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A Model for Evaluating the Basic Wake Effect in the Calculation of Wind Turbine Power Output on Offshore Wind Power Plant

Year 2019, , 1 - 9, 30.06.2019
https://doi.org/10.31466/kfbd.531554

Abstract

One of the most important topics of offshore
Wind Power Plant (WPP) installation is the wake effect of the wind turbines on
each other. This situation reduces annual energy production of WPP. WPP
installation should be performed by considering the loss of production due to
the wake effect. Nowadays, many methods are used for calculation of wake
effect. Among these methods, the Jensen method is mostly preferred due to the
simple and high degree of accuracy. In this study, Wake effect between two wind
turbines is modeled by using Jensen method for variable wind velocities and
frequencies at the same elevation in a region. The model is formed in the
Matrix Laboratory (MATLAB) software development environment. Also, Wind Atlas
Analysis and Application Program (WAsP) software is used to verify the former
model. In this software, two wind turbines are placed in offshore region. In
this case, gross and net production values of turbines were calculated. When
the results of MATLAB and commercially used WAsP model results were compared,
the approximately same production values were obtained. These results show that
the developed model can be used in calculations in offshore WPP.

References

  • Asta S., (2013). A. survey on recent off-shore wind farm layout optimization methods, technical report. Nottingham, UK: University of Nottingham.
  • Barthelmie, R.J., Folkerts, L., Larsen, G.C., Rados, K., Pryor, S.C., Frandsen, S.T. (2005). Comparison of wake model simulations with offshore wind turbine wake profiles measured by sodar. J Atmospheric Ocean Technology, 23, 881-901.
  • Barthelmie, R.J, Hansen K., Frandsen, S.T., Rathmann, O., Schepers, J.G., Schlez, W. (2009). Modeling and measuring flow and wind turbine wakes in large wind farms offshore. Wind Energy, 12: 431-444.
  • Barthelmie, R.J., Jensen, L.E. (2010). Evaluation of wind farm efficiency and wind turbine wakes at the nysted offshore wind farm. Wind Energy, 13, 573-586.
  • Crastoa, G., Gravdahla, A., Castellanib, F., Piccionib, E. (2012). Wake modeling with the actuator disc concept. Energy Procedia, 24, 385-392.
  • Crespo, A., Hernandez, J., Frandsen, S.T. (1999). Survey of modelling methods for wind turbine wakes and wind farms. Wind Energy, 2, 1-24.
  • Emami, A., Noghreh, P. (2010). New approach on optimization in placement of wind turbines within wind farm by genetic algorithms. Renew Energy, 35: 1559-1564.
  • Frandsen, S.T. (1992). On the wind speed reduction in the center of large clusters of wind turbines. Journal of Wind Eng Ind Aerodyn, 39: 251-256.
  • Jensen, N. (1983). A note on wind turbine interaction. Technical report Ris-M-2411. Roskilde, Denmark: Risø National Laboratory.
  • Katic, I., Højstrup, J., Jensen, N. (1986). A simple model for cluster efficiency. In: Proceedings of the European wind energy association conference and exhibition, Rome, Italy.
  • Kiranoudis, C.T., Maroulis, Z.B. (1997). Effective short-cut modelling of wind park efficiency. Renew Energy, 11, 439-457.
  • Kusiak, A., Song, Z. (2010). Design of wind farm layout for maximum wind energy capture. Renew Energy, 35, 685-694.
  • Marmidis, G., Lazarou, S., Pyrgloti, E. (2008). Optimal placement of wind turbines in a wind park using Monte Carlo simulation. Renew Energy, 33, 1455-1460.
  • Nielsen, M., Jørgensen, H. E., Frandsen, S. T. (2009). Wind and wake models for IEC 61400-1 site assessment. In EWEC 2009 Proceedings online EWEC.
  • Porté-Agel, F., Wu, Y.T., Chen, C-H. (2013). A numerical study of the effects of wind direction on turbine wakes and power losses in a large wind farm. Energies, 6 (10), 5297-313.
  • Turner, S.D.O., Romero, D.A., Zhang, P.Y., Amon, C.H., Chan, T.C.Y. (2014). A new mathematical programming approach to optimize wind farm layouts. Renewable Energy , 63, 674-680.
  • Thøgersen, M.L. (2005). Wind PRO/PARK: introduction to wind turbine wake modelling and wake generated turbulence. Technical report. Niels Jernes Vej 10, DK9220 Aalborg, Denmark: EMD International A/S.
  • URL-1: Foxwell, D. (2019). https://www.owjonline.com/news/view,5-ways-offshore-wind-will-continue-todiversify-in-2019_56228.htm, (Erişim Tarihi: 21 Şubat 2019).
  • URL-2: 2Bonus 2MW Turbine , https://en.wind-turbine-models.com/turbines/121-bonus-b76-2000, (Erişim Tarihi: 21 Şubat 2019).
  • Vermeer, L, Sørensen, J., Crespo, A. (2003). Wind turbine wake aerodynamics. Prog Aerosp Sci, 39, 467-510.

Deniz üstü Rüzgâr Enerji Santrallerinde Rüzgâr Türbini Çıkış Gücü Hesabında Temel İz Etkisinin Değerlendirilmesi için Bir Model

Year 2019, , 1 - 9, 30.06.2019
https://doi.org/10.31466/kfbd.531554

Abstract

Deniz üstü Rüzgâr enerjisi santrali (RES)
kurulumunda en önemli konulardan birisi de rüzgâr türbinlerinin iz etkisidir.
Bu durum RES'in yıllık üretimini düşürmektedir. Bu nedenle RES kurulumunda iz
etkisi sonucu meydana gelen üretim kaybı dikkate alınarak RES kurulumu
gerçekleştirilmelidir. Günümüzde iz etkisi hesabında birçok yöntem
kullanılmaktadır. Bu yöntemler arasında basit ve yüksek derecede doğruluğa
sahip olan Jensen yöntemi daha çok tercih edilmektedir. Bu çalışmada, iki
rüzgâr türbini arasındaki iz etkisi, bir bölgede aynı yükseklikteki değişken
rüzgâr hızları ve frekansları için Jensen yöntemi kullanılarak modellenmiştir.
Model, Matris Laboratuvarı (MATLAB) yazılım geliştirme ortamında
oluşturulmuştur. Ayrıca oluşturulan modeli doğrulamak için Rüzgâr Atlası Analiz
ve Uygulama Programı (WAsP) yazılımı kullanılmıştır. Bu yazılımda iki rüzgâr
türbini deniz kıyısında uzakta bir bölgeye yerleştirilmiştir. Bu duruma ilişkin
türbinlerin brüt üretim ve net üretim değerleri hesaplanmıştır. MATLAB modeli
sonuçları ve ticari olarak kullanılan WAsP modeli sonuçları
karşılaştırıldığında yaklaşık olarak aynı üretim değerleri elde edilmiştir. Bu
sonuçlar geliştirilen modelin deniz üstü RES’lerde yapılacak hesaplamalarda
kullanılabileceğini göstermektedir.

References

  • Asta S., (2013). A. survey on recent off-shore wind farm layout optimization methods, technical report. Nottingham, UK: University of Nottingham.
  • Barthelmie, R.J., Folkerts, L., Larsen, G.C., Rados, K., Pryor, S.C., Frandsen, S.T. (2005). Comparison of wake model simulations with offshore wind turbine wake profiles measured by sodar. J Atmospheric Ocean Technology, 23, 881-901.
  • Barthelmie, R.J, Hansen K., Frandsen, S.T., Rathmann, O., Schepers, J.G., Schlez, W. (2009). Modeling and measuring flow and wind turbine wakes in large wind farms offshore. Wind Energy, 12: 431-444.
  • Barthelmie, R.J., Jensen, L.E. (2010). Evaluation of wind farm efficiency and wind turbine wakes at the nysted offshore wind farm. Wind Energy, 13, 573-586.
  • Crastoa, G., Gravdahla, A., Castellanib, F., Piccionib, E. (2012). Wake modeling with the actuator disc concept. Energy Procedia, 24, 385-392.
  • Crespo, A., Hernandez, J., Frandsen, S.T. (1999). Survey of modelling methods for wind turbine wakes and wind farms. Wind Energy, 2, 1-24.
  • Emami, A., Noghreh, P. (2010). New approach on optimization in placement of wind turbines within wind farm by genetic algorithms. Renew Energy, 35: 1559-1564.
  • Frandsen, S.T. (1992). On the wind speed reduction in the center of large clusters of wind turbines. Journal of Wind Eng Ind Aerodyn, 39: 251-256.
  • Jensen, N. (1983). A note on wind turbine interaction. Technical report Ris-M-2411. Roskilde, Denmark: Risø National Laboratory.
  • Katic, I., Højstrup, J., Jensen, N. (1986). A simple model for cluster efficiency. In: Proceedings of the European wind energy association conference and exhibition, Rome, Italy.
  • Kiranoudis, C.T., Maroulis, Z.B. (1997). Effective short-cut modelling of wind park efficiency. Renew Energy, 11, 439-457.
  • Kusiak, A., Song, Z. (2010). Design of wind farm layout for maximum wind energy capture. Renew Energy, 35, 685-694.
  • Marmidis, G., Lazarou, S., Pyrgloti, E. (2008). Optimal placement of wind turbines in a wind park using Monte Carlo simulation. Renew Energy, 33, 1455-1460.
  • Nielsen, M., Jørgensen, H. E., Frandsen, S. T. (2009). Wind and wake models for IEC 61400-1 site assessment. In EWEC 2009 Proceedings online EWEC.
  • Porté-Agel, F., Wu, Y.T., Chen, C-H. (2013). A numerical study of the effects of wind direction on turbine wakes and power losses in a large wind farm. Energies, 6 (10), 5297-313.
  • Turner, S.D.O., Romero, D.A., Zhang, P.Y., Amon, C.H., Chan, T.C.Y. (2014). A new mathematical programming approach to optimize wind farm layouts. Renewable Energy , 63, 674-680.
  • Thøgersen, M.L. (2005). Wind PRO/PARK: introduction to wind turbine wake modelling and wake generated turbulence. Technical report. Niels Jernes Vej 10, DK9220 Aalborg, Denmark: EMD International A/S.
  • URL-1: Foxwell, D. (2019). https://www.owjonline.com/news/view,5-ways-offshore-wind-will-continue-todiversify-in-2019_56228.htm, (Erişim Tarihi: 21 Şubat 2019).
  • URL-2: 2Bonus 2MW Turbine , https://en.wind-turbine-models.com/turbines/121-bonus-b76-2000, (Erişim Tarihi: 21 Şubat 2019).
  • Vermeer, L, Sørensen, J., Crespo, A. (2003). Wind turbine wake aerodynamics. Prog Aerosp Sci, 39, 467-510.
There are 20 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

İbrahim Çelik 0000-0001-5923-554X

Ceyhun Yıldız 0000-0002-5498-4127

Mustafa Şekkeli 0000-0002-1641-3243

Publication Date June 30, 2019
Published in Issue Year 2019

Cite

APA Çelik, İ., Yıldız, C., & Şekkeli, M. (2019). Deniz üstü Rüzgâr Enerji Santrallerinde Rüzgâr Türbini Çıkış Gücü Hesabında Temel İz Etkisinin Değerlendirilmesi için Bir Model. Karadeniz Fen Bilimleri Dergisi, 9(1), 1-9. https://doi.org/10.31466/kfbd.531554