References
- Y. Shen, C. Zhang, X. Huang, X. Wang, and S. Cen, "The effect of wind speed averaging time on sand transport estimates", Catena, Vol. 175, 2019, pp. 286-293, doi: https://doi.org/10.1016/j.catena.2018.12.020.
- J. E. Stout, "Effect of averaging time on the apparent threshold for aeolian transport", Journal of Arid Environments, Vol. 39, No. 3, 1998, pp. 395-401, doi: https://doi.org/10.1006/jare.1997.0370.
- B. A. Harper, J. D. Kepert, and J. Ginger, "Wind speed time averaging conversions for tropical cyclone conditions", 28th Conference on Hurricanes and Tropical Meteorology, 2008. Retrieved from https://ams.confex.com/ams/28Hurricanes/techprogram/paper_138064.htm.
- Z. Guo, T. M. Zobeck, J. E. Stout, and K. Zhang, "The effect of wind averaging time on wind erosivity estimation", Earth Surface Processes and Landforms, Vol. 37, No. 7, 2012, pp. 797-802, doi: https://doi.org/10.1002/esp.3222.
- S. K. Gulev, "Influence of space-time averaging on the ocean-atmosphere exchange estimates in the North Atlantic midlatitudes", Journal of physical oceanography, Vol. 24, No. 6, 1994, pp. 1236-1255, doi: https://doi.org/10.1175/1520-0485(1994)024<1236:IOSTAO>2.0.CO;2.
- P. D. Clausen and D. H. Wood, "Research and development issues for small wind turbines", Renewable Energy, Vol. 16, No. 1-4, 1999, pp. 922-927, doi: https://doi.org/10.1016/S0960-1481(98)00316-4.
- K. Mohammadi, O. Alavi, A. Mostafaeipour, N. Goudarzi, and M. Jalilvand, "Assessing different parameters estimation methods of Weibull distribution to compute wind power density", Energy Conversion and Management, Vol. 108, 2016, pp. 322-335, doi: https://doi.org/10.1016/j.enconman.2015.11.015.
- E. K. Akpinar, "A statistical investigation of wind energy potential", Energy Sources, Part A, Vol. 28, No. 9, 2006, pp. 807-820, doi: https://doi.org/10.1080/009083190928038.
- L. Bilir, M. Imir, Y. Devrim, and A. Albostan, "An investigation on wind energy potential and small scale wind turbine performance at Incek region-Ankara, Turkey", Energy Conversion and Management, Vol. 103, 2015, pp. 910-923, doi: https://doi.org/10.1016/j.enconman.2015.07.017.
- Carrasco, J. M., Ortega, E. M., and Cordeiro, G. M., "A generalized modified Weibull distribution for lifetime modelling", Computational Statistics & Data Analysis, Vol. 53, No. 2, 2008, pp. 450-462, doi: https://doi.org/10.1016/j.csda.2008.08.023.
- T. P. Chang, "Wind speed and power density analyses based on mixture Weibull and maximum entropy distributions", International Journal of Applied Science and Engineering, Vol. 8, No. 1, 2010, pp. 39-46, doi: https://doi.org/10.6703/IJASE.2010.8(1).39.
- F. O. Hocaoglu, M. Fidan, and O. N. Gerek, "Mycielski approach for wind speed prediction", Energy Conversion and Management, Vol. 50, No. 6, 2009, pp. 1436-1443, doi: https://doi.org/10.1016/j.enconman.2009.03.003.
- C. Ozay and M. S. Celiktas, "Statistical analysis of wind speed using two-parameter Weibull distribution in Alacati region", Energy Conversion and Management, Vol. 121, 2016, pp. 49-54, doi: https://doi.org/10.1016/j.enconman.2016.05.026.
- S. H. Pishgar-Komleh, A. Keyhani, and P. Sefeedpari, "Wind speed and power density analysis based on Weibull and Rayleigh distributions (a case study: Firouzkooh county of Iran)", Renewable and Sustainable Energy Reviews, Vol. 42, 2015, pp. 313-322, doi: https://doi.org/10.1016/j.rser.2014.10.028.
- P. A. C. Rocha, R. C. de Sousa, C. F. de Andrade, and M. E. V. da Silva, "Comparison of seven numerical methods for determining Weibull parameters for wind energy generation in the northeast region of Brazil", Applied Energy, Vol. 89, No. 1, 2012, pp. 395-400, doi: https://doi.org/10.1016/j.apenergy.2011.08.003.
- H. Saleh, A. Abou El-Azm Aly, and S. Abdel-Hady, "Assessment of different methods used to estimate Weibull distribution parameters for wind speed in Zafarana wind farm, Suez Gulf, Egypt", Energy, Vol. 44, No. 1, 2012, pp. 710-719, doi: https://doi.org/10.1016/j.energy.2012.05.021.