Research Article
Wind Power Potential Estimation by Using the Statistical Models-Adama, Ethiopia
@INPROCEEDINGS{10.1007/978-3-030-80621-7_27, author={Endalew Ayenew and Getachew Biru and Asrat Mulatu and Santoshkumar Hampannavar}, title={Wind Power Potential Estimation by Using the Statistical Models-Adama, Ethiopia}, proceedings={Advances of Science and Technology. 8th EAI International Conference, ICAST 2020, Bahir Dar, Ethiopia, October 2-4, 2020, Proceedings, Part I}, proceedings_a={ICAST}, year={2021}, month={7}, keywords={Rayleigh probability distribution Weibull probability distribution Wind power estimation}, doi={10.1007/978-3-030-80621-7_27} }- Endalew Ayenew
Getachew Biru
Asrat Mulatu
Santoshkumar Hampannavar
Year: 2021
Wind Power Potential Estimation by Using the Statistical Models-Adama, Ethiopia
ICAST
Springer
DOI: 10.1007/978-3-030-80621-7_27
Abstract
This paper is aimed to statistically estimate wind power that can be converted to electrical power. It is important to have an inclusive fact of wind phenomena to efficiently plan the generation of power from the wind. To estimate wind power potential, this paper includes daily average wind speeds, monthly average wind speeds, and related wind power density, and frequency distribution based on wind speed probability frequency, Weibull and Rayleigh distributions. The two parameters for Weibull distribution were found out using data from the Adama wind farm site. The yearly average wind power densities for wind velocity frequency distribution, the Weibull distribution, and the Rayleigh distribution models 412 W/m2, 370 W/m2, and 532 W/m2respectively were estimated using wind speed statistics of the 2018 year at the ADAMA wind farm site. The value of estimated wind power density by Rayleigh distribution models is equivalent to maximum power density of the site. The result of this study shows that the selected site has utility-scale potential wind power.
