Analysis of Wind Resource Potential for Small-Scale Wind Turbine Performance in Kiseveni, Kenya
International Journal of High Energy Physics
Volume 6, Issue 1, June 2019, Pages: 17-29
Received: Feb. 6, 2019;
Accepted: Jun. 17, 2019;
Published: Jul. 9, 2019
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Justus Nzuka Mwanzia, Department of Physics, Jomo Kenyatta University of Agriculture and Technology, Juja, Kenya
David Wafula Wekesa, Department of Physics, Machakos University, Machakos, Kenya
Joseph Ngugi Kamau, Department of Physics, Jomo Kenyatta University of Agriculture and Technology, Juja, Kenya
"Kenya's energy depends on fossil fuels and the country is yet to embrace alternative sources especially in densely populated rural areas and urban poor. The use of wind is gaining popularity because it is cost effective, non-polluting, renewable and enormously available. The main challenge is non-availability of the renewable energy resource data in the rural areas where the bulk of the country’s population resides. The study assessed wind energy potential for Kiseveni area which is a rural site within expansive Mwingi/Kitui plateau in Kitui. The assessment entailed both empirical and numerical approaches by collecting a ten-minute interval wind speed for a period of six months with sensors elevated at 10 m height above the ground. From the collected data, wind speed analysis, wind directional analysis, wind energy and power both empirical and numerical was done to establish the available potential of wind energy at the site. In addition, the study elucidated the computational Fluid Dynamics (CFD) application in addressing wind energy potential at the site and its added value with respect to its empirical approach. The results of the study were used to evaluate the potential for wind energy at the site for small-scale wind turbine application to the power-starved population. Empirical power density ranged between 31.65 W/m 2 to 54.00 W/m2 between 40 m to 100 m hub heights respectively with corresponding numerical power density ranging between 71.76 W/m2 to 125.45 W/m2. Numerical rotor power (PR) and average wind power (PW) were found to be -0.26 and 33.71 W/m2 giving a negative CP for the height. The results of the study reveal that the site corresponds to wind class 1 meaning the wind resource in the area is not suitable for grid connected generation but can run off grid small wind turbines and stand-alone activities like water pumping. "
Justus Nzuka Mwanzia,
David Wafula Wekesa,
Joseph Ngugi Kamau,
Analysis of Wind Resource Potential for Small-Scale Wind Turbine Performance in Kiseveni, Kenya, International Journal of High Energy Physics.
Vol. 6, No. 1,
2019, pp. 17-29.
D. W. Wekesa, C. wang, Y. wei, empirical and numerical analysis of small wind turbine aerodynamic performance at a plateau terrain in kitui county.
B. Mukulo, J. Ngaruiya, J. Kamau, Determination of wind energy potential in the Mwingi-Kitui plateau of Kenya, Renew. Energy 63 (2014) 18-22.
Kenya National Bureau of Statistics, Energy Use in Kitui County, 2009, National population census report, 2010.
Kamau, J. N., 2010: Determination of wind power parameters for the assessment of the wind energy potential for selected sites in Kenya. PHD thesis, JKUAT, march 2010.
D. W. Wekesa, C. Wang, Y. Wei, L. A. M. Danao, Influence of operating conditions on unsteady wind performance of vertical axis wind turbines operating within a fluctuating free-stream: a numerical study, J. Wind Eng. Ind. Aerod. 135 (2014) 76-89.
D. W. Wekesa, C. Wang, Y. Wei, J. N. Kamau, L. A. M. Danao, A numerical analysis of unsteady inflow wind for site specific vertical axis wind turbine: a case study for Marsabit and Garissa in Kenya, Renew. Energy 76 (2015) 32-45.
L. A. Danao, J. Edwards, O. Eboibi, R. Howell, A numerical investigation into the influence of unsteady wind on the performance and aerodynamics of a vertical axis wind turbine, Appl. Energy 116 (2014) 111-124.
L. A. Danao, O. Eboibi, R. Howell, An experimental investigation into the influence of unsteady wind on the performance of a vertical axis wind turbine, Appl. Energy 107 (2013) 403-411.
J. M. Edwards, L. A. Danao, R. J. Howell, Novel experimental power curve determination and computational methods for the performance analysis of vertical axis wind turbines, J. Sol. Energy Eng. 134 (2012) 031008.
S. McTavish, D. Feszty, T. Sankar, Steady and rotating computational fluid dynamics simulations of a novel vertical axis wind turbine for small-scale power generation, Renew. Energy 41 (2012) 171e179. scale horizontal axis wind turbine, Energy 65 (2014) 412-418.
D. W. Wekesa, C. Wang, Y. Wei, J. N. Kamau, Wind resource assessment and numerical simulation for wind turbine airfoils, in: 2014 15th International Workshop on Research and Education in Mechatronics (REM), Egypt, vol. 15, IEEE, 2014, pp. 1e9.
D. W. Wekesa, J. N. Mutuku, J. N. Kamau, Microcontroller-based data logging instrumentation system for wind speed and direction measurements, J. Agric. Sci. Technol. 14 (2012) 176-189.
R. Nobile, M. Vahdati, J. F. Barlow, A. Mewburn-Crook, Unsteady flow simulation of a vertical axis augmented wind turbine: a two-dimensional study, J. Wind Eng. Ind. Aerod. 125 (2014) 168-179.
S. Mcintosh, Wind Energy for the Built Environment, PhD Thesis, Department of Engineering, Cambridge University, 2009, pp. 105-106, 164.
J. Kamau, R. Kinyua, J. Gathua, 6 years of wind data for Marsabit, Kenya average over 14 m/s at 100 m hub height; an analysis of the wind energy potential, Renew. Energy 35 (2010) 1298-1302.
National Renewable Energy Laboratory (NREL), Wind Data Details: http:// www.nrel.gov/gis/wind_detail.html, (accessed 20.10.2018 at 1230hrs EAT).