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Wind Power Density Estimation Using Rayleigh Probability Distribution Function
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DOI：10.1007/978-981-13-1819-1_26.png)
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The main aim of this paper is technical assessment of wind power for the complex hilly region of Hamirpur located in Himachal Pradesh, India. The wind data was recorded for 60 min interval for the year 2013 at this specific site at the measured height of 18.5 from above ground level. This time series wind data has been adopted to the Rayleigh distribution function for estimating the wind power density on monthly and annual basis. A Rayleigh model alone is applied for the first time to this specific site, which is the novelty and original contribution of this paper. Further, the monthly and annual disparities of the different wind resource characteristics namely, average wind speed, standard deviation, the frequency distribution, scale parameter (c) have been analyzed on the same time frames. Also, Rayleigh probability and cumulative distribution function have been computed by assuming shape parameter (k) is equal to 2, remains constant throughout the computational analysis. The monthly and year wise wind variability have been conveyed through the probability and cumulative distribution plots and it is derived from the measured data at this investigated site. Finally, the estimated annual wind power density showing 8.86 W/m(2) corresponding to the scale parameter 1.31 m/s. Hence, the outcome of this research work has been recognized that available wind resource is most suitable for micro and small wind power applications like standalone isolated systems, rural electrification, battery charging, home electricity appliances, irrigation of water by pumping through small wind mills.
Keyword:
Probability
Density function
Rayleigh distribution
Wind power density
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