Wind Energy Potential of Yozgat Province Based on the Hub Height and Wind Speed

Abstract

The amount of potential wind energy to be generated in Yozgat province was calculated depending on the hub height (m) and wind speed (m/sec) in this study. The data of 85 wind power plants installed and operating in Turkey were utilized. The data of the amount of produced energy (kWh) in these wind power plants belonged to the year 2018. The Multi-factor Anova method was employed in order to statistically analyze the significance levels of the data set. For the methodology part of the study, tower height and wind speed were determined as input factors and the amount of energy produced selected as the output factor. As a result of the statistical analysis, it was observed that both input factors were effective on the output variable. In line with these results, the potential energy amounts to be produced by the wind power plants to be established in Yozgat province have been calculated. According to the results, it was understood that Yozgat is a suitable region for wind power plants depending on the parameters and variables considered in this study.

Keywords

• Wind Energy
• ANOVA
• Hub Height
• Wind Speed

References

1. [1] Y. A. Atalan, M. Tayanç, K. Erkan, and A. Atalan, “Development of nonlinear optimization models for wind power plants using box-Behnken design of experiment: A case study for Turkey,” Sustain., 2020.
2. [2] H. ŞAHİN, “SİMAV’DAKİ SERALARIN ISITILMASINDA JEOTERMAL ENERJİ KULLANIM OLANAKLARI,” J. Acad. Soc. Sci. Stud., vol. 6, no. Number: 47, pp. 459–459, Jan. 2016.
3. [3] E. Koç and M. C. Şenel, “Dünyada ve Turkiye’de Enerji Durumu - Genel Değerlendirme,” Muhendis ve Makina, 2013.
4. [4] S. Y. Özkaya, “Yenilenebilir Enerji Kaynakları,” Uluslararası Ekon. Sorunlar Derg., vol. 14, 2004.
5. [5] Y. Kumar et al., “Wind energy: Trends and enabling technologies,” Renewable and Sustainable Energy Reviews. 2016.
6. [6] H. Gençel and İ. Tarhan, “Rüzgar Enerjisinin Önemli Geçiş Yerlerinden Olan Çanakkale Bölgesindeki Bazı Rüzgar Enerji Santralleri için Kapasite Faktörü İncelemesi,” Çanakkale Onsekiz Mart Üniversitesi Fen Bilim. Enstitüsü Derg., 2019.
7. [7] Umair Shahzad, “The Need For Renewable Energy Sources,” Int. J. Inf. Technol. Electr. Eng., 2012.
8. [8] N. L. Panwar, S. C. Kaushik, and S. Kothari, “Role of renewable energy sources in environmental protection: A review,” Renew. Sustain. Energy Rev., vol. 15, no. 3, pp. 1513–1524, 2011.

9. [9] O. Ellabban, H. Abu-Rub, and F. Blaabjerg, “Renewable energy resources: Current status, future prospects and their enabling technology,” Renewable and Sustainable Energy Reviews. 2014.
10. [10] Enerji ve Tabii Kaynaklar Bakanlığı, “Rüzgar,” Enerji ve Tabii Kaynaklar Bakanlığı, 2021. [Online]. Available: https://enerji.gov.tr/bilgi-merkezi-enerji-ruzgar.
11. [11] BP Statistical Review of World Energy, “Statistical Review of World Energy, 2020 | 69th Edition,” 2020.
12. [12] Z. R. Shu, Q. S. Li, and P. W. Chan, “Statistical analysis of wind characteristics and wind energy potential in Hong Kong,” Energy Convers. Manag., vol. 101, pp. 644–657, Sep. 2015.
13. [13] T. P. Chang, “Estimation of wind energy potential using different probability density functions,” Appl. Energy, vol. 88, no. 5, pp. 1848–1856, May 2011.
14. [14] S. Jung and S.-D. Kwon, “Weighted error functions in artificial neural networks for improved wind energy potential estimation,” Appl. Energy, vol. 111, pp. 778–790, Nov. 2013.
15. [15] M. S. Gross and V. Magar, “Offshore wind energy potential estimation using UPSCALE climate data,” Energy Sci. Eng., 2015.
16. [16] S. Chatterjee and A. S. Hadi, Regression Analysis by Example. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006.
17. [17] D. C. Montgomery, Design and Analysis of Experiments. 2012.
18. [18] A. I. Khuri, “Introduction to Linear Regression Analysis, Fifth Edition by Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining,” Int. Stat. Rev., 2013.
19. [19] G. K. F. Tso and K. K. W. Yau, “Predicting electricity energy consumption: A comparison of regression analysis, decision tree and neural networks,” Energy, vol. 32, no. 9, pp. 1761–1768, Sep. 2007.
20. [20] T.C. Enerji ve Tabii Kaynaklar Bakanlığı, “YILLIK ORTALAMA RÜZGAR HIZI DAĞILIMI – 100 METRE,” REPA, 2021. [Online]. Available: https://repa.enerji.gov.tr/REPA/iller/YOZGAT-REPA.pdf.