Wind power density characterization in arid and semi-arid Taita-Taveta and Garissa counties of Kenya

Abstract

Wind Power Density (WPD) is a crucial parameter that can be used in assessing the potential of a given site for energy development and determining the suitability of wind turbine installation. A 7-year long-term data (2014–2020) of temperature, relative humidity, and wind speeds were obtained from Voi and Garissa synoptic station with a 3-h resolution. The objective of the study was to characterize wind power density in selected arid regions in Kenya. Analysis was performed using Weibull distribution parameters statistical tools i.e. Moment of Methods, Empirical Method (Justus), and Empirical Method (Lyssen), and error analysis using Mean Absolute Percentage Error, Mean Absolute Deviation (MAD), Coefficient of determination (R2) and Root Mean squared Error to determine the WPD accurate characteristics. Results show that Moment of Methods (MoM) performed better compared to other statistical tools, while the Taita Taveta had a better coefficient of Variance (CoV) ranging between 0.20 and 0.28% compared to 0.28–0.43% in Garissa. Based on the wind power density, the sites were found to be within Class II on the wind power classification from IEC and thus not viable for commercial power purposes. Results imply that power produced can be used in supplementing Kenya Offgrid Solar Access Project (KoSAP) which supplements power production used in gazetted marginalized counties by Kenya Power.

Keywords

• Wind power density (WPD)
• Weibull parameters
• Wind power class
• Moment of moments (MoM)
• Standard deviation