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Rüzgarı Hasat Etmek: Türkiye'de Rüzgar Enerjisinin Fizibilitesi ve Gelişmeleri Üzerine Bir Araştırma

Year 2023, Issue: 49, 43 - 49, 31.03.2023
https://doi.org/10.31590/ejosat.1261573

Abstract

Konvansiyonel yanıcı (fosil) yakıtların (kömür, madeni yağ ve doğal gaz) rezervleri, bugünkü hızla kullanılması halinde 50 ila 200 yıl içinde tükenecektir. Doğal gaz, petrol, kömür veya nükleer gibi konvansiyonel enerji kaynakları sınırlıyken, rüzgar, güneş, biyogaz/biyokütle, jeotermal vb. gibi yenilenebilir enerji kaynakları temizdir ve doğada bol miktarda mevcuttur. Yenilebilir enerji kaynaklarından olan rüzgar enerjisi temiz, emisyonsuz bir enerji üretim teknolojisidir. Rüzgar enerjisi, üstün özellikleri, yenilenebilir enerji, geniş dağıtım ve sıfır kirlilik nedeniyle “yeşil enerji”nin ana destekçilerinden biridir.
Bu çalışma, son yıllarda yapılan araştırmalara dayanarak rüzgar enerjisinin potansiyelini tartışmaktadır. Çalışmada öncelikle rüzgar enerjisi kavramı kapsamlı bir şekilde anlatılacak, rüzgar enerjisi kullanımının avantaj ve dezavantajlarına değinilecektir. Daha sonra rüzgar enerjisi santrali bileşenlerinden rüzgar türbinleri üzerinde durulacaktır. Rüzgar türbinleri türleri ve özellikleri açıklanacaktır. Son olarak Türkiye’nin rüzgar ve rüzgar enerjisi potansiyeli hakkında bilgi verilecektir. Araştırmanın sonuç kısmında ise araştırmada elde edilen bilgilere dayanılarak, Türkiye’nin rüzgar enerjisi gücünün gelişimine yönelik önerilerde bulunulacaktır.

References

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  • Archer, C. L., & Jacobson, M. Z. (2005). Evaluation of global wind power. Journal of Geophysical Research: Atmospheres, 110(D12).
  • Argüeso, D., & Businger, S. (2018). Wind power characteristics of Oahu, Hawaii. Renewable energy, 128, 324-336.
  • Atılgan, S. (2022). Forecasting and economic analysis of electricity consumption and wind turbine production in line with sustainable development. (Unpublished Master Thesis). Batman University Graduate Education Institute, Batman
  • Begec, H. (2022). Investigation of the Use of Wind Turbines in High Buildings, Journal of Eksen Dokuz Eylul University Faculty of Architecture, 3 (2), 1-18. DOI: 10.58317/axis.1082215
  • Beig, A., & Muyeen, S. M. (2015). Wind energy. In Electric Renewable Energy Systems (pp. 60-77).
  • Boulouiha, H. M., Allali, A., & Denai, M. (2017). Grid integration of wind energy systems: Control design, stability, and power quality issues. In Clean energy for sustainable development (pp. 239-335). AcademicPress.
  • Caliskan, M. (2019). Turkey Wind Energy Potential. https://www.mgm.gov.tr/FILES/haberler/2010/rets-seminer/2_Mustafa_CALISKAN_RITM.pdf
  • Demolli, H., Dokuz, A. S., Ecemis, A., & Gokcek, M. (2019). Wind power forecasting based on daily wind speed data using machine learning algorithms. Energy Conversion and Management, 198, 111823.
  • Esteban, M. D., Diez, J. J., López, J. S., & Negro, V. (2011). Why offshore wind energy?. Renewable energy, 36(2), 444-450.
  • Günhan, N. E. M. (2020). Numerical analysis of small scale vertical axis wind turbines (Doctoral dissertation, Bursa Uludag University).
  • Kalmikov, A. (2017). Wind power fundamentals. In Wind Energy Engineering (pp. 17-24). AcademicPress.
  • Köktürk, G., & Tokuç, A. (2017). Vision for wind energy with a smart grid in Izmir. Renewable and Sustainable energy reviews, 73, 332-345.
  • Malkoç, Y. (2008). Our Wind Energy Resources. Electrical Works Survey Administration General, 84. https://www.emo.org.tr/ekler/5237d34f69ddac7_ek.pdf
  • Mustafakulov, A. A., & Arzikulov, F. (2020). Current State Of Wind Power Industry. The American Journal of Engineering and Technology, 2(09), 32–36. https://doi.org/10.37547/tajet/Volume02Issue09-05
  • Özkan, A., Uslu, Y. & Gedikli, E. (2022). Wind Power in Turkey's Renewable Energy Potential and the Example of Denmark. Mediterranean FEAS Journal, 22 (2), 26-35. DOI: 10.25294/auiibfd.1111423
  • Pryor, S. C., Barthelmie, R. J., Bukovsky, M. S., Leung, L. R., & Sakaguchi, K. (2020). Climate change impacts on wind power generation. Nature Reviews Earth & Environment, 1(12), 627-643.
  • Rogner, H. H., & Popescu, A. (2001). World energy assessment [Chapter 1:An introduction to energy].
  • Sharifian, A., Ghadi, M. J., Ghavidel, S., Li, L., & Zhang, J. (2018). A new method based on Type-2 fuzzy neural network for accurate wind power forecasting under uncertain data. Renewable energy, 120, 220-230.
  • Şenel, M. C., & Koç, E. (2015). Wind energy situation in the world and in Turkey-General evaluation. Engineer and Machinery, 56(663), 46-56.
  • Wang, Y., Zou, R., Liu, F., Zhang, L., & Liu, Q. (2021). A review of wind speed and wind power forecasting with deep neural networks. Applied Energy, 304, 117766.
  • Yilmaz, M. (2022). Comparative analysis of Turkey's regional wind energy potential using distribution functions (Master's thesis, Bilecik Şeyh Edebali University, Institute of Science and Technology).

Harvesting the Wind: A Study on theFeasibility and Advancements of Wind Energy in Turkey

Year 2023, Issue: 49, 43 - 49, 31.03.2023
https://doi.org/10.31590/ejosat.1261573

Abstract

This research delves into the potential of wind energy, drawing on recent studies to explore its advantages and disadvantages. The study will begin by providing a comprehensive explanation of the concept of wind energy, followed by an in-depth analysis of wind turbines, which are key components of wind power plants. This will involve a discussion of the various types of wind turbines and their individual characteristics. The research will also examine Turkey's wind and wind energy potential, providing valuable insights into the country's renewable energy prospects. In conclusion, the findings of this study will be used to propose recommendations for the development of wind energy in Turkey. Overall, the study aims to highlight the significance of wind energy as a clean, abundant, and sustainable source of power, and to explore ways in which it can be harnessed to meet the energy needs of the future.

References

  • Ammar, N., Sulaiman, M., & Nor, A. F. M. (2018). Long-term load forecasting of power systems using artificial neural network and ANFIS. ARPN Journal of Engineering and Applied Sciences, 13(3), 828-834.
  • Archer, C. L., & Jacobson, M. Z. (2005). Evaluation of global wind power. Journal of Geophysical Research: Atmospheres, 110(D12).
  • Argüeso, D., & Businger, S. (2018). Wind power characteristics of Oahu, Hawaii. Renewable energy, 128, 324-336.
  • Atılgan, S. (2022). Forecasting and economic analysis of electricity consumption and wind turbine production in line with sustainable development. (Unpublished Master Thesis). Batman University Graduate Education Institute, Batman
  • Begec, H. (2022). Investigation of the Use of Wind Turbines in High Buildings, Journal of Eksen Dokuz Eylul University Faculty of Architecture, 3 (2), 1-18. DOI: 10.58317/axis.1082215
  • Beig, A., & Muyeen, S. M. (2015). Wind energy. In Electric Renewable Energy Systems (pp. 60-77).
  • Boulouiha, H. M., Allali, A., & Denai, M. (2017). Grid integration of wind energy systems: Control design, stability, and power quality issues. In Clean energy for sustainable development (pp. 239-335). AcademicPress.
  • Caliskan, M. (2019). Turkey Wind Energy Potential. https://www.mgm.gov.tr/FILES/haberler/2010/rets-seminer/2_Mustafa_CALISKAN_RITM.pdf
  • Demolli, H., Dokuz, A. S., Ecemis, A., & Gokcek, M. (2019). Wind power forecasting based on daily wind speed data using machine learning algorithms. Energy Conversion and Management, 198, 111823.
  • Esteban, M. D., Diez, J. J., López, J. S., & Negro, V. (2011). Why offshore wind energy?. Renewable energy, 36(2), 444-450.
  • Günhan, N. E. M. (2020). Numerical analysis of small scale vertical axis wind turbines (Doctoral dissertation, Bursa Uludag University).
  • Kalmikov, A. (2017). Wind power fundamentals. In Wind Energy Engineering (pp. 17-24). AcademicPress.
  • Köktürk, G., & Tokuç, A. (2017). Vision for wind energy with a smart grid in Izmir. Renewable and Sustainable energy reviews, 73, 332-345.
  • Malkoç, Y. (2008). Our Wind Energy Resources. Electrical Works Survey Administration General, 84. https://www.emo.org.tr/ekler/5237d34f69ddac7_ek.pdf
  • Mustafakulov, A. A., & Arzikulov, F. (2020). Current State Of Wind Power Industry. The American Journal of Engineering and Technology, 2(09), 32–36. https://doi.org/10.37547/tajet/Volume02Issue09-05
  • Özkan, A., Uslu, Y. & Gedikli, E. (2022). Wind Power in Turkey's Renewable Energy Potential and the Example of Denmark. Mediterranean FEAS Journal, 22 (2), 26-35. DOI: 10.25294/auiibfd.1111423
  • Pryor, S. C., Barthelmie, R. J., Bukovsky, M. S., Leung, L. R., & Sakaguchi, K. (2020). Climate change impacts on wind power generation. Nature Reviews Earth & Environment, 1(12), 627-643.
  • Rogner, H. H., & Popescu, A. (2001). World energy assessment [Chapter 1:An introduction to energy].
  • Sharifian, A., Ghadi, M. J., Ghavidel, S., Li, L., & Zhang, J. (2018). A new method based on Type-2 fuzzy neural network for accurate wind power forecasting under uncertain data. Renewable energy, 120, 220-230.
  • Şenel, M. C., & Koç, E. (2015). Wind energy situation in the world and in Turkey-General evaluation. Engineer and Machinery, 56(663), 46-56.
  • Wang, Y., Zou, R., Liu, F., Zhang, L., & Liu, Q. (2021). A review of wind speed and wind power forecasting with deep neural networks. Applied Energy, 304, 117766.
  • Yilmaz, M. (2022). Comparative analysis of Turkey's regional wind energy potential using distribution functions (Master's thesis, Bilecik Şeyh Edebali University, Institute of Science and Technology).
There are 22 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Barış Ayar 0000-0002-6897-8705

Zehra Gulten Yalçın 0000-0001-5460-289X

Mustafa Dağ 0000-0001-9540-3475

Early Pub Date March 25, 2023
Publication Date March 31, 2023
Published in Issue Year 2023 Issue: 49

Cite

APA Ayar, B., Yalçın, Z. G., & Dağ, M. (2023). Rüzgarı Hasat Etmek: Türkiye’de Rüzgar Enerjisinin Fizibilitesi ve Gelişmeleri Üzerine Bir Araştırma. Avrupa Bilim Ve Teknoloji Dergisi(49), 43-49. https://doi.org/10.31590/ejosat.1261573