A comparative analysis of wind power density prediction methods for Çanakkale, Intepe region, Turkey

Yasemin Oner, Selin Ozcira, Nur Bekiroglu and Ibrahim Senol

Renewable and Sustainable Energy Reviews, 2013, vol. 23, issue C, 491-502

Abstract: Wind is an environmentally natural and a renewable source of energy. In most parts of the world, wind energy has been utilized as an energy source. In some developed countries, particularly in Europe, the global climate change issue has been the main cause of the wind energy developments. In parallel to these developments, the importance dedicated to the renewable energies has risen in recent years in Turkey; and the number of renewable energy operated power plants has gradually increased as a result. Determination of the potential has the priority for the energy generation from wind power studies. The present study attempts to review and discuss the status and potential of Çanakkale—Intepe region in Turkey with a focus on wind energy. Wind energy resource assessment was carried out by using WAsP software. The average wind speed data and the potential wind energy generation are determined using dominant wind directions, speeds, and the frequency distribution in between 2009 and 2010 for Çanakkale—Intepe region. The results show that the total average of wind speed for the year is 4.26m/s and average power density is 115.5W/m2. Besides wind speed frequencies has been compared with the Weibull, Rayleigh and Normal distribution functions. As a result the Wiebull distribution suits and verifies the actual values. According to the analysis the most frequent wind speed is notably high. The obtained data are classified based on the measurement elevations and the energy potentials were determined using reliable meteorological measurements. Some practical data and considerations given in this study can be used by a company keen to invest in the wind potential in Intepe. A possible wind farm design was performed in the mentioned region.

Keywords: Wind energy; Wind resource assessment; Numerical wind prediction; Wind farm (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (9)

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DOI: 10.1016/j.rser.2013.01.052

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