International Journal of Mathematics Trends and Technology
Volume 68 | Issue 6 | Year 2022 | Article Id. IJMTT-V68I6P509 | DOI : https://doi.org/10.14445/22315373/IJMTT-V68I6P509
| Received | Revised | Accepted | Published |
|---|---|---|---|
| 17 Apr 2022 | 30 May 2022 | 04 Jun 2022 | 25 Jun 2022 |
Wind speed as a renewable energy source, therefore wind speed data is needed to produce statistical modeling, especially in determining the best probability density function. for this purpose, several modified Gamma distributions will be used and tested to determine the best model to describe wind speed in Pekanbaru. the main goal of this study is to find the best fitting distribution to the daily wind speed measured over Pekanbaru region for the years 1999-2020 by using the four modified Gamma distributions. the maximum likelihood method will be used to get the estimated parameter value from the distribution used in this study. the distributions will be selected based on graphical inspection probability density function (pdf), cumulative distribution function (cdf) and numerical criteria (Akaike’s information criterion (AIC). in most the cases, graphical inspection gave the same result but their AIC result differed. the best fit result was chosen as the distribution with the lowest values of AIC. in general, the Sujatha distribution has been selected as the best model.
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Arian Syaputra, Rado Yendra, Muhammad Marizal, Ari Pani Desvina, Rahmadeni, "Wind Speed Modelling using Some Modified Gamma Distribution," International Journal of Mathematics Trends and Technology (IJMTT), vol. 68, no. 6, pp. 87-95, 2022. Crossref, https://doi.org/10.14445/22315373/IJMTT-V68I6P509
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