Rüzgar Enerji Sistemleri İçin Hava Yoğunluğunun Hesaplanması

Year 2018, Volume: 21 Issue: 2, 273 - 281, 01.06.2018

Ferhat Bingöl

https://doi.org/10.2339/politeknik.385523

Cited By: 2

Abstract

Rüzgar tarlaları son yıllarda
dünyada ve Türkiye’de deniz seviyesindeki alanların yanı sıra yüksek rüzgar
hızı kapasitesine sahip dağlık bölgelerde de kurulmaya başlamıştır. Ancak,
dikkat edilmesi gereken en önemli nokta bu konumlarda hava yoğunluğunun azaldığı
ve bunun da rüzgar türbinlerinden üretim gücüne doğrudan etkilediğidir. Küçük
görünen farklar eğer fizibilite aşamasında yanlış hesaplanırsa uzun yıllar
üretim göz önüne alındığında önemli farklar yaratabilirler. Bu çalışmada
Türkiye'de 126 ölçüm yapılmış nokta için temelde iki farklı yöntem kullanılarak
yoğunluk hesabı yapılmış ve karşılaştırılmıştır. Genel itibariyle, sonuçlar
yıllık ortalamalar dikkate alındığında iki metotta da birbirine yakın çıkmakta
ama aylık ortalamalarda %2 seviyelerine ulaşan üretim tahmininde hatalara yol
açacak farklılıklar göstermektedir.  

Keywords

Rüzgar türbinleri, hava yoğunluğu, fizibilite

Calculation of Air Density for Wind Energy Systems Use

Abstract

In recent years, wind farms are being located at
mountainous high altitude locations in Turkey. Nevertheless, most important
point to pay attention for those locations are that the air density is lower
and this effects the production of wind turbines directly. If the feasibility
calculations are not performed in detail on the subject, small effects of air
density can create a big loss in long term operational wind farms. In this
study, two known methods (i) International standards for calculations and (ii)
widely used engineering method are applied on datasets from 126 weathers
stations all around Turkey and calculations are compared with each other.
Results show similarities on yearly averages but outlines up to 2% differences
in different months of the year.

Keywords

Wind turbines, air density, feasibility

References

• [1] Tu¨rkiye Ru¨zgar Enerjileri Birlig˘i, ˙Istatistik Raporu, Ocak (2017).
• [2] Yenilenebilir Enerjiler Genel Mu¨du¨rlu¨g˘u¨. REPA (˙Il Bazlı Ru¨zgaˆr Enerjisi Potansiyeli Atlası), (2012).
• [3] Jake Badger, Neil Davis, Andrea N. Hahmann, Bjarke Tobias Olsen, Xiaoli Guo Larse´n, Mark C. Kelly, Patrick Volker, Merete Badger, Tobias Torben Ahsbahs, Niels Gylling Mortensen, Hans Ejsing Jørgensen, Erik Lundtang Petersen, Julia Lange, and Nicolas Fichaux. The new worldwide mic- roscale wind resource assessment data on IRENA’s Global Atlas. The EUDP Global Wind Atlas, (2015).
• [4] Ferhat Bingo¨l. Adaptation of Uniform Wind Atlases: Case Study of Turkey. TU¨ B˙ITAK (114C016) Final Report.
• [5] Sinem Deg˘irmenci. Environmental Impact And Capacity Analysis Of Renewable Energy Resources: Case Study Of Wind Energy In Turkey. Master’s thesis, Izmir Institute of Technology, (2016).
• [6] M.O.L. Hansen. Aerodynamics of Wind Turbines. Earthscan, (2013).
• [7] H. Tennekes. The logarithmic wind profile. Journal of the Atmospheric Sciences, 30(2): 234–238, (1973).
• [8] J. C. Kaimal and J. J. Finnigan. Atmospheric Boundary Layer Flows: Their Structure and Measurement. Oxford University Press, (1994).
• [9] R Stull. Meteorology for Scientists & Engineers. Univ. of British Columbia, 3rd edi- tion edition, (2011).
• [10] P Giacomo. Equation for the determination of the density of moist air (1981). Metrolo- gia, 18(1): 33, (1982).
• [11] R S Davis. Equation for the determination of the density of moist air (1981/91). Met- rologia, 29(1): 67, (1992).
• [12] A Picard and H Fang. Three methods of determining the density of moist air during mass comparisons. Metrologia, 39(1): 31, (2002).
• [13] A Picard, H Fang, and M Gla¨ser. Discrepancies in air density determination between the thermodynamic formula and a gravimet- ric method: evidence for a new value of the mole fraction of argon in air. Metrologia, 41(6):396, (2004).
• [14] S Y Park, J S Kim, J B Lee, M B Esler, R S Davis, and R I Wielgosz. A redetermination of the argon content of air for buoyancy corrections in mass standard comparisons. Metrologia, 41(6):387, (2004).
• [15] A Picard, R S Davis, M Gla¨ser, and K Fujii. Revised formula for th density of moist air (cipm-2007). Metrologia, 45(2):149, (2008).
• [16] Wind turbines - part 12-1: Power perfor- mance measurements f electricity producing wind turbines (iec 61400-12-1:2005), (2005).
• [17] Lasse Svenningsen. Power curve air density correction and other power cuve options in windpro. Technical report, EMD Internati- onal A/S,( 2010).
• [18] J.W. Wagenaar and P.J. Eecen. Dependence of power performance o atmospheric conditions and possible corrections. Technical report, ECN Wind Energy, 2011. In Proce- edings at EWEA (2011).
• [19] Mark Young. Power curve measurement ex- periences, and new approaches. In EWEA Resource Assessment Workshop - Dublin, (2013).
• [20] Wind energy generation systems - part 12-1: Power performance measurements of electricity producing wind turbines (iec 61400- 12-1: (2017).
• [21] R. Feistel, D. G. Wright, H.-J. Kretzschmar, E. Hagen, S. Herrmann, and R. Span. Thermodynamic properties of sea air. Ocean Science, 6(1):91–141, (2010).
• [22] Technical University of Denmark. WAsP, Help Documents, version 11 edition, (2014).
• [23] Robert J. Hijmans, Susan E. Cameron, Juan L. Parra, Peter G. Jones, and Andy Jarvis. Very high resolution interpo- lated climate surfaces for global land areas. International Journal of Climatology, 25(15): 1965–1978, (2005).
• [24] H. I. Reuter, A. Nelson, and A. Jarvis. An evaluation of void-filling interpolation methods for SRTM data. International Jour- nal of Geographical Information Science, 21(9): 983–1008, (2007).
• [25] Erik Lundtang Petersen, Ib Troen, Hans Ejsing Jørgensen, and Jakob Mann. The new european wind atlas. Energy Bulletin, 1(17): 34–39, (2014).