Geostatistical Modeling of Wind Speed Distribution in Uganda Using Ordinary Kriging Interpolation Technique

Noah Kisuule^1*, Mahmut Cetin², Nicholas Kiggundu¹, and Julia Kigozi¹

Abstract

Wind power is one of the thriving renewable energy technologies lately in the world. Therefore, the assessment of wind speed data is imperative for a specific site. This study focused on geostatistical modeling of wind speed distribution in Uganda. Wind speed data from 1981 to 2019, recorded at a height of 10 m above mean sea level was captured from NASA POWER Data Access Viewer and analyzed. The study area consisted of 35 stations evenly distributed over the country. Probabilistic assessment was performed using Minitab® statistical software to determine the best-fitting probability distribution function to the data sets.  Experimental semi-variograms were calculated using exceedance probability data sets of 20%, 50%, 80%, and 95% obtained from probabilistic analysis. The theoretical models were then fitted to the experimental semi-variograms. Jack-knifing cross-validation approach was employed to assess the performance and validity of the theoretical semi-variogram models and their parameters. Kriging maps for the wind speed of pre-defined probabilities were then generated using JeoStat geostatistical software and Surfers 13®. Of the different theoretical semi-variogram models tested, the spherical model showed the best fit to all experimental semi-variograms. Cross-validation proved that the theoretical models obtained were in good agreement with the experimental data used. The kriging maps revealed that areas around Lake Victoria and Mt. Elgon experience higher wind speeds compared to other parts. Therefore, Kriging maps can be used to assess spatial distribution and magnitude of wind speed as well as the representativeness of geographical locations of observation stations.

Keywords

Geostatistics; wind speed; wind speed distribution; kriging; semi-variogram

Cite This Article

Kisuule, N., Cetin, M., Kiggundu, N., Kiozi, J. (2023). Geostatistical Modeling of Wind Speed Distribution in Uganda Using Ordinary Kriging Interpolation Technique. International Journal of Scientific Advances (IJSCIA), Volume 4| Issue 3: May-Jun 2023, Pages 454-465, URL: https://www.ijscia.com/wp-content/uploads/2023/06/Volume4-Issue3-May-Jun-No.456-454-465.pdf

Volume 4 | Issue 3: May-Jun 2023