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Statistical Estimation of Wind Power Potential At Hamirpur Region in Himachal Pradesh, India
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Abstract
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The wind energy is one of the prominent renewable energy source in India. In this research paper, monthly and annual wind power density (WPD) have been estimated based on the statistical approaches known as Weibull and Rayleigh distribution functions (WDF & RDF) for the hourly time series wind data measured during the year 2013. The main objective of this research has been to estimate the wind power potential at NIT Hamirpur wind monitoring facility of Himachal Pradesh in India and to propose feasibility of wind power plant. The proposed methodology is a new contribution for small and micro power generation for this region. Modeling of wind speed deviation is the most necessary obligation for the design of wind turbines. The variations in monthly and annual mean wind speed, standard deviation, and Weibull parameters along with the frequency distribution format of measured wind speeds have been presented in this paper. The monthly and annual probability density and cumulative distribution function's (CDF) have been derived from the frequency distribution. The probability density of WDF and RDF has been well fitted with the measured probability functions on monthly and yearly basis. The investigation shows that though the particular site is not suitable for grid connected applications yet available wind potential is suitable for isolated standalone systems like rural electrification, house hold electric appliances like battery charging, mechanical applications like water pumping for irrigation etc.
Keywords:
cumulative distribution function (CDF)
Rayleigh distribution function (RDF)
small/micro power generation
wind data
wind speed
Weibull distribution function (WDF)
wind power density (WPD)
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