Application to the city of Bafoussam, Cameroon
Estimating mixture hybrid Weibull distribution parameters for wind energy application using Bayesian approach
Comparative Study of Wind Energy Potential Estimation Methods for Wind Sites in Togo and Benin (West Sub-Saharan Africa)
Estimating Weibull Parameters for Wind Energy Applications using Seven Numerical Methods: Case studies of three costal sites in West Africa
Last update: 2024-12-13 11:56:55
Estimating weibull parameters for wind energy applications using seven numerical methods: Case studies of three coastal sites in West Africa
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. Articles are freely available to both subscribers and the wider public with permitted reuse.
All articles published Open Access will be immediately and permanently free for everyone to read and download. We are continuously working with our author communities to select the best choice of license options: Creative Commons Attribution-ShareAlike (CC BY-SA). Authors and readers can copy and redistribute the material in any medium or format, as well as remix, transform, and build upon the material for any purpose, even commercially, but they must give appropriate credit (cite to the article or content), provide a link to the license, and indicate if changes were made. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
International Journal of Renewable Energy Development (ISSN:2252-4940) published by CBIORE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.