@article{(Open Science Index):https://publications.waset.org/pdf/13911,
	  title     = {Establishing a Probabilistic Model of Extrapolated Wind Speed Data for Wind Energy Prediction},
	  author    = {Mussa I. Mgwatu and  Reuben R. M. Kainkwa},
	  country	= {},
	  institution	= {},
	  abstract     = {Wind is among the potential energy resources which
can be harnessed to generate wind energy for conversion into
electrical power. Due to the variability of wind speed with time and
height, it becomes difficult to predict the generated wind energy more
optimally. In this paper, an attempt is made to establish a
probabilistic model fitting the wind speed data recorded at
Makambako site in Tanzania. Wind speeds and direction were
respectively measured using anemometer (type AN1) and wind Vane
(type WD1) both supplied by Delta-T-Devices at a measurement
height of 2 m. Wind speeds were then extrapolated for the height of
10 m using power law equation with an exponent of 0.47. Data were
analysed using MINITAB statistical software to show the variability
of wind speeds with time and height, and to determine the underlying
probability model of the extrapolated wind speed data. The results
show that wind speeds at Makambako site vary cyclically over time;
and they conform to the Weibull probability distribution. From these
results, Weibull probability density function can be used to predict
the wind energy.},
	    journal   = {International Journal of Mechanical and Mechatronics Engineering},
	  volume    = {6},
	  number    = {10},
	  year      = {2012},
	  pages     = {2055 - 2060},
	  ee        = {https://publications.waset.org/pdf/13911},
	  url   	= {https://publications.waset.org/vol/70},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 70, 2012},
	}