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WIND ENERGY POWER POTENTIAL OF MARDİN AND POLATLI REGIONS IN TURKEY

Year 2019, Volume: 1 Issue: 1, 1 - 15, 30.06.2019

Abstract

Despite the high wind energy
potential in Turkey, electric power generation using wind energy is quite low.
Thus, the results obtained from studies on wind power have become extremely
important. In the present study, the wind energy potential of two regions in
Turkey was estimated
in
accordance with the data obtained from Turkish State Meteorological Service. First, suitable distribution for wind speed
data was specified by Anderson-Darling and Kolmogorov-Smirnov
goodness-of-fit tests. The Weibull distribution was determined to be the
best fit distribution for wind speed data. The parameters of the Weibull
distribution were estimated by the moment method, least squares method, and
modified maximum likelihood method, which are commonly used methods in the literature.
The parameters obtained were placed in the power density function and the power
density was computed for the two regions. This study provides approximate
information about the wind energy potential of the regions examined.

References

  • Abbas, K., Khalil, A., Khan, S.A., Ali, A., Khan, D.M., and Khalil, U. (2012), Statistical Analysis of Wind Speed Data in Pakistan, World Applied Sciences Journal, 18(11): 1533-1539.
  • Adekoya, L.O., and Adewale, A.A. (1992), Wind Energy Potential of Nigeria, Renewable Energy, 2(1): 35-39.
  • Akdağ, S.A., and Güler, Ö. (2008), Weibull Dağılım Parametrelerini Belirleme Metodlarının Karşılaştırılması, VII. Ulusal Temiz Enerji Sempozyumu, 707-714.
  • Akpınar, E.K., and Akpınar, S. (2005), An Assessment on Seasonal Analysis of Wind Energy Characteristics and Wind Turbine Characteristics, Energy Conversion and Management, 46(11-12): 1848-1867.
  • Akpınar, E.K. (2006), A Statistical Investigation of Wind Energy Potential, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 28(9): 807-820.
  • Bilgili, M., Şahin, B., and Şimşek, E. (2010), Wind Energy Density in The Southern, Southwestern and Western Region of Turkey, Journal of Thermal Science and Technology, 30(1): 1-12.
  • Chang, T.P. (2011), Performance Comparison of Six Numerical Methods in Estimating Weibull Parameters for Wind Energy Application, Applied Energy, Elsevier, 88(1): 272-282.
  • Çelik, A.N. (2003), A Statistical Analysis of Wind Power Density Based on The Weibull and Rayleigh Models at The Southern Region of Turkey, Renewable Energy, 29(4): 593-604.
  • Çetin, N.S. (2001), Küçük Güçlü Bir Rüzgâr Türbini Tasarımı ve Elektrik Enerjisi Eldesi, VI. Türk Alman Enerji Sempozyumu Kitapçığı, 83-93.
  • Erişoğlu, M. (2003), Use of Statistical Estimation Techniques in The Estimation of The Parameters of Weibull Distribution and Application of Weibull Distribution to Earthquake Data, Thesis of Master Degree, pp: 119.
  • Gülersoy, T., and Çetin, N.S. (2010), Using the Weibull and Rayleigh Distributions for the Wind Turbines in Menemen, Turkey, Journal of Polytechnic, 13(3): 209-213.
  • Islam, M.R., Saidur, R., and Rahim, N.A. (2011), Assessment of Wind Energy Potentiality at Kudat and Labuan, Malaysia Using Weibull Distribution Function, Energy, 36(2): 985-992.
  • Karagali, I., Pena, A., Badger, M., and Hasager, C.B. (2014), Wind Characteristics in The North and Baltic Seas from The QuikSCAT Satellite, Wind Energy, 17(1): 123-140.
  • Koçaslan, G. (2010), Sürdürülebilir Kalkınma Hedefi Çerçevesinde Türkiye’nin Rüzgâr Enerjisi Potansiyelinin Yeri ve Önemi, Sosyal Bilimler Dergisi, 4: 53-61.
  • Kurban, M., Hocaoğlu, F.O., and Kantar, M.Y. (2007), The Comparative Analysis of Two Different Statistical Distributions Used to Estimate The Wind Energy Potential, Pamukkale Unıversity Engineering College Journal of Engineering Sciences, 13(1): 103-109.
  • Kurban, M., Kantar, M.Y., and Hocaoğlu, F.O. (2007b), Statistical Analysis of Wind Speed and Power Densities Using Weibull Distribution, Afyon Kocatepe University Journal of Science, 7(2): 205-218.
  • Nayir, A., and Pecen, R. (2011), Yenilenebilir Enerji Sistemleri Gözlemleme ve Uygulama Laboratuarı, Elektrik-Elektronik ve Bilgisayar Sempozyumu (FEEB 2011) Bildiriler kitabı, Elazığ, 279-283.
  • Saenko, A.V. (2008), Assessment of Wind Energy Resources for Residential Use in Victoria, BC, Canada. Thesis of Master Degree.
  • Şahin, A.D., Dinçer, I., and Rosen, M.A. (2006), Thermodynamic Analysis of Wind Energy, International Journal of Energy Research, 30(8): 553-566.
  • Şahin, B., Bilgili, M., and Akıllı, H. (2005), The Wind Power Potential of the Eastern Mediterranean Region of Turkey, Journal of Wind Engineering and Industrial Aerodynamics, 93(2): 171–183.
  • Ülgen, K., and Hepbaşlı, A. (2002), Determination of Weibull Parameters for Wind Energy Analysis of Izmir, Turkey, International Journal of Energy Research, 26(6): 495-506.
  • Yıldırım, U., Gazibey, Y., and Güngör, A. (2012), Wind Energy Potential of Niğde Province, Nigde University Journal of Engineering Sciences, 1(2): 37-47.
  • Yılmaz, V., Aras, H., and Çelik, H.E. (2005), Rüzgâr Hız Verilerinin İstatistiksel Analizi, Eskişehir Osmangazi Üniversitesi Müh. Mim. Fak. Dergisi, 18: 45-54.
  • Yılmaz, V., and Çelik, H.E. (2008), A Statistical Approach to Estimate the Wind Speed Distribution: The Case of Gelibolu Region, Doğuş Üniversitesi Dergisi, 9(1): 122-132.

TÜRKİYE’DE MARDİN VE POLATLI BÖLGELERİNİN RÜZGAR ENERJİSİ GÜÇ POTANSİYELİ

Year 2019, Volume: 1 Issue: 1, 1 - 15, 30.06.2019

Abstract

Rüzgâr enerji potansiyeli ülkemizde yüksek olmasına
rağmen rüzgâr enerjisi kullanımı ile elektrik enerjisi üretimi oldukça azdır.
Bu yüzden rüzgâr gücüne dayalı olarak yapılan çalışmalardan elde edilen
sonuçlar son derece önemli hale gelmiştir.
Bu çalışmada Devlet
Meteoroloji Genel Müdürlüğü’nden elde edilen verilere göre Türkiye’deki iki
bölgenin rüzgâr enerji potansiyeli tahmin edilmiştir. İlk olarak
Kolmogorov-Smirnov ve Anderson-Darling uygunluk testleri ile rüzgâr hızı
verileri için uygun dağılım belirlenmiştir. Rüzgâr hızı verileri için Weibull
dağılımının en uygun dağılım olduğu saptanmıştır. Literatürde genel olarak
kullanılan moment yöntemi, düzeltilmiş en çok olabilirlik yöntemi ve en küçük
kareler yöntemi ile Weibull dağılımının parametreleri tahmin edilmiştir. Elde
edilen bu parametreler güç yoğunluğu fonksiyonunda yerine koyularak bu iki
bölge için güç yoğunluğu hesaplanmıştır.
Bu çalışma incelenen bölgelerin rüzgâr enerji potansiyelleri
konusunda yaklaşık olarak bilgi vermektedir.

References

  • Abbas, K., Khalil, A., Khan, S.A., Ali, A., Khan, D.M., and Khalil, U. (2012), Statistical Analysis of Wind Speed Data in Pakistan, World Applied Sciences Journal, 18(11): 1533-1539.
  • Adekoya, L.O., and Adewale, A.A. (1992), Wind Energy Potential of Nigeria, Renewable Energy, 2(1): 35-39.
  • Akdağ, S.A., and Güler, Ö. (2008), Weibull Dağılım Parametrelerini Belirleme Metodlarının Karşılaştırılması, VII. Ulusal Temiz Enerji Sempozyumu, 707-714.
  • Akpınar, E.K., and Akpınar, S. (2005), An Assessment on Seasonal Analysis of Wind Energy Characteristics and Wind Turbine Characteristics, Energy Conversion and Management, 46(11-12): 1848-1867.
  • Akpınar, E.K. (2006), A Statistical Investigation of Wind Energy Potential, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 28(9): 807-820.
  • Bilgili, M., Şahin, B., and Şimşek, E. (2010), Wind Energy Density in The Southern, Southwestern and Western Region of Turkey, Journal of Thermal Science and Technology, 30(1): 1-12.
  • Chang, T.P. (2011), Performance Comparison of Six Numerical Methods in Estimating Weibull Parameters for Wind Energy Application, Applied Energy, Elsevier, 88(1): 272-282.
  • Çelik, A.N. (2003), A Statistical Analysis of Wind Power Density Based on The Weibull and Rayleigh Models at The Southern Region of Turkey, Renewable Energy, 29(4): 593-604.
  • Çetin, N.S. (2001), Küçük Güçlü Bir Rüzgâr Türbini Tasarımı ve Elektrik Enerjisi Eldesi, VI. Türk Alman Enerji Sempozyumu Kitapçığı, 83-93.
  • Erişoğlu, M. (2003), Use of Statistical Estimation Techniques in The Estimation of The Parameters of Weibull Distribution and Application of Weibull Distribution to Earthquake Data, Thesis of Master Degree, pp: 119.
  • Gülersoy, T., and Çetin, N.S. (2010), Using the Weibull and Rayleigh Distributions for the Wind Turbines in Menemen, Turkey, Journal of Polytechnic, 13(3): 209-213.
  • Islam, M.R., Saidur, R., and Rahim, N.A. (2011), Assessment of Wind Energy Potentiality at Kudat and Labuan, Malaysia Using Weibull Distribution Function, Energy, 36(2): 985-992.
  • Karagali, I., Pena, A., Badger, M., and Hasager, C.B. (2014), Wind Characteristics in The North and Baltic Seas from The QuikSCAT Satellite, Wind Energy, 17(1): 123-140.
  • Koçaslan, G. (2010), Sürdürülebilir Kalkınma Hedefi Çerçevesinde Türkiye’nin Rüzgâr Enerjisi Potansiyelinin Yeri ve Önemi, Sosyal Bilimler Dergisi, 4: 53-61.
  • Kurban, M., Hocaoğlu, F.O., and Kantar, M.Y. (2007), The Comparative Analysis of Two Different Statistical Distributions Used to Estimate The Wind Energy Potential, Pamukkale Unıversity Engineering College Journal of Engineering Sciences, 13(1): 103-109.
  • Kurban, M., Kantar, M.Y., and Hocaoğlu, F.O. (2007b), Statistical Analysis of Wind Speed and Power Densities Using Weibull Distribution, Afyon Kocatepe University Journal of Science, 7(2): 205-218.
  • Nayir, A., and Pecen, R. (2011), Yenilenebilir Enerji Sistemleri Gözlemleme ve Uygulama Laboratuarı, Elektrik-Elektronik ve Bilgisayar Sempozyumu (FEEB 2011) Bildiriler kitabı, Elazığ, 279-283.
  • Saenko, A.V. (2008), Assessment of Wind Energy Resources for Residential Use in Victoria, BC, Canada. Thesis of Master Degree.
  • Şahin, A.D., Dinçer, I., and Rosen, M.A. (2006), Thermodynamic Analysis of Wind Energy, International Journal of Energy Research, 30(8): 553-566.
  • Şahin, B., Bilgili, M., and Akıllı, H. (2005), The Wind Power Potential of the Eastern Mediterranean Region of Turkey, Journal of Wind Engineering and Industrial Aerodynamics, 93(2): 171–183.
  • Ülgen, K., and Hepbaşlı, A. (2002), Determination of Weibull Parameters for Wind Energy Analysis of Izmir, Turkey, International Journal of Energy Research, 26(6): 495-506.
  • Yıldırım, U., Gazibey, Y., and Güngör, A. (2012), Wind Energy Potential of Niğde Province, Nigde University Journal of Engineering Sciences, 1(2): 37-47.
  • Yılmaz, V., Aras, H., and Çelik, H.E. (2005), Rüzgâr Hız Verilerinin İstatistiksel Analizi, Eskişehir Osmangazi Üniversitesi Müh. Mim. Fak. Dergisi, 18: 45-54.
  • Yılmaz, V., and Çelik, H.E. (2008), A Statistical Approach to Estimate the Wind Speed Distribution: The Case of Gelibolu Region, Doğuş Üniversitesi Dergisi, 9(1): 122-132.
There are 24 citations in total.

Details

Primary Language English
Subjects Statistics
Journal Section Articles
Authors

Mehmet Sandal 0000-0001-7396-0801

Murat Doğan 0000-0002-8932-9587

Publication Date June 30, 2019
Published in Issue Year 2019 Volume: 1 Issue: 1

Cite

APA Sandal, M., & Doğan, M. (2019). WIND ENERGY POWER POTENTIAL OF MARDİN AND POLATLI REGIONS IN TURKEY. Nicel Bilimler Dergisi, 1(1), 1-15.