Document Type : Research Article
Authors
Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
Abstract
Introduction
Considering the low cost of the wind power production and its relatively good compatibility with the environment, wind farms have shown extensive growth in the past few years. Considering the importance of using the wind power and its advantages, the careful planning is needed to identify the available generation potentials in a region or a country to facilitate its increased use. By the end of 2009, the capacity of wind turbines installed in the wind farms of Iran was 92 MW, which demonstrates the significant potential for additional wind farms in the country and suggests investments in the wind power industry are likely cost effective. The main purpose of this research is to assess the potential of wind power for the city of Pars Abad in northwestern Iran.
Materials and Methods
In order to measure wind power density and wind energy potential, wind speed data collected every 3 hours at a height of 30 m above the ground for 11 consecutive years are analyzed; the data are provided by the Iranian Meteorological Organization and are used in the assessment of electricity production potential in the area chosen for the wind turbines installation. To determine the wind energy potential at a site and estimate the energy output from this site, statistical functions like probability functions are used. There are many probability functions but the Weibull distribution function is usually considered the most useful function for wind speed data analysis due to its simplicity and good accuracy. The Weibull probability density function is defined with two parameters of k and c as follows:
(1) f (v) = k/(c ) 〖( v/c )〗^(k-1) exp (- 〖( v/c )〗^k )
After calculating the Weibull function parameters, status of a location for wind energy potential can be assessed. A good way to assess the available wind resources is by calculation of the wind power density. This parameter indicates how much energy can be converted to electricity at a site and can be calculated as follows:
(2) P/A=1/2 ρc^3 Г ( (k+3)/k)
Wind energy density expresses the wind power density for a given time period T.The wind energy density for a definite site and in a given time period (one month or one year) (T) can be calculated as:
(3) E/A=1/2 ρc^3 Г ((k+3)/k) T
Results and Discussion
In this study, wind speed data collected in Parsabad, Iran, over a ten-year period (2005-2015) are analyzed, and the Weibull distribution parameters c and k, average wind speed, and average wind power and wind energy densities are determined.
According to Table 1, the minimum and maximum standard deviations of the average monthly indicators during 11 years in November and July are 0.63 and 2.51, respectively, and the minimum and maximum wind speeds of the average monthly indicators during 11 years in November and June are 2.09 ms-1 and 4.87 ms-1, respectively. The average annual Weibull scale parameter (c) is 3.84 while the average annual Weibull shape parameter (k) is 2.61. The average annual wind power density (P/A) during 11 years is 45 Wm-2, while the average annual wind energy density (E/A) during 11 years is 389 kWhm-2/year. Pars Abad in terms of generation potential of wind energy and based on quantitative classification for wind resource is located in weak to average region.
Conclusion
Pars Abad with an average wind power density of 45 Wm-2 and average wind speed of 3.41 ms-1 is not a good candidate for wind power plants and it is just suitable for off-grid electrical and mechanical applications such as charging batteries and pumping water for agricultural and livestock uses.
Keywords
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