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Mehdi Hashemi-Tilehnoee, Mehdi
IAU-Energy Engineeing
Chemistry Energy

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Assessment of Wind Energy Potential in Golestan Province of Iran Hashemi-Tilehnoee, Mehdi; Khaleghi, Masoud; Babayani, Dayan
International Journal of Renewable Energy Development Vol 5, No 1 (2016): February 2016
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.5.1.25-31

Abstract

Renewable energy sources are estimated to have a thriving future in many countries as well as Iran. The aim of this work is the evaluation of wind energy potentiality for the five counties of Golestan province in the northern region of Iran. A long term data source, consisting of  30 years in Gorgan, 22 years in Gonbade-e Qabus, 21 years in Maraveh Tappeh, 9 years in Aliabad, and 7 years in Bandar-e Turkaman of eight-hourly mean wind data, was adopted and analyzed. Mean wind power based on quantified data, Weibull distribution function, the relative percentage error (RPE) and wind direction between obtaining values of wind power has been considered. According to these data, it was found that the numerical values of the shape parameter and scale parameter for Golestan varied a tight range. Annual values of ‘‘k’’ ranged from 2.7 to 4.7 where it is constant in different elevation because of better performance of this method in estimating wind energy potential, while annual values of ‘‘c’’ were in the range of 2.6 m/s in 10 m and 7.6 m/s in 40 m. Wind power densities have been estimated and relatively low for large wind turbines. The consequences indicate that in some months Maraveh Tappeh and Bandar-e Turkaman has best wind energy potential, as class 2, in order to establish some small wind turbine models for the sustainable development of Golestan province. Article History: Received Sept 13, 2015; Received in revised form Dec 27, 2015; Accepted January 17, 2016; Available online How to Cite This Article: Babayani, D., Khaleghi, M. and Hashemi-Tilehnoee, M. (2016) Assessment of Wind Energy Potential in Golestan Province of Iran. Int. Journal of Renewable Energy Development, 5(1), 25-31. http://dx.doi.org/10.14710/ijred.5.1.25-31 
Evaluating wind energy potential in Gorgan–Iran using two methods of Weibull distribution function Hashemi-Tilehnoee, Mehdi; Babayani, Dayan; Khaleghi, Masoud
International Journal of Renewable Energy Development Vol 5, No 1 (2016): February 2016
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.5.1.43-48

Abstract

In this study, wind energy characteristics of the, a city in northeast of Iran, measured at 10m height in 2014. The Gorgan airport one hour recorded data extrapolated to 50m height. The data have been statistically analyzed hourly, daily, monthly, seasonally and annually to determine the wind power potential. Weibull distribution function has been used to determine the wind power density and then the potential energy. Standard deviation method and power density method are the methods used to calculate the scaling and shaping parameters of the Weibull distribution function. The annual mean wind power calculated by the standard deviation method and the power density method is 38.98w/m2 and 41.32w/m2, respectively. By comparing the results concluded that the power density method is a better method than the standard deviation method. In addition, Gorgan wind energy potentiality categorized into class 1. So is unsuitable to utilize large wind energy turbine. Article History: Received November 21, 2015; Received in revised form January 15, 2016; Accepted February 10, 2016; Available onlineHow to Cite This Article: Babayani, D., Khaleghi, M., Tashakor, S., and Hashemi-Tilehnoee.,M. (2016) Evaluating wind energy potential in Gorgan–Iran using two methods of Weibull distribution function. Int. Journal of Renewable Energy Development, 5(1), 43-48.http://dx.doi.org/10.14710/ijred.5.1.43-48 
Co-Authors Dayan Babayani, Dayan Masoud Khaleghi, Masoud